Tue, 08 Aug 2023

Package walker updated to version 1.0.7 with previous version 1.0.6-1 dated 2022-10-16

Title: Bayesian Generalized Linear Models with Time-Varying Coefficients
Description: Efficient Bayesian generalized linear models with time-varying coefficients as in Helske (2022, <doi:10.1016/j.softx.2022.101016>). Gaussian, Poisson, and binomial observations are supported. The Markov chain Monte Carlo (MCMC) computations are done using Hamiltonian Monte Carlo provided by Stan, using a state space representation of the model in order to marginalise over the coefficients for efficient sampling. For non-Gaussian models, the package uses the importance sampling type estimators based on approximate marginal MCMC as in Vihola, Helske, Franks (2020, <doi:10.1111/sjos.12492>).
Author: Jouni Helske [aut, cre]
Maintainer: Jouni Helske <jouni.helske@iki.fi>

Diff between walker versions 1.0.6-1 dated 2022-10-16 and 1.0.7 dated 2023-08-08

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 15 files changed, 156 insertions(+), 154 deletions(-)

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Package tiler updated to version 0.3.0 with previous version 0.2.5 dated 2021-02-20

Title: Create Geographic and Non-Geographic Map Tiles
Description: Creates geographic map tiles from geospatial map files or non-geographic map tiles from simple image files. This package provides a tile generator function for creating map tile sets for use with packages such as 'leaflet'. In addition to generating map tiles based on a common raster layer source, it also handles the non-geographic edge case, producing map tiles from arbitrary images. These map tiles, which have a non-geographic, simple coordinate reference system (CRS), can also be used with 'leaflet' when applying the simple CRS option. Map tiles can be created from an input file with any of the following extensions: tif, grd and nc for spatial maps and png, jpg and bmp for basic images. This package requires 'Python' and the 'gdal' library for 'Python'. 'Windows' users are recommended to install 'OSGeo4W' (<https://trac.osgeo.org/osgeo4w/>) as an easy way to obtain the required 'gdal' support for 'Python'.
Author: Matthew Leonawicz [aut, cre] , Alex M Chubaty [ctb]
Maintainer: Matthew Leonawicz <mfleonawicz@gmail.com>

Diff between tiler versions 0.2.5 dated 2021-02-20 and 0.3.0 dated 2023-08-08

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Package swfscAirDAS updated to version 0.3.0 with previous version 0.2.3 dated 2022-06-01

Title: Southwest Fisheries Science Center Aerial DAS Data Processing
Description: Process and summarize aerial survey 'DAS' data (AirDAS) <https://swfsc-publications.fisheries.noaa.gov/publications/TM/SWFSC/NOAA-TM-NMFS-SWFSC-185.PDF> collected using an aerial survey program from the Southwest Fisheries Science Center (SWFSC) <https://www.fisheries.noaa.gov/west-coast/science-data/california-current-marine-mammal-assessment-program>. PDF files detailing the relevant AirDAS data formats are included in this package.
Author: Sam Woodman [aut, cre]
Maintainer: Sam Woodman <sam.woodman@noaa.gov>

Diff between swfscAirDAS versions 0.2.3 dated 2022-06-01 and 0.3.0 dated 2023-08-08

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Package restatapi updated to version 0.21.2 with previous version 0.20.6 dated 2023-03-09

Title: Search and Retrieve Data from Eurostat Database
Description: Eurostat is the statistical office of the European Union and provides high quality statistics for Europe. Large set of the data is disseminated through the Eurostat database (<https://ec.europa.eu/eurostat/web/main/data/database>). The tools are using the REST API with the Statistical Data and Metadata eXchange (SDMX) Web Services (<https://wikis.ec.europa.eu/pages/viewpage.action?pageId=44165555>) to search and download data from the Eurostat database using the SDMX standard.
Author: Matyas Meszaros [aut, cre], Sebastian Weinand [ctb]
Maintainer: Matyas Meszaros <matyas.meszaros@ec.europa.eu>

Diff between restatapi versions 0.20.6 dated 2023-03-09 and 0.21.2 dated 2023-08-08

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Package LogicReg updated to version 1.6.6 with previous version 1.6.5 dated 2022-10-31

Title: Logic Regression
Description: Routines for fitting Logic Regression models. Logic Regression is described in Ruczinski, Kooperberg, and LeBlanc (2003) <DOI:10.1198/1061860032238>. Monte Carlo Logic Regression is described in and Kooperberg and Ruczinski (2005) <DOI:10.1002/gepi.20042>.
Author: Charles Kooperberg <clk@fredhutch.org> and Ingo Ruczinski <ingo@jhu.edu>
Maintainer: Charles Kooperberg <clk@fredhutch.org>

Diff between LogicReg versions 1.6.5 dated 2022-10-31 and 1.6.6 dated 2023-08-08

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Package dLagM updated to version 1.1.12 with previous version 1.1.8 dated 2022-05-10

Title: Time Series Regression Models with Distributed Lag Models
Description: Provides time series regression models with one predictor using finite distributed lag models, polynomial (Almon) distributed lag models, geometric distributed lag models with Koyck transformation, and autoregressive distributed lag models. It also consists of functions for computation of h-step ahead forecasts from these models. See Demirhan (2020)(<doi:10.1371/journal.pone.0228812>) and Baltagi (2011)(<doi:10.1007/978-3-642-20059-5>) for more information.
Author: Haydar Demirhan [aut, cre, cph]
Maintainer: Haydar Demirhan <haydar.demirhan@rmit.edu.au>

Diff between dLagM versions 1.1.8 dated 2022-05-10 and 1.1.12 dated 2023-08-08

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Package BiocManager updated to version 1.30.22 with previous version 1.30.21.1 dated 2023-07-18

Title: Access the Bioconductor Project Package Repository
Description: A convenient tool to install and update Bioconductor packages.
Author: Martin Morgan [aut] , Marcel Ramos [aut, cre]
Maintainer: Marcel Ramos <marcel.ramos@roswellpark.org>

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Package aggTrees updated to version 2.0.1 with previous version 2.0.0 dated 2023-02-21

Title: Aggregation Trees
Description: Nonparametric data-driven approach to discovering heterogeneous subgroups in a selection-on-observables framework. Aggregation trees allow researchers to assess whether there is relevant heterogeneity in treatment effects. The approach generates a sequence of optimal groupings, one for each level of granularity. For each grouping, we obtain point estimation and inference about the Group Average Treatment Effects. Please reference the use as Di Francesco (2022) <doi:10.2139/ssrn.4304256>.
Author: Riccardo Di Francesco [aut, cre]
Maintainer: Riccardo Di Francesco <difrancesco.riccardo96@gmail.com>

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Package prioritizr updated to version 8.0.3 with previous version 8.0.2 dated 2023-05-01

Title: Systematic Conservation Prioritization in R
Description: Systematic conservation prioritization using mixed integer linear programming (MILP). It provides a flexible interface for building and solving conservation planning problems. Once built, conservation planning problems can be solved using a variety of commercial and open-source exact algorithm solvers. By using exact algorithm solvers, solutions can be generated that are guaranteed to be optimal (or within a pre-specified optimality gap). Furthermore, conservation problems can be constructed to optimize the spatial allocation of different management actions or zones, meaning that conservation practitioners can identify solutions that benefit multiple stakeholders. To solve large-scale or complex conservation planning problems, users should install the Gurobi optimization software (available from <https://www.gurobi.com/>) and the 'gurobi' R package (see Gurobi Installation Guide vignette for details). Users can also install the IBM CPLEX software (<https://www.ibm.com/products [...truncated...]
Author: Jeffrey O Hanson [aut] , Richard Schuster [aut, cre] , Nina Morrell [aut], Matthew Strimas-Mackey [aut] , Brandon P M Edwards [aut] , Matthew E Watts [aut], Peter Arcese [aut] , Joseph Bennett [aut] , Hugh P Possingham [aut]
Maintainer: Richard Schuster <richard.schuster@glel.carleton.ca>

Diff between prioritizr versions 8.0.2 dated 2023-05-01 and 8.0.3 dated 2023-08-08

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 man/add_cuts_portfolio.Rd                                  |  208 
 man/add_default_solver.Rd                                  |   90 
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 man/add_feature_weights.Rd                                 |  504 +-
 man/add_gap_portfolio.Rd                                   |  218 
 man/add_gurobi_solver.Rd                                   |  490 +-
 man/add_highs_solver.Rd                                    |  192 
 man/add_linear_constraints.Rd                              |  590 +-
 man/add_linear_penalties.Rd                                |  498 +-
 man/add_locked_in_constraints.Rd                           |  552 +-
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 man/add_loglinear_targets.Rd                               |  264 -
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 man/add_mandatory_allocation_constraints.Rd                |  174 
 man/add_manual_bounded_constraints.Rd                      |  338 -
 man/add_manual_locked_constraints.Rd                       |  334 -
 man/add_manual_targets.Rd                                  |  550 +-
 man/add_max_cover_objective.Rd                             |  354 -
 man/add_max_features_objective.Rd                          |  288 -
 man/add_max_phylo_div_objective.Rd                         |  480 +-
 man/add_max_phylo_end_objective.Rd                         |  486 +-
 man/add_max_utility_objective.Rd                           |  274 -
 man/add_min_largest_shortfall_objective.Rd                 |  286 -
 man/add_min_set_objective.Rd                               |  226 
 man/add_min_shortfall_objective.Rd                         |  280 -
 man/add_neighbor_constraints.Rd                            |  437 -
 man/add_proportion_decisions.Rd                            |  164 
 man/add_relative_targets.Rd                                |  346 -
 man/add_rsymphony_solver.Rd                                |  218 
 man/add_semicontinuous_decisions.Rd                        |  178 
 man/add_shuffle_portfolio.Rd                               |  210 
 man/add_top_portfolio.Rd                                   |  186 
 man/adjacency_matrix.Rd                                    |  200 
 man/binary_stack.Rd                                        |  106 
 man/boundary_matrix.Rd                                     |  206 
 man/branch_matrix.Rd                                       |   88 
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 man/feature_names.Rd                                       |   96 
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 man/new_waiver.Rd                                          |   58 
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 tests/testthat/test_Waiver.R                               |   16 
 tests/testthat/test_add_absolute_targets.R                 |  608 +-
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 tests/testthat/test_add_cbc_solver.R                       |  576 +-
 tests/testthat/test_add_connectivity_penalties.R           |  686 +-
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 tests/testthat/test_add_feature_contiguity_constraints.R   | 1024 ++--
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 tests/testthat/test_add_gurobi_solver.R                    |  576 +-
 tests/testthat/test_add_highs_solver.R                     |  524 +-
 tests/testthat/test_add_linear_constraints.R               | 1260 ++---
 tests/testthat/test_add_linear_penalties.R                 | 1134 ++--
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 tests/testthat/test_add_max_cover_objective.R              | 1268 ++---
 tests/testthat/test_add_max_features_objective.R           | 1510 +++---
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 tests/testthat/test_add_max_phylo_end_objective.R          | 2110 ++++-----
 tests/testthat/test_add_max_utility_objective.R            | 1334 ++---
 tests/testthat/test_add_min_largest_shortfall_objective.R  | 1360 ++---
 tests/testthat/test_add_min_set_objective.R                |  766 +--
 tests/testthat/test_add_min_shortfall_objective.R          | 1536 +++---
 tests/testthat/test_add_neighbor_constraints.R             |  685 +-
 tests/testthat/test_add_relative_targets.R                 |  516 +-
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 tests/testthat/test_all_binary.R                           |  222 
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 tests/testthat/test_assertions.R                           |  512 +-
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 tests/testthat/test_assertions_raster.R                    |  150 
 tests/testthat/test_assertions_sf.R                        |   24 
 tests/testthat/test_assertions_vector.R                    |   80 
 tests/testthat/test_binary_stack.R                         |   60 
 tests/testthat/test_boundary_matrix.R                      |  718 +--
 tests/testthat/test_branch_matrix.R                        |   80 
 tests/testthat/test_category_layer.R                       |   70 
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 tests/testthat/test_decisions.R                            |  542 +-
 tests/testthat/test_documentation.R                        |   14 
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 tests/testthat/test_eval_feature_representation_summary.R  | 1272 ++---
 tests/testthat/test_eval_ferrier_importance.R              |  696 +-
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 tests/testthat/test_eval_rare_richness_importance.R        |  788 +--
 tests/testthat/test_eval_replacement_importance.R          | 1350 ++---
 tests/testthat/test_eval_target_coverage_summary.R         |  666 +-
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 tests/testthat/test_feature_abundances.R                   |  668 +-
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 tests/testthat/test_marxan_boundary_data_to_matrix.R       |   96 
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 tests/testthat/test_marxan_problem.R                       |  870 +--
 tests/testthat/test_planning_unit_solution_status.R        |  820 +--
 tests/testthat/test_presolve_check.R                       |  642 +-
 tests/testthat/test_prioritizrdata.R                       |  138 
 tests/testthat/test_problem-deprecated.R                   | 1592 +++---
 tests/testthat/test_problem.R                              | 2724 ++++++-----
 tests/testthat/test_problem_negative.R                     | 2338 +++++-----
 tests/testthat/test_proximity_matrix.R                     |  748 +--
 tests/testthat/test_repr.R                                 |  184 
 tests/testthat/test_rescale_matrix.R                       |only
 tests/testthat/test_rij_matrix.R                           |  564 +-
 tests/testthat/test_run_calculations.R                     |   50 
 tests/testthat/test_simulate.R                             |  228 
 tests/testthat/test_solve.R                                | 1208 ++---
 tests/testthat/test_st_geometry_classes.R                  |   76 
 tests/testthat/test_write_problem.R                        |  172 
 tests/testthat/test_zones.R                                |  178 
 vignettes/calibrating_trade-offs_tutorial.Rmd              | 1423 +++---
 vignettes/connectivity_tutorial.Rmd                        | 1021 ++--
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 414 files changed, 88058 insertions(+), 87467 deletions(-)

More information about prioritizr at CRAN
Permanent link

Package pkgndep updated to version 1.99.2 with previous version 1.2.1 dated 2022-11-15

Title: Analyze Dependency Heaviness of R Packages
Description: A new metric named 'dependency heaviness' is proposed that measures the number of additional dependency packages that a parent package brings to its child package and are unique to the dependency packages imported by all other parents. The dependency heaviness analysis is visualized by a customized heatmap. The package is described in <doi:10.1093/bioinformatics/btac449>. We have also performed the dependency heaviness analysis on the CRAN/Bioconductor package ecosystem and the results are implemented as a web-based database which provides comprehensive tools for querying dependencies of individual R packages. The systematic analysis on the CRAN/Bioconductor ecosystem is described in <doi:10.1016/j.jss.2023.111610>. From 'pkgndep' version 2.0.0, the heaviness database includes snapshots of the CRAN/Bioconductor ecosystems for many old R versions.
Author: Zuguang Gu [aut, cre]
Maintainer: Zuguang Gu <z.gu@dkfz.de>

Diff between pkgndep versions 1.2.1 dated 2022-11-15 and 1.99.2 dated 2023-08-08

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 87 files changed, 2061 insertions(+), 837 deletions(-)

More information about pkgndep at CRAN
Permanent link

Package neojags updated to version 0.1.4 with previous version 0.1.3 dated 2023-07-05

Title: Neo-Normal Distributions Family for Markov Chain Monte Carlo (MCMC) Models in 'JAGS'
Description: A 'JAGS' extension module provides neo-normal distributions family including MSNBurr, MSNBurr-IIa, GMSNBurr, Lunetta Exponential Power, Fernandez-Steel Skew t, Fernandez-Steel Skew Normal, Fernandez-Osiewalski-Steel Skew Exponential Power, Jones Skew Exponential Power. References: Choir, A. S. (2020). "The New Neo-Normal Distributions and Their Properties".Unpublished Dissertation. Denwood, M.J. (2016) <doi:10.18637/jss.v071.i09>. Fernandez, C., Osiewalski, J., & Steel, M. F. (1995) <doi:10.1080/01621459.1995.10476637>. Fernandez, C., & Steel, M. F. (1998) <doi:10.1080/01621459.1998.10474117>. Iriawan, N. (2000). "Computationally Intensive Approaches to Inference in NeoNormal Linear Models".Unpublished Dissertation. Mineo, A., & Ruggieri, M. (2005) <doi:10.18637/jss.v012.i04>. Rigby, R. A., & Stasinopoulos, D. M. (2005) <doi:10.1111/j.1467-9876.2005.00510.x>. Lunetta, G. (1963). "Di una Generalizzazione dello Schema della Curva Normale". Ri [...truncated...]
Author: Achmad Syahrul Choir [aut, cre], Resi Ramadani [aut], Nur Iriawan [aut], S Sifa'ul Khusna Malikhatul Mutmainah [ctb], Matthew Denwood [cph], Martyn Plummer [cph]
Maintainer: Achmad Syahrul Choir <madsyair@stis.ac.id>

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Package minimaxApprox updated to version 0.1.0 with previous version 0.0.2 dated 2023-07-20

Title: Implementation of Remez Algorithm for Polynomial and Rational Function Approximation
Description: Implements the algorithm of Remez (1962) for polynomial minimax approximation and of Cody et al. (1968) <doi:10.1007/BF02162506> for rational minimax approximation.
Author: Avraham Adler [aut, cre, cph]
Maintainer: Avraham Adler <Avraham.Adler@gmail.com>

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Package LCMSQA updated to version 1.0.1 with previous version 1.0.0 dated 2023-03-16

Title: Liquid Chromatography/Mass Spectrometry (LC/MS) Quality Assessment
Description: The goal of 'LCMSQA' is to make it easy to check the quality of liquid chromatograph/mass spectrometry (LC/MS) experiments using a 'shiny' application. This package provides interactive data visualizations for quality control (QC) samples, including total ion current chromatogram (TIC), base peak chromatogram (BPC), mass spectrum, extracted ion chromatogram (XIC), and feature detection results from internal standards or known metabolites.
Author: Jaehyun Joo [aut, cre], Blanca Himes [aut]
Maintainer: Jaehyun Joo <jaehyunjoo@outlook.com>

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Package OlinkAnalyze updated to version 3.5.1 with previous version 3.4.1 dated 2023-05-08

Title: Facilitate Analysis of Proteomic Data from Olink
Description: A collection of functions to facilitate analysis of proteomic data from Olink, primarily NPX data that has been exported from Olink Software. The functions also work on QUANT data from Olink by log- transforming the QUANT data. The functions are focused on reading data, facilitating data wrangling and quality control analysis, performing statistical analysis and generating figures to visualize the results of the statistical analysis. The goal of this package is to help users extract biological insights from proteomic data run on the Olink platform.
Author: Kathleen Nevola [aut, cre] , Marianne Sandin [aut] , Jamey Guess [aut] , Simon Forsberg [aut] , Christoffer Cambronero [aut] , Pascal Pucholt [aut] , Boxi Zhang [aut] , Masoumeh Sheikhi [aut] , Klev Diamanti [aut] , Amrita Kar [aut] , Lei Conze [aut] [...truncated...]
Maintainer: Kathleen Nevola <biostattools@olink.com>

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Package MSinference updated to version 0.1.0 with previous version 0.0.9 dated 2023-01-23

Title: Multiscale Inference for Nonparametric Time Trend(s)
Description: Performs a multiscale analysis of a nonparametric regression or nonparametric regressions with time series errors. In case of one regression, with the help of this package it is possible to detect the regions where the trend function is increasing or decreasing. In case of multiple regressions, the test identifies regions where the trend functions are different from each other. See Khismatullina and Vogt (2020) <doi:10.1111/rssb.12347>, Khismatullina and Vogt (2022) <doi:10.48550/arXiv.2209.10841> and Khismatullina and Vogt (2023) <doi:10.1016/j.jeconom.2021.04.010> for more details on theory and applications.
Author: Marina Khismatullina [aut, cre], Michael Vogt [aut]
Maintainer: Marina Khismatullina <khismatullina@ese.eur.nl>

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Package RKorAPClient updated to version 0.7.7 with previous version 0.7.6 dated 2023-04-19

Title: 'KorAP' Web Service Client Package
Description: A client package that makes the 'KorAP' web service API accessible from R. The corpus analysis platform 'KorAP' has been developed as a scientific tool to make potentially large, stratified and multiply annotated corpora, such as the 'German Reference Corpus DeReKo' or the 'Corpus of the Contemporary Romanian Language CoRoLa', accessible for linguists to let them verify hypotheses and to find interesting patterns in real language use. The 'RKorAPClient' package provides access to 'KorAP' and the corpora behind it for user-created R code, as a programmatic alternative to the 'KorAP' web user-interface. You can learn more about 'KorAP' and use it directly on 'DeReKo' at <https://korap.ids-mannheim.de/>.
Author: Marc Kupietz [aut, cre], Nils Diewald [ctb], Leibniz Institute for the German Language [cph, fnd]
Maintainer: Marc Kupietz <kupietz@ids-mannheim.de>

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Package QTLRel updated to version 1.14 with previous version 1.12 dated 2022-11-04

Title: Tools for Mapping of Quantitative Traits of Genetically Related Individuals and Calculating Identity Coefficients from Pedigrees
Description: This software provides tools for quantitative trait mapping in populations such as advanced intercross lines where relatedness among individuals should not be ignored. It can estimate background genetic variance components, impute missing genotypes, simulate genotypes, perform a genome scan for putative quantitative trait loci (QTL), and plot mapping results. It also has functions to calculate identity coefficients from pedigrees, especially suitable for pedigrees that consist of a large number of generations, or estimate identity coefficients from genotypic data in certain circumstances.
Author: Riyan Cheng [aut, cre]
Maintainer: Riyan Cheng <riyancheng@hotmail.com>

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Package pagoda2 updated to version 1.0.11 with previous version 1.0.10 dated 2022-04-19

Title: Single Cell Analysis and Differential Expression
Description: Analyzing and interactively exploring large-scale single-cell RNA-seq datasets. 'pagoda2' primarily performs normalization and differential gene expression analysis, with an interactive application for exploring single-cell RNA-seq datasets. It performs basic tasks such as cell size normalization, gene variance normalization, and can be used to identify subpopulations and run differential expression within individual samples. 'pagoda2' was written to rapidly process modern large-scale scRNAseq datasets of approximately 1e6 cells. The companion web application allows users to explore which gene expression patterns form the different subpopulations within your data. The package also serves as the primary method for preprocessing data for conos, <https://github.com/kharchenkolab/conos>. This package interacts with data available through the 'p2data' package, which is available in a 'drat' repository. To access this data package, see the instructions at <https://github.com/kharche [...truncated...]
Author: Nikolas Barkas [aut], Viktor Petukhov [aut], Peter Kharchenko [aut], Simon Steiger [ctb], Rasmus Rydbirk [ctb], Evan Biederstedt [cre, aut]
Maintainer: Evan Biederstedt <evan.biederstedt@gmail.com>

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Package MendelianRandomization updated to version 0.9.0 with previous version 0.8.0 dated 2023-07-04

Title: Mendelian Randomization Package
Description: Encodes several methods for performing Mendelian randomization analyses with summarized data. Summarized data on genetic associations with the exposure and with the outcome can be obtained from large consortia. These data can be used for obtaining causal estimates using instrumental variable methods.
Author: Olena Yavorska <olena.yavorska@ludwig.ox.ac.uk> James Staley <james.staley@bristol.ac.uk>
Maintainer: Stephen Burgess <sb452@medschl.cam.ac.uk>

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Package cqcr (with last version 0.1.2) was removed from CRAN

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Package noctua updated to version 2.6.2 with previous version 2.6.1 dated 2022-12-20

Title: Connect to 'AWS Athena' using R 'AWS SDK' 'paws' ('DBI' Interface)
Description: Designed to be compatible with the 'R' package 'DBI' (Database Interface) when connecting to Amazon Web Service ('AWS') Athena <https://aws.amazon.com/athena/>. To do this the 'R' 'AWS' Software Development Kit ('SDK') 'paws' <https://github.com/paws-r/paws> is used as a driver.
Author: Dyfan Jones [aut, cre]
Maintainer: Dyfan Jones <dyfan.r.jones@gmail.com>

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Package hierarchicalDS (with last version 3.0) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2019-07-02 3.0
2014-11-26 2.9
2012-09-28 2.01
2012-07-12 1.0

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Package WordPools updated to version 1.2.0 with previous version 1.1-1 dated 2018-12-15

Title: Word Pools Used in Studies of Learning and Memory
Description: Collects several classical word pools used most often to provide lists of words in psychological studies of learning and memory. It provides a simple function, 'pickList' for selecting random samples of words within given ranges.
Author: Michael Friendly [aut, cre] , Matthew Dubins [ctb]
Maintainer: Michael Friendly <friendly@yorku.ca>

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Package SVDNF updated to version 0.1.8 with previous version 0.1.7 dated 2023-07-20

Title: Discrete Nonlinear Filtering for Stochastic Volatility Models
Description: Generates simulated paths from various financial stochastic volatility models with jumps and applies the discrete nonlinear filter (DNF) of Kitagawa (1987) <doi:10.1080/01621459.1987.10478534> to compute likelihood evaluations, filtering distribution estimates, and maximum likelihood parameter estimates. The algorithm is implemented following the work of Bégin and Boudreault (2021) <doi:10.1080/10618600.2020.1840995>.
Author: Louis Arsenault-Mahjoubi [aut, cre], Jean-Francois Begin [aut], Mathieu Boudreault [aut]
Maintainer: Louis Arsenault-Mahjoubi <larsenau@sfu.ca>

Diff between SVDNF versions 0.1.7 dated 2023-07-20 and 0.1.8 dated 2023-08-08

 DESCRIPTION  |    6 +++---
 MD5          |    4 ++--
 R/DNFOptim.R |   20 +++++++++++---------
 3 files changed, 16 insertions(+), 14 deletions(-)

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New package s3 with initial version 1.0.0
Package: s3
Title: Download Files from 'AWS S3'
Version: 1.0.0
Description: Download files hosted on 'AWS S3' (Amazon Web Services Simple Storage Service; <https://aws.amazon.com/s3/>) to a local directory based on their URI. Avoid downloading files that are already present locally. Allow for customization of where to store downloaded files.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: cli, prettyunits, fs, httr, glue, purrr (>= 0.3.4), dplyr, aws.signature, digest
Suggests: testthat, withr
URL: https://github.com/geomarker-io/s3
BugReports: https://github.com/geomarker-io/s3/issues
NeedsCompilation: no
Packaged: 2023-08-08 02:09:08 UTC; broeg1
Author: Cole Brokamp [aut, cre] , Erika Rasnick [aut]
Maintainer: Cole Brokamp <cole.brokamp@gmail.com>
Repository: CRAN
Date/Publication: 2023-08-08 16:20:02 UTC

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New package ranktreeEnsemble with initial version 0.21
Package: ranktreeEnsemble
Title: Ensemble Models of Rank-Based Trees with Extracted Decision Rules
Version: 0.21
Date: 2023-08-03
Maintainer: Min Lu <luminwin@gmail.com>
BugReports: https://github.com/TransBioInfoLab/ranktreeEnsemble/issues/
License: GPL (>= 2)
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 1.0.10),randomForestSRC,gbm,methods,data.tree
LinkingTo: Rcpp
Description: Fast computing an ensemble of rank-based trees via boosting or random forest on binary and multi-class problems. It converts continuous gene expression profiles into ranked gene pairs, for which the variable importance indices are computed and adopted for dimension reduction. Decision rules can be extracted from trees.
URL: https://github.com/TransBioInfoLab/ranktreeEnsemble/
LazyData: TRUE
NeedsCompilation: yes
Packaged: 2023-08-05 20:15:26 UTC; min
Repository: CRAN
Date/Publication: 2023-08-08 16:20:05 UTC
Author: Ruijie Yin [aut], Chen Ye [aut], Min Lu [aut, cre]

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New package latenetwork with initial version 1.0.1
Package: latenetwork
Title: Inference on LATEs under Network Interference of Unknown Form
Version: 1.0.1
Description: Estimating causal parameters in the presence of treatment spillover is of great interest in statistics. This package provides tools for instrumental variables estimation of average causal effects under network interference of unknown form. The target parameters are the local average direct effect, the local average indirect effect, the local average overall effect, and the local average spillover effect. The methods are developed by Hoshino and Yanagi (2023) <doi:10.48550/arXiv.2108.07455>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: igraph, methods, statip, stats
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://tkhdyanagi.github.io/latenetwork/
NeedsCompilation: no
Packaged: 2023-08-07 23:58:25 UTC; Takahide Yanagi
Author: Tadao Hoshino [aut, cph] , Takahide Yanagi [aut, cre, cph]
Maintainer: Takahide Yanagi <yanagi@econ.kyoto-u.ac.jp>
Repository: CRAN
Date/Publication: 2023-08-08 16:10:02 UTC

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Package genridge updated to version 0.7.0 with previous version 0.6.7 dated 2020-01-29

Title: Generalized Ridge Trace Plots for Ridge Regression
Description: The genridge package introduces generalizations of the standard univariate ridge trace plot used in ridge regression and related methods. These graphical methods show both bias (actually, shrinkage) and precision, by plotting the covariance ellipsoids of the estimated coefficients, rather than just the estimates themselves. 2D and 3D plotting methods are provided, both in the space of the predictor variables and in the transformed space of the PCA/SVD of the predictors.
Author: Michael Friendly [aut, cre]
Maintainer: Michael Friendly <friendly@yorku.ca>

Diff between genridge versions 0.6.7 dated 2020-01-29 and 0.7.0 dated 2023-08-08

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Package evolqg updated to version 0.3-3 with previous version 0.3-2 dated 2023-03-22

Title: Evolutionary Quantitative Genetics
Description: Provides functions for covariance matrix comparisons, estimation of repeatabilities in measurements and matrices, and general evolutionary quantitative genetics tools. Melo D, Garcia G, Hubbe A, Assis A P, Marroig G. (2016) <doi:10.12688/f1000research.7082.3>.
Author: Diogo Melo [aut, cre] , Ana Paula Assis [aut], Edgar Zanella [ctb], Fabio Andrade Machado [aut] , Guilherme Garcia [aut], Alex Hubbe [rev] , Gabriel Marroig [ths]
Maintainer: Diogo Melo <diogro@gmail.com>

Diff between evolqg versions 0.3-2 dated 2023-03-22 and 0.3-3 dated 2023-08-08

 DESCRIPTION          |   12 ++++++------
 MD5                  |    4 ++--
 R/MatrixStatistics.R |    6 ++++--
 3 files changed, 12 insertions(+), 10 deletions(-)

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New package CINNA with initial version 1.2.2
Package: CINNA
Title: Deciphering Central Informative Nodes in Network Analysis
Version: 1.2.2
Date: 2023-08-07
Description: Computing, comparing, and demonstrating top informative centrality measures within a network. "CINNA: an R/CRAN package to decipher Central Informative Nodes in Network Analysis" provides a comprehensive overview of the package functionality Ashtiani et al. (2018) <doi:10.1093/bioinformatics/bty819>.
License: GPL-3
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
Suggests: knitr, rmarkdown
Imports: igraph, network, sna, centiserve, FactoMineR, factoextra, GGally, pheatmap, corrplot, dendextend, viridis, ggplot2, Rtsne, plyr, circlize, intergraph, utils, stats
NeedsCompilation: no
Repository: CRAN
Packaged: 2023-08-08 09:06:13 UTC; minooashtiani
Author: Minoo Ashtiani [aut, cre], Mehdi Mirzaie [ctb], Mohieddin Jafari [ctb]
Maintainer: Minoo Ashtiani <ashtiani.minoo@gmail.com>
Date/Publication: 2023-08-08 16:40:02 UTC

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Package tempdisagg updated to version 1.1.1 with previous version 1.1 dated 2023-03-09

Title: Methods for Temporal Disaggregation and Interpolation of Time Series
Description: Temporal disaggregation methods are used to disaggregate and interpolate a low frequency time series to a higher frequency series, where either the sum, the mean, the first or the last value of the resulting high frequency series is consistent with the low frequency series. Temporal disaggregation can be performed with or without one or more high frequency indicator series. Contains the methods of Chow-Lin, Santos-Silva-Cardoso, Fernandez, Litterman, Denton and Denton-Cholette, summarized in Sax and Steiner (2013) <doi:10.32614/RJ-2013-028>. Supports most R time series classes.
Author: Christoph Sax [aut, cre] , Peter Steiner [aut], Tommaso Di Fonzo [ctb]
Maintainer: Christoph Sax <christoph.sax@gmail.com>

Diff between tempdisagg versions 1.1 dated 2023-03-09 and 1.1.1 dated 2023-08-08

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 MD5                          |   16 ++--
 NEWS.md                      |    7 ++
 build/partial.rdb            |binary
 build/vignette.rds           |binary
 inst/doc/hf-disagg.html      |  144 +++++++++++++++++++++----------------------
 inst/doc/intro.html          |  134 ++++++++++++++++++++--------------------
 tests/test-all.R             |    7 +-
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 9 files changed, 164 insertions(+), 155 deletions(-)

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New package SpatialRDD with initial version 0.1.0
Package: SpatialRDD
Title: Conduct Multiple Types of Geographic Regression Discontinuity Designs
Version: 0.1.0
Description: Spatial versions of Regression Discontinuity Designs (RDDs) are becoming increasingly popular as tools for causal inference. However, conducting state-of-the-art analyses often involves tedious and time-consuming steps. This package offers comprehensive functionalities for executing all required spatial and econometric tasks in a streamlined manner. Moreover, it equips researchers with tools for performing essential placebo and balancing checks comprehensively. The fact that researchers do not have to rely on 'APIs' of external 'GIS' software ensures replicability and raises the standard for spatial RDDs.
Depends: R (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: dplyr, sf, ggplot2, rdrobust, lmtest, sandwich, cowplot, magrittr, rlang, broom
Suggests: knitr, tmap, rmarkdown, testthat, utils, kableExtra, lfe, stargazer
VignetteBuilder: knitr
URL: https://axlehner.github.io/SpatialRDD/
BugReports: https://github.com/axlehner/SpatialRDD/issues
NeedsCompilation: no
Packaged: 2023-08-07 20:28:45 UTC; alexanderlehner
Author: Alexander Lehner [aut, cre]
Maintainer: Alexander Lehner <lehner@uchicago.edu>
Repository: CRAN
Date/Publication: 2023-08-08 15:30:05 UTC

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New package MortalityLaws with initial version 2.0.3
Package: MortalityLaws
Title: Parametric Mortality Models, Life Tables and HMD
Version: 2.0.3
Maintainer: Marius D. Pascariu <mpascariu@outlook.com>
Description: Fit the most popular human mortality 'laws', and construct full and abridge life tables given various input indices. A mortality law is a parametric function that describes the dying-out process of individuals in a population during a significant portion of their life spans. For a comprehensive review of the most important mortality laws see Tabeau (2001) <doi:10.1007/0-306-47562-6_1>. Practical functions for downloading data from various human mortality databases are provided as well.
License: MIT + file LICENSE
LazyData: TRUE
Depends: R (>= 3.0.0)
Imports: minpack.lm (>= 1.2), RCurl (>= 1.95), pbapply (>= 1.3-4), tidyr (>= 0.8.1), rvest (>= 1.0.3), httr (>= 1.4.5)
Suggests: testthat, knitr, rmarkdown
URL: https://github.com/mpascariu/MortalityLaws
BugReports: https://github.com/mpascariu/MortalityLaws/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2023-08-07 19:56:54 UTC; mpascariu
Author: Marius D. Pascariu [aut, cre, cph] , Vladimir Canudas-Romo [ctb]
Repository: CRAN
Date/Publication: 2023-08-08 15:20:06 UTC

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New package kosis with initial version 0.0.1
Package: kosis
Title: Korean Statistical Information Service (KOSIS)
Version: 0.0.1
Description: API wrapper to download statistical information from the Korean Statistical Information Service (KOSIS) <https://kosis.kr/openapi/index/index.jsp>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: data.table (>= 1.13.0), httr (>= 1.4.3), jsonlite (>= 1.7.2), tibble (>= 3.2.1)
NeedsCompilation: no
Packaged: 2023-08-08 00:08:02 UTC; seokhoonj
Author: Seokhoon Joo [aut, cre]
Maintainer: Seokhoon Joo <seokhoonj@gmail.com>
Repository: CRAN
Date/Publication: 2023-08-08 16:00:03 UTC

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Package fastLogisticRegressionWrap updated to version 1.2.0 with previous version 1.1 dated 2023-07-13

Title: Fast Logistic Regression Wrapper
Description: Provides very fast logistic regression with coefficient inferences plus other useful methods such as a forward stepwise model generator (see the benchmarks by visiting the github page at the URL below). The inputs are flexible enough to accomodate GPU computations. The coefficient estimation employs the fastLR() method in the 'RcppNumerical' package by Yixuan Qiu et al. This package allows their work to be more useful to a wider community that consumes inference.
Author: Adam Kapelner [aut, cre] , Beau Walker [rev, dtc] , Gabriel Mayer [fnd, dtc]
Maintainer: Adam Kapelner <kapelner@qc.cuny.edu>

Diff between fastLogisticRegressionWrap versions 1.1 dated 2023-07-13 and 1.2.0 dated 2023-08-08

 CHANGELOG                               |   11 ++
 DESCRIPTION                             |   14 +--
 MD5                                     |   21 ++---
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New package defm with initial version 0.1-0
Package: defm
Title: Estimation and Simulation of Multi-Binary Response Models
Version: 0.1-0
Description: Multi-binary response models are a class of models that allow for the estimation of multiple binary outcomes simultaneously. This package provides functions to estimate and simulate these models using the Discrete Exponential-Family Models [DEFM] framework. In it, we implement the models described in Vega Yon, Valente, and Pugh (2023) <doi:10.48550/arXiv.2211.00627>. DEFMs include Exponential-Family Random Graph Models [ERGMs], which characterize graphs using sufficient statistics, which is also the core of DEFMs. Using sufficient statistics, we can describe the data through meaningful motifs, for example, transitions between different states, joint distribution of the outcomes, etc.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp
Imports: Rcpp
Depends: R (>= 2.10), stats4
Suggests: texreg
NeedsCompilation: yes
Packaged: 2023-08-07 22:53:31 UTC; george
Author: George Vega Yon [aut, cre] , Department of Veterans Affairs - Rehabilitation, Research, and Development Service [fnd]
Maintainer: George Vega Yon <g.vegayon@gmail.com>
Repository: CRAN
Date/Publication: 2023-08-08 15:40:03 UTC

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New package suggests with initial version 0.1.0
Package: suggests
Title: Declare when Suggested Packages are Needed
Version: 0.1.0
Date: 2023-07-14
Description: By adding dependencies to the "Suggests" field of a package's DESCRIPTION file, and then declaring that they are needed within any dependent functionality, it is often possible to significantly reduce the number of "hard" dependencies required by a package. This package provides a minimal way to declare when a suggested package is needed.
License: MIT + file LICENSE
URL: https://github.com/owenjonesuob/suggests
BugReports: https://github.com/owenjonesuob/suggests/issues
Imports: utils
Suggests: covr, testthat (>= 3.0.0)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2023-08-07 17:07:51 UTC; Owen
Author: Owen Jones [aut, cre]
Maintainer: Owen Jones <owenjonesuob@gmail.com>
Repository: CRAN
Date/Publication: 2023-08-08 14:30:02 UTC

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Package scorecard updated to version 0.4.3 with previous version 0.4.2 dated 2023-04-23

Title: Credit Risk Scorecard
Description: The `scorecard` package makes the development of credit risk scorecard easier and efficient by providing functions for some common tasks, such as data partition, variable selection, woe binning, scorecard scaling, performance evaluation and report generation. These functions can also used in the development of machine learning models. The references including: 1. Refaat, M. (2011, ISBN: 9781447511199). Credit Risk Scorecard: Development and Implementation Using SAS. 2. Siddiqi, N. (2006, ISBN: 9780471754510). Credit risk scorecards. Developing and Implementing Intelligent Credit Scoring.
Author: Shichen Xie [aut, cre]
Maintainer: Shichen Xie <xie@shichen.name>

Diff between scorecard versions 0.4.2 dated 2023-04-23 and 0.4.3 dated 2023-08-08

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New package rolap with initial version 2.0.0
Package: rolap
Title: Obtaining Star Databases from Flat Tables
Version: 2.0.0
Description: Data in multidimensional systems is obtained from operational systems and is transformed to adapt it to the new structure. Frequently, the operations to be performed aim to transform a flat table into a ROLAP (Relational On-Line Analytical Processing) star database. The main objective of the package is to allow the definition of these transformations easily. The implementation of the multidimensional database obtained can be exported to work with multidimensional analysis tools on spreadsheets or relational databases.
License: MIT + file LICENSE
URL: https://josesamos.github.io/rolap/, https://github.com/josesamos/rolap
BugReports: https://github.com/josesamos/rolap/issues
Depends: R (>= 2.10)
Imports: dm, dplyr, purrr, rlang, snakecase, tibble, tidyr, tidyselect
Suggests: DBI, dbplyr, DiagrammeR, DiagrammeRsvg, knitr, pander, rmarkdown, RSQLite, stringr, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-GB
LazyData: true
NeedsCompilation: no
Packaged: 2023-08-07 17:46:14 UTC; joses
Author: Jose Samos [aut, cre, cph]
Maintainer: Jose Samos <jsamos@ugr.es>
Repository: CRAN
Date/Publication: 2023-08-08 14:40:06 UTC

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Package Rmpfr updated to version 0.9-3 with previous version 0.9-2 dated 2023-04-21

Title: R MPFR - Multiple Precision Floating-Point Reliable
Description: Arithmetic (via S4 classes and methods) for arbitrary precision floating point numbers, including transcendental ("special") functions. To this end, the package interfaces to the 'LGPL' licensed 'MPFR' (Multiple Precision Floating-Point Reliable) Library which itself is based on the 'GMP' (GNU Multiple Precision) Library.
Author: Martin Maechler [aut, cre] , Richard M. Heiberger [ctb] , *Bin, *Dec), John C. Nash [ctb] , origin of unirootR), Hans W. Borchers [ctb] ; origin of hjkMpfr)
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>

Diff between Rmpfr versions 0.9-2 dated 2023-04-21 and 0.9-3 dated 2023-08-08

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Package odr updated to version 1.4.4 with previous version 1.4.2 dated 2023-04-24

Title: Optimal Design and Statistical Power for Experimental Studies Investigating Main, Mediation, and Moderation Effects
Description: Calculate the optimal sample size allocation that produces the highest statistical power for experimental studies under a budget constraint, and perform power analyses with and without accommodating cost structures of sampling. The designs cover single-level and multilevel experiments detecting main, mediation, and moderation effects (and some combinations). The references for the proposed methods include: (1) Shen, Z., & Kelcey, B. (2020). Optimal sample allocation under unequal costs in cluster-randomized trials. Journal of Educational and Behavioral Statistics, 45(4): 446-474. <doi:10.3102/1076998620912418>. (2) Shen, Z., & Kelcey, B. (2022b). Optimal sample allocation for three-level multisite cluster-randomized trials. Journal of Research on Educational Effectiveness, 15 (1), 130-150. <doi:10.1080/19345747.2021.1953200>. (3) Shen, Z., & Kelcey, B. (2022a). Optimal sample allocation in multisite randomized trials. The Journal of Experimental Education. <d [...truncated...]
Author: Zuchao Shen [aut, cre] , Benjamin Kelcey [aut]
Maintainer: Zuchao Shen <zuchao.shen@gmail.com>

Diff between odr versions 1.4.2 dated 2023-04-24 and 1.4.4 dated 2023-08-08

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 20 files changed, 708 insertions(+), 932 deletions(-)

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New package npboottprm with initial version 0.1.0
Package: npboottprm
Title: Nonparametric Bootstrap Test with Pooled Resampling
Version: 0.1.0
Description: Addressing crucial research questions often necessitates a small sample size due to factors such as distinctive target populations, rarity of the event under study, time and cost constraints, ethical concerns, or group-level unit of analysis. Many readily available analytic methods, however, do not accommodate small sample sizes, and the choice of the best method can be unclear. The 'npboottprm' package enables the execution of nonparametric bootstrap tests with pooled resampling to help fill this gap. Grounded in the statistical methods for small sample size studies detailed in Dwivedi, Mallawaarachchi, and Alvarado (2017) <doi:10.1002/sim.7263>, the package facilitates a range of statistical tests, encompassing independent t-tests, paired t-tests, and one-way Analysis of Variance (ANOVA) F-tests. The nonparboot() function undertakes essential computations, yielding detailed outputs which include test statistics, effect sizes, confidence intervals, and bootstrap distributions. F [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/mightymetrika/npboottprm
BugReports: https://github.com/mightymetrika/npboottprm/issues
Suggests: testthat (>= 3.0.0)
Depends: R (>= 2.10)
LazyData: true
Imports: ggplot2, shiny, shinythemes
NeedsCompilation: no
Packaged: 2023-08-07 15:13:07 UTC; Administrator
Author: Mackson Ncube [aut, cre], mightymetrika, LLC [cph, fnd]
Maintainer: Mackson Ncube <macksonncube.stats@gmail.com>
Repository: CRAN
Date/Publication: 2023-08-08 14:10:02 UTC

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Permanent link

Package jsmodule updated to version 1.4.2 with previous version 1.4.1 dated 2023-04-14

Title: 'RStudio' Addins and 'Shiny' Modules for Medical Research
Description: 'RStudio' addins and 'Shiny' modules for descriptive statistics, regression and survival analysis.
Author: Jinseob Kim [aut, cre] , Zarathu [cph, fnd], Hyunki Lee [aut], Changwoo Lim [aut], Jinhwan Kim [aut]
Maintainer: Jinseob Kim <jinseob2kim@gmail.com>

Diff between jsmodule versions 1.4.1 dated 2023-04-14 and 1.4.2 dated 2023-08-08

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Package iGasso updated to version 1.6 with previous version 1.4 dated 2016-06-04

Title: Statistical Tests and Utilities for Genetic Association
Description: A collection of statistical tests for genetic association studies and summary data based Mendelian randomization.
Author: Dr. Kai Wang
Maintainer: Kai Wang <kai-wang@uiowa.edu>

Diff between iGasso versions 1.4 dated 2016-06-04 and 1.6 dated 2023-08-08

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Package IDEATools updated to version 3.5.0 with previous version 3.4.2 dated 2023-04-24

Title: Individual and Group Farm Sustainability Assessments using the IDEA4 Method
Description: Collection of tools to automate the processing of data collected though the IDEA4 method (see Zahm et al. (2018) <doi:10.1051/cagri/2019004> ). Starting from the original data collecting files this packages provides functions to compute IDEA indicators, draw modern and aesthetic plots, and produce a wide range of reporting materials.
Author: David Carayon [aut, cre, cph]
Maintainer: David Carayon <david.carayon@inrae.fr>

Diff between IDEATools versions 3.4.2 dated 2023-04-24 and 3.5.0 dated 2023-08-08

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New package bvpa with initial version 1.0.0
Package: bvpa
Title: Bivariate Pareto Distribution
Version: 1.0.0
Date: 2023-08-07
Maintainer: Biplab Paul <paul.biplab497@gmail.com>
Description: Implements the EM algorithm with one-step Gradient Descent method to estimate the parameters of the Block-Basu bivariate Pareto distribution with location and scale. We also found parametric bootstrap and asymptotic confidence intervals based on the observed Fisher information of scale and shape parameters, and exact confidence intervals for location parameters. Details are in Biplab Paul and Arabin Kumar Dey (2023) <doi:10.48550/arXiv.1608.02199> "An EM algorithm for absolutely continuous Marshall-Olkin bivariate Pareto distribution with location and scale"; E L Lehmann and George Casella (1998) <doi:10.1007/b98854> "Theory of Point Estimation"; Bradley Efron and R J Tibshirani (1994) <doi:10.1201/9780429246593> "An Introduction to the Bootstrap"; A P Dempster, N M Laird and D B Rubin (1977) <www.jstor.org/stable/2984875> "Maximum Likelihood from Incomplete Data via the EM Algorithm".
License: GPL (>= 2)
Imports: numDeriv, stats
Author: Biplab Paul [aut, cre], Arabin Kumar Dey [aut]
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2023-08-07 19:29:00 UTC; GOBINDO
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2023-08-08 14:50:02 UTC

More information about bvpa at CRAN
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New package atRisk with initial version 0.1.0
Package: atRisk
Title: At-Risk
Version: 0.1.0
Description: The at-Risk (aR) approach is based on a two-step parametric estimation procedure that allows to forecast the full conditional distribution of an economic variable at a given horizon, as a function of a set of factors. These density forecasts are then be used to produce coherent forecasts for any downside risk measure, e.g., value-at-risk, expected shortfall, downside entropy. Initially introduced by Adrian et al. (2019) <doi:10.1257/aer.20161923> to reveal the vulnerability of economic growth to financial conditions, the aR approach is currently extensively used by international financial institutions to provide Value-at-Risk (VaR) type forecasts for GDP growth (Growth-at-Risk) or inflation (Inflation-at-Risk). This package provides methods for estimating these models. Datasets for the US and the Eurozone are available to allow testing of the Adrian et al. (2019) model. This package constitutes a useful toolbox (data and functions) for private practitioners, scholars as well as p [...truncated...]
Depends: R (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: stats, quantreg, sn, dfoptim, ggplot2, ggridges
NeedsCompilation: no
Packaged: 2023-08-07 18:24:53 UTC; quentin.lajaunie_ver
Author: Quentin Lajaunie [aut, cre], Guillaume Flament [aut, ctb], Christophe Hurlin [aut], Souzan Kazemi [rev]
Maintainer: Quentin Lajaunie <quentin_lajaunie@hotmail.fr>
Repository: CRAN
Date/Publication: 2023-08-08 14:50:05 UTC

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New package poolABC with initial version 1.0.0
Package: poolABC
Title: Approximate Bayesian Computation with Pooled Sequencing Data
Version: 1.0.0
Description: Provides functions to simulate Pool-seq data under models of demographic formation and to import Pool-seq data from real populations. Implements two ABC algorithms for performing parameter estimation and model selection using Pool-seq data. Cross-validation can also be performed to assess the accuracy of ABC estimates and model choice. Carvalho et al., (2022) <doi:10.1111/1755-0998.13834>.
License: GPL (>= 3)
Encoding: UTF-8
Imports: doParallel, foreach, ggplot2, graphics, locfit, MetricsWeighted, nnet, poolHelper (>= 1.1.0), RColorBrewer, rlang, scrm, stats, utils
Depends: R (>= 2.10)
LazyData: true
URL: https://github.com/joao-mcarvalho/poolABC
BugReports: https://github.com/joao-mcarvalho/poolABC/issues
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2023-07-21 10:38:00 UTC; jcarvalho
Author: Joao Carvalho [aut, cre, cph] , Vitor Sousa [aut]
Maintainer: Joao Carvalho <jgcarvalho@fc.ul.pt>
Repository: CRAN
Date/Publication: 2023-08-08 14:00:02 UTC

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Package optic updated to version 1.0.1 with previous version 1.0.0 dated 2023-05-26

Title: Simulation Tool for Causal Inference Using Longitudinal Data
Description: Implements a simulation study to assess the strengths and weaknesses of causal inference methods for estimating policy effects using panel data. See Griffin et al. (2021) <doi:10.1007/s10742-022-00284-w> and Griffin et al. (2022) <doi:10.1186/s12874-021-01471-y> for a description of our methods.
Author: Beth Ann Griffin [aut, cph] , Pedro Nascimento de Lima [cre, aut] , Max Griswold [aut] , Adam Scherling [aut], Joseph Pane [aut], Geoffrey Grimm [aut]
Maintainer: Pedro Nascimento de Lima <plima@rand.org>

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Package naijR updated to version 0.6.0 with previous version 0.5.2 dated 2023-06-14

Title: Operations to Ease Data Analyses Specific to Nigeria
Description: A set of convenience functions as well as geographical/political data about Nigeria, aimed at simplifying work with data and information that are specific to the country.
Author: Victor Ordu [aut, cre]
Maintainer: Victor Ordu <victorordu@outlook.com>

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Package mixlm updated to version 1.3.0 with previous version 1.2.6 dated 2022-02-24

Title: Mixed Model ANOVA and Statistics for Education
Description: The main functions perform mixed models analysis by least squares or REML by adding the function r() to formulas of lm() and glm(). A collection of text-book statistics for higher education is also included, e.g. modifications of the functions lm(), glm() and associated summaries from the package 'stats'.
Author: Kristian Hovde Liland [aut, cre], Solve Saeboe¸ [ctb], R-Core [ctb]
Maintainer: Kristian Hovde Liland <kristian.liland@nmbu.no>

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Package MGMM updated to version 1.0.1 with previous version 1.0.0 dated 2021-12-21

Title: Missingness Aware Gaussian Mixture Models
Description: Parameter estimation and classification for Gaussian Mixture Models (GMMs) in the presence of missing data. This package complements existing implementations by allowing for both missing elements in the input vectors and full (as opposed to strictly diagonal) covariance matrices. Estimation is performed using an expectation conditional maximization algorithm that accounts for missingness of both the cluster assignments and the vector components. The output includes the marginal cluster membership probabilities; the mean and covariance of each cluster; the posterior probabilities of cluster membership; and a completed version of the input data, with missing values imputed to their posterior expectations. For additional details, please see McCaw ZR, Julienne H, Aschard H. "Fitting Gaussian mixture models on incomplete data." <doi:10.1186/s12859-022-04740-9>.
Author: Zachary McCaw [aut, cre]
Maintainer: Zachary McCaw <zmccaw@alumni.harvard.edu>

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Package EgoCor updated to version 1.1.0 with previous version 1.0.0 dated 2022-08-11

Title: Simple Presentation of Estimated Exponential Semi-Variograms
Description: User friendly interface based on the R package 'gstat' to fit exponential parametric models to empirical semi-variograms in order to model the spatial correlation structure of health data. Geo-located health outcomes of survey participants may be used to model spatial effects on health in an ego-centred approach. The package contains a range of functions to help explore the spatial structure of the data as well as visualize the fit of exponential models for various metaparameter combinations with respect to the number of lag intervals and maximal distance. Furthermore, the outcome of interest can be adjusted for covariates by fitting a linear regression in a preliminary step before the semi-variogram fitting process.
Author: Julia Dyck [aut, cre], Odile Sauzet [aut], Jan-Ole Koslik [aut]
Maintainer: Julia Dyck <j.dyck@uni-bielefeld.de>

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Package dtts updated to version 0.1.1 with previous version 0.1.0 dated 2022-03-09

Title: 'data.table' Time-Series
Description: High-frequency time-series support via 'nanotime' and 'data.table'.
Author: Dirk Eddelbuettel and Leonardo Silvestri
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package scan updated to version 0.60.0 with previous version 0.59.0 dated 2023-06-03

Title: Single-Case Data Analyses for Single and Multiple Baseline Designs
Description: A collection of procedures for analysing, visualising, and managing single-case data. These include piecewise linear regression models, multilevel models, overlap indices ('PND', 'PEM', 'PAND', 'PET', 'tau-u', 'baseline corrected tau', 'CDC'), and randomization tests. Data preparation functions support outlier detection, handling missing values, scaling, truncation, rank transformation, and smoothing. An export function helps to generate html and latex tables in a publication friendly style. More details can be found in the online book 'Analyzing single-case data with R and scan', Juergen Wilbert (2023) <https://jazznbass.github.io/scan-Book/>.
Author: Juergen Wilbert [cre, aut] , Timo Lueke [aut]
Maintainer: Juergen Wilbert <juergen.wilbert@uni-potsdam.de>

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Package rintcal updated to version 0.6.3 with previous version 0.6.2 dated 2023-07-16

Title: Radiocarbon Calibration Curves
Description: The IntCal20 radiocarbon calibration curves (Reimer et al. 2020 <doi:10.1017/RDC.2020.68>) are provided as a data package, together with previous IntCal curves (IntCal13, IntCal09, IntCal04, IntCal98) and postbomb curves. Also provided are functions to copy the curves into memory, to plot the curves and their underlying data, to calibrate radiocarbon dates and to transform between different radiocarbon 'domains'.
Author: Maarten Blaauw [aut, cre]
Maintainer: Maarten Blaauw <maarten.blaauw@qub.ac.uk>

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Package repeated updated to version 1.1.7 with previous version 1.1.6 dated 2022-10-27

Title: Non-Normal Repeated Measurements Models
Description: Various functions to fit models for non-normal repeated measurements, such as Binary Random Effects Models with Two Levels of Nesting, Bivariate Beta-binomial Regression Models, Marginal Bivariate Binomial Regression Models, Cormack capture-recapture models, Continuous-time Hidden Markov Chain Models, Discrete-time Hidden Markov Chain Models, Changepoint Location Models using a Continuous-time Two-state Hidden Markov Chain, generalized nonlinear autoregression models, multivariate Gaussian copula models, generalized non-linear mixed models with one random effect, generalized non-linear mixed models using h-likelihood for one random effect, Repeated Measurements Models for Counts with Frailty or Serial Dependence, Repeated Measurements Models for Continuous Variables with Frailty or Serial Dependence, Ordinal Random Effects Models with Dropouts, marginal homogeneity models for square contingency tables, correlated negative binomial models with Kalman update. References include Lindsey's [...truncated...]
Author: Bruce Swihart [cre, aut], Jim Lindsey [aut] , T.R. Ten Have [ctb, cph] .), Richard Cook [ctb, cph] , Iain MacDonald [ctb, cph] , Walter Zucchini [ctb, cph] , Burton Garbow [ctb, cph] , Euginia Zharichenko [ctb, cph]
Maintainer: Bruce Swihart <bruce.swihart@gmail.com>

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Package quickcode updated to version 0.2 with previous version 0.1 dated 2023-07-18

Title: A Compilation of Some Frequently Used R Functions
Description: The NOT functions and a simple compilation of various functions for easy usage. Shorthand code to save memory usage.
Author: Obinna Obianom [aut, cre]
Maintainer: Obinna Obianom <idonshayo@gmail.com>

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Package openalexR updated to version 1.2.0 with previous version 1.1.0 dated 2023-05-04

Title: Getting Bibliographic Records from 'OpenAlex' Database Using 'DSL' API
Description: A set of tools to extract bibliographic content from 'OpenAlex' database using API <https://docs.openalex.org>.
Author: Massimo Aria [aut, cre, cph] , Corrado Cuccurullo [ctb] , Trang Le [aut] , June Choe [ctb]
Maintainer: Massimo Aria <aria@unina.it>

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Package MBNMAdose updated to version 0.4.2 with previous version 0.4.1 dated 2022-02-24

Title: Dose-Response MBNMA Models
Description: Fits Bayesian dose-response model-based network meta-analysis (MBNMA) that incorporate multiple doses within an agent by modelling different dose-response functions, as described by Mawdsley et al. (2016) <doi:10.1002/psp4.12091>. By modelling dose-response relationships this can connect networks of evidence that might otherwise be disconnected, and can improve precision on treatment estimates. Several common dose-response functions are provided; others may be added by the user. Various characteristics and assumptions can be flexibly added to the models, such as shared class effects. The consistency of direct and indirect evidence in the network can be assessed using unrelated mean effects models and/or by node-splitting at the treatment level.
Author: Hugo Pedder [aut, cre] , Adil Karim [ctb]
Maintainer: Hugo Pedder <hugopedder@gmail.com>

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Package gpindex updated to version 0.5.0 with previous version 0.4.3 dated 2022-04-30

Title: Generalized Price and Quantity Indexes
Description: A small package for calculating lots of different price indexes, and by extension quantity indexes. Provides tools to build and work with any type of bilateral generalized-mean index (of which most price indexes are), along with a few important indexes that don't belong to the generalized-mean family (e.g., superlative quadratic-mean indexes, GEKS). Implements and extends many of the methods in Balk (2008, ISBN:978-1-107-40496-0), von der Lippe (2001, ISBN:3-8246-0638-0), and the CPI manual (2020, ISBN:978-1-51354-298-0) for bilateral price indexes.
Author: Steve Martin [aut, cre, cph]
Maintainer: Steve Martin <stevemartin041@gmail.com>

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Package geojson updated to version 0.3.5 with previous version 0.3.4 dated 2020-06-23

Title: Classes for 'GeoJSON'
Description: Classes for 'GeoJSON' to make working with 'GeoJSON' easier. Includes S3 classes for 'GeoJSON' classes with brief summary output, and a few methods such as extracting and adding bounding boxes, properties, and coordinate reference systems; working with newline delimited 'GeoJSON'; and serializing to/from 'Geobuf' binary 'GeoJSON' format.
Author: Scott Chamberlain [aut] , Jeroen Ooms [aut], Michael Sumner [cre]
Maintainer: Michael Sumner <mdsumner@gmail.com>

Diff between geojson versions 0.3.4 dated 2020-06-23 and 0.3.5 dated 2023-08-08

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Package DeclareDesign updated to version 1.0.4 with previous version 1.0.2 dated 2023-01-10

Title: Declare and Diagnose Research Designs
Description: Researchers can characterize and learn about the properties of research designs before implementation using `DeclareDesign`. Ex ante declaration and diagnosis of designs can help researchers clarify the strengths and limitations of their designs and to improve their properties, and can help readers evaluate a research strategy prior to implementation and without access to results. It can also make it easier for designs to be shared, replicated, and critiqued.
Author: Graeme Blair [aut, cre] , Jasper Cooper [aut] , Alexander Coppock [aut] , Macartan Humphreys [aut] , Neal Fultz [aut]
Maintainer: Graeme Blair <graeme.blair@gmail.com>

Diff between DeclareDesign versions 1.0.2 dated 2023-01-10 and 1.0.4 dated 2023-08-08

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Package airt updated to version 0.2.2 with previous version 0.2.1 dated 2021-12-17

Title: Evaluation of Algorithm Collections Using Item Response Theory
Description: An evaluation framework for algorithm portfolios using Item Response Theory (IRT). We use continuous and polytomous IRT models to evaluate algorithms and introduce algorithm characteristics such as stability, effectiveness and anomalousness (Kandanaarachchi, Smith-Miles 2020) <doi:10.13140/RG.2.2.11363.09760>.
Author: Sevvandi Kandanaarachchi [aut, cre]
Maintainer: Sevvandi Kandanaarachchi <sevvandik@gmail.com>

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Package siren updated to version 1.0.3 with previous version 1.0.1 dated 2022-03-09

Title: Hybrid FA-CFA for Controlling Acquiescence in Restricted Factorial Solutions
Description: Performs hybrid multi-stage factor analytic procedure for controlling acquiescence in restricted solutions (Ferrando & Lorenzo-Seva, 2000 <https://www.uv.es/revispsi/articulos3.00/ferran7.pdf>).
Author: David Navarro-Gonzalez [aut, cre], Pere J. Ferrando [aut], Fabia Morales-Vives [aut], Ana Hernandez-Dorado [aut]
Maintainer: David Navarro-Gonzalez <david.navarro@urv.cat>

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Package rCNV updated to version 1.2.0 with previous version 1.1.0 dated 2022-10-26

Title: Detect Copy Number Variants from SNPs Data
Description: Functions in this package will import filtered variant call format (VCF) files of SNPs data and generate data sets to detect copy number variants, visualize them and do downstream analyses with copy number variants(e.g. Environmental association analyses).
Author: Piyal Karunarathne [aut, cre] , Qiujie Zhou [aut] , Klaus Schliep [aut] , Pascal Milesi [aut]
Maintainer: Piyal Karunarathne <piyalkarumail@yahoo.com>

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Package eventTrack updated to version 1.0.3 with previous version 1.0.2 dated 2022-08-25

Title: Event Prediction for Time-to-Event Endpoints
Description: Implements the hybrid framework for event prediction described in Fang & Zheng (2011, <doi:10.1016/j.cct.2011.05.013>). To estimate the survival function the event prediction is based on, a piecewise exponential hazard function is fit to the time-to-event data to infer the potential change points. Prior to the last identified change point, the survival function is estimated using Kaplan-Meier, and the tail after the change point is fit using piecewise exponential.
Author: Kaspar Rufibach
Maintainer: Kaspar Rufibach <kaspar.rufibach@roche.com>

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 eventTrack-1.0.3/eventTrack/MD5                                                                                     |  122 
 eventTrack-1.0.3/eventTrack/NEWS                                                                                    |    8 
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 eventTrack-1.0.3/eventTrack/vignettes/biblio.bib                                                                    |    2 
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Package weibullness updated to version 1.23.8 with previous version 1.22.12 dated 2022-12-02

Title: Goodness-of-Fit Test for Weibull Distribution (Weibullness)
Description: Performs a goodness-of-fit test for Weibull distribution (weibullness test) and provides the parameter estimates of the two- and three-parameter Weibull distributions. Note that the threshold parameter is estimated based on the correlation from the Weibull plot. For more details, see <doi:10.23055/ijietap.2017.24.4.2848>, <doi:10.1155/2018/6056975>, and <doi:10.3390/math11143156>. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2022R1A2C1091319, RS-2023-00242528).
Author: Chanseok Park [aut, cre]
Maintainer: Chanseok Park <statpnu@gmail.com>

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Package packagefinder updated to version 0.3.5 with previous version 0.3.4 dated 2023-01-06

Title: Comfortable Search for R Packages on CRAN, Either Directly from the R Console or with an R Studio Add-in
Description: Search for R packages on CRAN directly from the R console, based on the packages' titles, short and long descriptions, or other fields. Combine multiple keywords with logical operators ('and', 'or'), view detailed information on any package and keep track of the latest package contributions to CRAN. If you don't want to search from the R console, use the comfortable R Studio add-in.
Author: Joachim Zuckarelli [aut, cre]
Maintainer: Joachim Zuckarelli <joachim@zuckarelli.de>

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Permanent link

Package openmeteo updated to version 0.2.1 with previous version 0.1.1 dated 2023-03-10

Title: Retrieve Weather Data from the Open-Meteo API
Description: A client for the Open-Meteo API that retrieves Open-Meteo weather data in a tidy format. No API key is required. The API specification is located at <https://open-meteo.com/en/docs>.
Author: Tom Pisel [aut, cre, cph]
Maintainer: Tom Pisel <mail@tompisel.com>

Diff between openmeteo versions 0.1.1 dated 2023-03-10 and 0.2.1 dated 2023-08-08

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Package matrixdist updated to version 1.1.9 with previous version 1.1.8 dated 2023-04-07

Title: Statistics for Matrix Distributions
Description: Tools for phase-type distributions including the following variants: continuous, discrete, multivariate, in-homogeneous, right-censored, and regression. Methods for functional evaluation, simulation and estimation using the expectation-maximization (EM) algorithm are provided for all models. The methods of this package are based on the following references. Asmussen, S., Nerman, O., & Olsson, M. (1996). Fitting phase-type distributions via the EM algorithm, Olsson, M. (1996). Estimation of phase-type distributions from censored data, Albrecher, H., & Bladt, M. (2019) <doi:10.1017/jpr.2019.60>, Albrecher, H., Bladt, M., & Yslas, J. (2022) <doi:10.1111/sjos.12505>, Albrecher, H., Bladt, M., Bladt, M., & Yslas, J. (2022) <doi:10.1016/j.insmatheco.2022.08.001>, Bladt, M., & Yslas, J. (2022) <doi:10.1080/03461238.2022.2097019>, Bladt, M. (2022) <doi:10.1017/asb.2021.40>, Bladt, M. (2023) <doi:10.1080/10920277.2023.2167833>, Albrecher, [...truncated...]
Author: Martin Bladt [aut, cre], Jorge Yslas [aut], Alaric Mueller [ctb]
Maintainer: Martin Bladt <martinbladt@gmail.com>

Diff between matrixdist versions 1.1.8 dated 2023-04-07 and 1.1.9 dated 2023-08-08

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Package matchingMarkets updated to version 1.0-4 with previous version 1.0-3 dated 2023-07-21

Title: Analysis of Stable Matchings
Description: Implements structural estimators to correct for the sample selection bias from observed outcomes in matching markets. This includes one-sided matching of agents into groups (Klein, 2015) <https://www.econ.cam.ac.uk/research-files/repec/cam/pdf/cwpe1521.pdf> as well as two-sided matching of students to schools (Aue et al., 2020) <https://ftp.zew.de/pub/zew-docs/dp/dp20032.pdf>. The package also contains algorithms to find stable matchings in the three most common matching problems: the stable roommates problem (Irving, 1985) <doi:10.1016/0196-6774(85)90033-1>, the college admissions problem (Gale and Shapley, 1962) <doi:10.2307/2312726>, and the house allocation problem (Shapley and Scarf, 1974) <doi:10.1016/0304-4068(74)90033-0>.
Author: Thilo Klein [aut, cre, cph], Robert Aue [ctb], Fahiem Bacchus [cph], Sven Giegerich [ctb], Matthias Hericks [ctb], Alexander Sauer [ctb], Niklas Sorensson [cph]
Maintainer: Thilo Klein <thilo@klein.uk>

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Package iRepro updated to version 1.2 with previous version 1.1 dated 2018-06-12

Title: Reproducibility for Interval-Censored Data
Description: Calculates intraclass correlation coefficient (ICC) for assessing reproducibility of interval-censored data with two repeated measurements (Kovacic and Varnai (2014) <doi:10.1097/EDE.0000000000000139>). ICC is estimated by maximum likelihood from model with one fixed and one random effect (both intercepts). Help in model checking (normality of subjects' means and residuals) is provided.
Author: Jelena Kovacic
Maintainer: Jelena Kovacic <jkovacic@imi.hr>

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Package ggblanket updated to version 4.0.0 with previous version 3.0.0 dated 2023-06-30

Title: Simplify 'ggplot2' Visualisation
Description: Simplify 'ggplot2' visualisation with 'ggblanket' wrapper functions.
Author: David Hodge [aut, cre, cph] , Nik Mitchell [ctb]
Maintainer: David Hodge <davidhodge931@gmail.com>

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Package ChineseNames updated to version 2023.8 with previous version 1.1.1 dated 2021-11-29

Title: Chinese Name Database 1930-2008
Description: A database of Chinese surnames and Chinese given names (1930-2008). This database contains nationwide frequency statistics of 1,806 Chinese surnames and 2,614 Chinese characters used in given names, covering about 1.2 billion Han Chinese population (96.8% of the Han Chinese household-registered population born from 1930 to 2008 and still alive in 2008). This package also contains a function for computing multiple features of Chinese surnames and Chinese given names for scientific research (e.g., name uniqueness, name gender, name valence, and name warmth/competence).
Author: Han-Wu-Shuang Bao [aut, cre]
Maintainer: Han-Wu-Shuang Bao <baohws@foxmail.com>

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Package BCClong updated to version 1.0.1 with previous version 1.0.0 dated 2023-01-13

Title: Bayesian Consensus Clustering for Multiple Longitudinal Features
Description: It is very common nowadays for a study to collect multiple features and appropriately integrating multiple longitudinal features simultaneously for defining individual clusters becomes increasingly crucial to understanding population heterogeneity and predicting future outcomes. 'BCClong' implements a Bayesian consensus clustering (BCC) model for multiple longitudinal features via a generalized linear mixed model. Compared to existing packages, several key features make the 'BCClong' package appealing: (a) it allows simultaneous clustering of mixed-type (e.g., continuous, discrete and categorical) longitudinal features, (b) it allows each longitudinal feature to be collected from different sources with measurements taken at distinct sets of time points (known as irregularly sampled longitudinal data), (c) it relaxes the assumption that all features have the same clustering structure by estimating the feature-specific (local) clusterings and consensus (global) clustering.
Author: Zhiwen Tan [aut, cre], Zihang Lu [ctb], Chang Shen [ctb]
Maintainer: Zhiwen Tan <21zt9@queensu.ca>

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Package BayesMultiMode updated to version 0.6.0 with previous version 0.5.1 dated 2023-04-06

Title: Bayesian Mode Inference
Description: A Bayesian approach for mode inference which works in two steps. First, a mixture distribution is fitted on the data using a sparse finite mixture (SFM) Markov chain Monte Carlo (MCMC) algorithm following Malsiner-Walli, Frühwirth-Schnatter and Grün (2016) <doi:10.1007/s11222-014-9500-2>). The number of mixture components does not have to be known; the size of the mixture is estimated endogenously through the SFM approach. Second, the modes of the estimated mixture at each MCMC draw are retrieved using algorithms specifically tailored for mode detection. These estimates are then used to construct posterior probabilities for the number of modes, their locations and uncertainties, providing a powerful tool for mode inference.
Author: Nalan Bastuerk [aut], Jamie Cross [aut], Peter de Knijff [aut], Lennart Hoogerheide [aut], Paul Labonne [aut, cre], Herman van Dijk [aut]
Maintainer: Paul Labonne <paul.labonne@bi.no>

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Package slendr updated to version 0.7.2 with previous version 0.7.1 dated 2023-07-14

Title: A Simulation Framework for Spatiotemporal Population Genetics
Description: A framework for simulating spatially explicit genomic data which leverages real cartographic information for programmatic and visual encoding of spatiotemporal population dynamics on real geographic landscapes. Population genetic models are then automatically executed by the 'SLiM' software by Haller et al. (2019) <doi:10.1093/molbev/msy228> behind the scenes, using a custom built-in simulation 'SLiM' script. Additionally, fully abstract spatial models not tied to a specific geographic location are supported, and users can also simulate data from standard, non-spatial, random-mating models. These can be simulated either with the 'SLiM' built-in back-end script, or using an efficient coalescent population genetics simulator 'msprime' by Baumdicker et al. (2022) <doi:10.1093/genetics/iyab229> with a custom-built 'Python' script bundled with the R package. Simulated genomic data is saved in a tree-sequence format and can be loaded, manipulated, and summarised using tree-sequen [...truncated...]
Author: Martin Petr [aut, cre]
Maintainer: Martin Petr <contact@bodkan.net>

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Package scrutiny updated to version 0.3.0 with previous version 0.2.4 dated 2023-01-20

Title: Error Detection in Science
Description: Test published summary statistics for consistency (Brown and Heathers, 2017, <doi:10.1177/1948550616673876>; Allard, 2018, <https://aurelienallard.netlify.app/post/anaytic-grimmer-possibility-standard-deviations/>; Heathers and Brown, 2019, <https://osf.io/5vb3u/>). The package also provides infrastructure for implementing new error detection techniques.
Author: Lukas Jung [aut, cre], Aurelien Allard [ctb]
Maintainer: Lukas Jung <jung-lukas@gmx.net>

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Package PsychWordVec updated to version 2023.8 with previous version 0.3.2 dated 2023-03-04

Title: Word Embedding Research Framework for Psychological Science
Description: An integrative toolbox of word embedding research that provides: (1) a collection of 'pre-trained' static word vectors in the '.RData' compressed format <https://psychbruce.github.io/WordVector_RData.pdf>; (2) a series of functions to process, analyze, and visualize word vectors; (3) a range of tests to examine conceptual associations, including the Word Embedding Association Test <doi:10.1126/science.aal4230> and the Relative Norm Distance <doi:10.1073/pnas.1720347115>, with permutation test of significance; (4) a set of training methods to locally train (static) word vectors from text corpora, including 'Word2Vec' <arXiv:1301.3781>, 'GloVe' <doi:10.3115/v1/D14-1162>, and 'FastText' <arXiv:1607.04606>; (5) a group of functions to download 'pre-trained' language models (e.g., 'GPT', 'BERT') and extract contextualized (dynamic) word vectors (based on the R package 'text').
Author: Han-Wu-Shuang Bao [aut, cre]
Maintainer: Han-Wu-Shuang Bao <baohws@foxmail.com>

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Package ProjectionBasedClustering updated to version 1.2.0 with previous version 1.1.8 dated 2022-05-26

Title: Projection Based Clustering
Description: A clustering approach applicable to every projection method is proposed here. The two-dimensional scatter plot of any projection method can construct a topographic map which displays unapparent data structures by using distance and density information of the data. The generalized U*-matrix renders this visualization in the form of a topographic map, which can be used to automatically define the clusters of high-dimensional data. The whole system is based on Thrun and Ultsch, "Using Projection based Clustering to Find Distance and Density based Clusters in High-Dimensional Data" <DOI:10.1007/s00357-020-09373-2>. Selecting the correct projection method will result in a visualization in which mountains surround each cluster. The number of clusters can be determined by counting valleys on the topographic map. Most projection methods are wrappers for already available methods in R. By contrast, the neighbor retrieval visualizer (NeRV) is based on C++ source code of the 'dredviz' softw [...truncated...]
Author: Michael Thrun [aut, cre, cph], Quirin Stier [ctb, rev] , Brinkmann Luca [ctb], Florian Lerch [aut], Felix Pape [aut], Tim Schreier [aut], Luis Winckelmann [aut], Kristian Nybo [cph], Jarkko Venna [cph], van der Maaten Laurens [cph]
Maintainer: Michael Thrun <m.thrun@gmx.net>

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Package PELVIS updated to version 2.0.4 with previous version 2.0.3 dated 2021-05-07

Title: Probabilistic Sex Estimate using Logistic Regression, Based on VISual Traits of the Human Os Coxae
Description: An R-Shiny application implementing a method of sexing the human os coxae based on logistic regressions and Bruzek's nonmetric traits <doi:10.1002/ajpa.23855>.
Author: Frederic Santos [aut, cre] , Élodie Bernardeau [ctb]
Maintainer: Frederic Santos <frederic.santos@u-bordeaux.fr>

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Package frailtyMMpen updated to version 1.2.1 with previous version 1.1.2 dated 2023-07-07

Title: Efficient Algorithm for High-Dimensional Frailty Model
Description: The penalized and non-penalized Minorize-Maximization (MM) method for frailty models to fit the clustered data, multi-event data and recurrent data. Least absolute shrinkage and selection operator (LASSO), minimax concave penalty (MCP) and smoothly clipped absolute deviation (SCAD) penalized functions are implemented. All the methods are computationally efficient. These general methods are proposed based on the following papers, Huang, Xu and Zhou (2022) <doi:10.3390/math10040538>, Huang, Xu and Zhou (2023) <doi:10.1177/09622802221133554>.
Author: Xifen Huang [aut], Yunpeng Zhou [aut, cre], Jinfeng Xu [ctb]
Maintainer: Yunpeng Zhou <u3514104@connect.hku.hk>

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Package AnthropMMD updated to version 4.0.2 with previous version 3.1.0 dated 2020-07-20

Title: An R Package for the Mean Measure of Divergence (MMD)
Description: Offers a graphical user interface for the calculation of the mean measure of divergence, with facilities for trait selection and graphical representations <doi:10.1002/ajpa.23336>.
Author: Frederic Santos [aut, cre]
Maintainer: Frederic Santos <frederic.santos@u-bordeaux.fr>

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Package scapGNN updated to version 0.1.4 with previous version 0.1.3 dated 2022-12-02

Title: Graph Neural Network-Based Framework for Single Cell Active Pathways and Gene Modules Analysis
Description: It is a single cell active pathway analysis tool based on the graph neural network (F. Scarselli (2009) <doi:10.1109/TNN.2008.2005605>; Thomas N. Kipf (2017) <arXiv:1609.02907v4>) to construct the gene-cell association network, infer pathway activity scores from different single cell modalities data, integrate multiple modality data on the same cells into one pathway activity score matrix, identify cell phenotype activated gene modules and parse association networks of gene modules under multiple cell phenotype. In addition, abundant visualization programs are provided to display the results.
Author: Xudong Han [aut, cre, cph], Xujiang Guo [fnd]
Maintainer: Xudong Han <hanxd1217@163.com>

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Package polyglotr updated to version 1.2.1 with previous version 1.2.0 dated 2023-07-17

Title: Translate Text
Description: The goal of the this package is to provide easy methods to translate pieces of text. Functions send requests to translation services online.
Author: Tomer Iwan [aut, cre, cph]
Maintainer: Tomer Iwan <t.iwan@vu.nl>

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Package NMA updated to version 1.3-1 with previous version 1.2-1 dated 2023-07-17

Title: Network Meta-Analysis Based on Multivariate Meta-Analysis Models
Description: Network meta-analysis tools based on contrast-based approach using the multivariate meta-analysis and meta-regression models (Noma et al. (2023) <Forthcoming>). Standard analysis tools for network meta-analysis and meta-regression (e.g., synthesis analysis, ranking analysis, and creating league table) are available by simple commands. For inconsistency analyses, the local and global inconsistency tests based on the Higgins' design-by-treatment interaction model can be applied. Also, the side-splitting and the Jackson's random inconsistency model are available. Standard graphical tools for network meta-analysis (e.g., network plot, ranked forest plot, and transitivity analysis) can also be utilized. For the synthesis analyses, the Noma-Hamura's improved REML (restricted maximum likelihood)-based methods (Noma et al. (2023) <doi:10.1002/jrsm.1652> <doi:10.1002/jrsm.1651>) are adopted as the default methods.
Author: Hisashi Noma [aut, cre] , Kazushi Maruo [aut], Shiro Tanaka [aut], Toshi A. Furukawa [aut]
Maintainer: Hisashi Noma <noma@ism.ac.jp>

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Package minSNPs updated to version 0.1.0 with previous version 0.0.4 dated 2023-04-19

Title: Resolution-Optimised SNPs Searcher
Description: This is a R implementation of "Minimum SNPs" software as described in "Price E.P., Inman-Bamber, J., Thiruvenkataswamy, V., Huygens, F and Giffard, P.M." (2007) <doi:10.1186/1471-2105-8-278> "Computer-aided identification of polymorphism sets diagnostic for groups of bacterial and viral genetic variants."
Author: Ludwig Kian Soon Hoon [aut, cre] , Peter Shaw [aut, ctb] , Phil Giffard [aut, ctb]
Maintainer: Ludwig Kian Soon Hoon <ldwgkshoon@gmail.com>

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Package meconetcomp updated to version 0.3.0 with previous version 0.2.0 dated 2022-10-05

Title: Compare Microbial Networks of 'trans_network' Class of 'microeco' Package
Description: Compare microbial co-occurrence networks created from 'trans_network' class of 'microeco' package <https://github.com/ChiLiubio/microeco>. This package is the extension of 'trans_network' class of 'microeco' package and especially useful when different networks are constructed and analyzed simultaneously.
Author: Chi Liu [aut, cre], Minjie Yao [ctb], Xiangzhen Li [ctb]
Maintainer: Chi Liu <liuchi0426@126.com>

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Package hhsmm updated to version 0.3.6 with previous version 0.3.5 dated 2023-03-06

Title: Hidden Hybrid Markov/Semi-Markov Model Fitting
Description: Develops algorithms for fitting, prediction, simulation and initialization of the hidden hybrid Markov/semi-Markov model, introduced by Guedon (2005) <doi:10.1016/j.csda.2004.05.033>, which also includes several tools for handling missing data, nonparametric mixture of B-splines emissions (Langrock et al., 2015 <doi:10.1111/biom.12282>), fitting regime switching regression (Kim et al., 2008 <doi:10.1016/j.jeconom.2007.10.002>) and auto-regressive hidden hybrid Markov/semi-Markov model, spline-based nonparametric estimation of additive state-switching models (Langrock et al., 2018 <doi:10.1111/stan.12133>) and many other useful tools (read for more description: Amini et al., 2022 <doi:10.1007/s00180-022-01248-x> and its arxiv version: <arXiv:2109.12489>).
Author: Morteza Amini [aut, cre, cph], Afarin Bayat [aut], Reza Salehian [aut]
Maintainer: Morteza Amini <morteza.amini@ut.ac.ir>

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Package FuzzyResampling updated to version 0.6.1 with previous version 0.6.0 dated 2022-12-15

Title: Resampling Methods for Triangular and Trapezoidal Fuzzy Numbers
Description: The classical (i.e. Efron's, see Efron and Tibshirani (1994, ISBN:978-0412042317) "An Introduction to the Bootstrap") bootstrap is widely used for both the real (i.e. "crisp") and fuzzy data. The main aim of the algorithms implemented in this package is to overcome a problem with repetition of a few distinct values and to create fuzzy numbers, which are "similar" (but not the same) to values from the initial sample. To do this, different characteristics of triangular/trapezoidal numbers are kept (like the value, the ambiguity, etc., see Grzegorzewski et al. <doi:10.2991/eusflat-19.2019.68>, Grzegorzewski et al. (2020) <doi:10.2991/ijcis.d.201012.003>, Grzegorzewski et al. (2020) <doi:10.34768/amcs-2020-0022>, Grzegorzewski and Romaniuk (2022) <doi:10.1007/978-3-030-95929-6_3>, Romaniuk and Hryniewicz (2019) <doi:10.1007/s00500-018-3251-5>). Some additional procedures related to these resampling methods are also provided, like calculation of the Bertoluz [...truncated...]
Author: Maciej Romaniuk [aut, cre], Przemyslaw Grzegorzewski [aut], Olgierd Hryniewicz [aut]
Maintainer: Maciej Romaniuk <mroman@ibspan.waw.pl>

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Package D3mirt updated to version 1.1.0 with previous version 1.0.5 dated 2023-07-20

Title: Descriptive 3D Multidimensional Item Response Theory Modeling
Description: For identifying, estimating, and plotting descriptive multidimensional item response theory models, restricted to 3D and dichotomous or polytomous data that fit the two-parameter logistic model or the graded response model. The method is foremost explorative and centered around the plot function that exposes item characteristics and constructs, represented by vector arrows, located in a three-dimensional interactive space. The results can be useful for item-level analysis as well as test development.
Author: Erik Forsberg [aut, cre, cph]
Maintainer: Erik Forsberg <forsbergpsychometrics@gmail.com>

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Package wdpar updated to version 1.3.5 with previous version 1.3.4 dated 2023-02-24

Title: Interface to the World Database on Protected Areas
Description: Fetch and clean data from the World Database on Protected Areas (WDPA) and the World Database on Other Effective Area-Based Conservation Measures (WDOECM). Data is obtained from Protected Planet <https://www.protectedplanet.net/en>. To augment data cleaning procedures, users can install the 'prepr' R package (available at <https://github.com/dickoa/prepr>). For more information on this package, see Hanson (2022) <doi:10.21105/joss.04594>.
Author: Jeffrey O Hanson [aut, cre]
Maintainer: Jeffrey O Hanson <jeffrey.hanson@uqconnect.edu.au>

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Package twdtw updated to version 1.0-1 with previous version 1.0-0 dated 2023-07-13

Title: Time-Weighted Dynamic Time Warping
Description: Implements Time-Weighted Dynamic Time Warping (TWDTW), a measure for quantifying time series similarity. The TWDTW algorithm, described in Maus et al. (2016) <doi:10.1109/JSTARS.2016.2517118> and Maus et al. (2019) <doi:10.18637/jss.v088.i05>, is applicable to multi-dimensional time series of various resolutions. It is particularly suitable for comparing time series with seasonality for environmental and ecological data analysis, covering domains such as remote sensing imagery, climate data, hydrology, and animal movement. The 'twdtw' package offers a user-friendly 'R' interface, efficient 'Fortran' routines for TWDTW calculations, flexible time weighting definitions, as well as utilities for time series preprocessing and visualization.
Author: Victor Maus [aut, cre]
Maintainer: Victor Maus <vwmaus1@gmail.com>

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Package sspse updated to version 1.1.0 with previous version 1.0.3 dated 2022-09-04

Title: Estimating Hidden Population Size using Respondent Driven Sampling Data
Description: Estimate the size of a networked population based on respondent-driven sampling data. The package is part of the "RDS Analyst" suite of packages for the analysis of respondent-driven sampling data. See Handcock, Gile and Mar (2014) <doi:10.1214/14-EJS923> and Handcock, Gile and Mar (2015) <doi:10.1111/biom.12255>.
Author: Mark S. Handcock [aut, cre, cph] , Krista J. Gile [aut, cph], Brian Kim [ctb], Katherine R. McLaughlin [ctb]
Maintainer: Mark S. Handcock <handcock@stat.ucla.edu>

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Package ShapeSelectForest updated to version 1.6 with previous version 1.5 dated 2022-08-15

Title: Shape Selection for Landsat Time Series of Forest Dynamics
Description: Landsat satellites collect important data about global forest conditions. Documentation about Landsat's role in forest disturbance estimation is available at the site <https://landsat.gsfc.nasa.gov/>. By constrained quadratic B-splines, this package delivers an optimal shape-restricted trajectory to a time series of Landsat imagery for the purpose of modeling annual forest disturbance dynamics to behave in an ecologically sensible manner assuming one of seven possible "shapes", namely, flat, decreasing, one-jump (decreasing, jump up, decreasing), inverted vee (increasing then decreasing), vee (decreasing then increasing), linear increasing, and double-jump (decreasing, jump up, decreasing, jump up, decreasing). The main routine selects the best shape according to the minimum Bayes information criterion (BIC) or the cone information criterion (CIC), which is defined as the log of the estimated predictive squared error. The package also provides parameters summarizing the temporal [...truncated...]
Author: Xiyue Liao [aut, cre] , Mary Meyer [aut], Elizabeth Freeman [aut], Gretchen Moisen [aut]
Maintainer: Xiyue Liao <xliao@sdsu.edu>

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Package readabs updated to version 0.4.14 with previous version 0.4.13 dated 2023-01-29

Title: Download and Tidy Time Series Data from the Australian Bureau of Statistics
Description: Downloads, imports, and tidies time series data from the Australian Bureau of Statistics <https://www.abs.gov.au/>.
Author: Matt Cowgill [aut, cre] , Zoe Meers [aut], Jaron Lee [aut], David Diviny [aut], Hugh Parsonage [ctb], Kinto Behr [ctb]
Maintainer: Matt Cowgill <mattcowgill@gmail.com>

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Package r5r updated to version 1.1.0 with previous version 1.0.1 dated 2023-03-06

Title: Rapid Realistic Routing with 'R5'
Description: Rapid realistic routing on multimodal transport networks (walk, bike, public transport and car) using 'R5', the Rapid Realistic Routing on Real-world and Reimagined networks engine <https://github.com/conveyal/r5>. The package allows users to generate detailed routing analysis or calculate travel time matrices using seamless parallel computing on top of the R5 Java machine. While R5 is developed by Conveyal, the package r5r is independently developed by a team at the Institute for Applied Economic Research (Ipea) with contributions from collaborators. Apart from the documentation in this package, users will find additional information on R5 documentation at <https://docs.conveyal.com/>. Although we try to keep new releases of r5r in synchrony with R5, the development of R5 follows Conveyal's independent update process. Hence, users should confirm the R5 version implied by the Conveyal user manual (see <https://docs.conveyal.com/changelog>) corresponds with the R5 ver [...truncated...]
Author: Marcus Saraiva [aut] , Rafael H. M. Pereira [aut, cre] , Daniel Herszenhut [aut] , Carlos Kaue Vieira Braga [aut] , Matthew Wigginton Conway [aut] , Ipea - Institute for Applied Economic Research [cph, fnd]
Maintainer: Rafael H. M. Pereira <rafa.pereira.br@gmail.com>

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Package QTLEMM updated to version 1.3.0 with previous version 1.2.0 dated 2023-06-05

Title: QTL Mapping and Hotspots Detection
Description: For QTL mapping, it consists of several functions to perform various tasks, including simulating or analyzing data, computing the significance thresholds and visualizing the QTL mapping results. The single-QTL or multiple-QTL method that allows a host of statistical models to be fitted and compared is applied to analyze the data for the estimation of QTL parameters. The models include the linear regression, permutation test, normal mixture model and truncated normal mixture model. The Gaussian stochastic process is implemented to compute the significance thresholds for QTL detection onto a genetic linkage map in the experimental populations. Two types of data, the complete genotyping or selective genotyping data, from various experimental populations, including backcross, F2, recombinant inbred (RI) populations, advanced intercrossed (AI) populations, are considered in the QTL mapping analysis. For QTL hotpot detection, the statistical methods can be developed based on either using the [...truncated...]
Author: Ping-Yuan Chung [cre], Chen-Hung Kao [aut], Y.-T. Guo [aut], H.-N. Ho [aut], H.-I. Lee [aut], P.-Y. Wu [aut], M.-H. Yang [aut], M.-H. Zeng [aut]
Maintainer: Ping-Yuan Chung <pychung@webmail.stat.sinica.edu.tw>

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Package oscar updated to version 1.1.7 with previous version 1.1.4 dated 2023-03-28

Title: Optimal Subset Cardinality Regression (OSCAR) Models Using the L0-Pseudonorm
Description: Optimal Subset Cardinality Regression (OSCAR) models offer regularized linear regression using the L0-pseudonorm, conventionally known as the number of non-zero coefficients. The package estimates an optimal subset of features using the L0-penalization via cross-validation, bootstrapping and visual diagnostics. Effective Fortran implementations are offered along the package for finding optima for the DC-decomposition, which is used for transforming the discrete L0-regularized optimization problem into a continuous non-convex optimization task. These optimization modules include DBDC ('Double Bundle method for nonsmooth DC optimization' as described in Joki et al. (2018) <doi:10.1137/16M1115733>) and LMBM ('Limited Memory Bundle Method for large-scale nonsmooth optimization' as in Haarala et al. (2004) <doi:10.1080/10556780410001689225>). The OSCAR models are comprehensively exemplified in Halkola et al. (2023) <doi:10.1371/journal.pcbi.1010333>). Multiple regression m [...truncated...]
Author: Teemu Daniel Laajala [aut, cre] , Kaisa Joki [aut], Anni Halkola [aut]
Maintainer: Teemu Daniel Laajala <teelaa@utu.fi>

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Package cities updated to version 0.1.3 with previous version 0.1.2 dated 2023-05-23

Title: Clinical Trials with Intercurrent Events Simulator
Description: Simulates clinical trials and summarizes causal effects and treatment policy estimands in the presence of intercurrent events in a transparent and intuitive manner.
Author: Ahmad Hakeem Abdul Wahab [aut, cre] , Yongming Qu [aut], Hege Michiels [aut], Junxiang Luo [aut], Run Zhuang [aut], Dominique McDaniel [aut], Dong Xi [aut], Elena Polverejan [aut], Steven Gilbert [aut], Stephen Ruberg [aut], Arman Sabbagh [aut]
Maintainer: Ahmad Hakeem Abdul Wahab <hakeemwahab00@gmail.com>

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Package AHPtools updated to version 0.2.0 with previous version 0.1.0 dated 2023-04-17

Title: Consistency in the Analytic Hierarchy Process
Description: A Swiss Army knife of utility functions for AHP users which will help you assess the consistency of a PCM as well as improve the consistency ratio, compute the sensitivity of a PCM, create a logical, not a random PCM, from the preferences you provide for the alternatives, and a function that helps evaluate the actual consistency of a PCM based on objective, fair bench marking. The toolkit additionally allows a user to specify only the upper triangular comparison ratios of the PCM and performs its assigned task.
Author: Amarnath Bose [aut, cre]
Maintainer: Amarnath Bose <amarnath.bose@gmail.com>

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