Thu, 07 Sep 2023

Package washi updated to version 0.2.0 with previous version 0.1.0 dated 2023-05-19

Title: Washington Soil Health Initiative Branding
Description: Create plots and tables in a consistent style with WaSHI (Washington Soil Health Initiative) branding. Use 'washi' to easily style your 'ggplot2' plots and 'flextable' tables.
Author: Jadey Ryan [aut, cre], Molly Mcilquham [aut], Dani Gelardi [aut], Washington State Department of Agriculture [cph, fnd]
Maintainer: Jadey Ryan <jryan@agr.wa.gov>

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Package sasLM updated to version 0.9.12 with previous version 0.9.11 dated 2023-08-09

Title: 'SAS' Linear Model
Description: This is a core implementation of 'SAS' procedures for linear models - GLM, REG, ANOVA, TTEST, FREQ, and UNIVARIATE. Some R packages provide type II and type III SS. However, the results of nested and complex designs are often different from those of 'SAS.' Different results does not necessarily mean incorrectness. However, many wants the same results to SAS. This package aims to achieve that. Reference: Littell RC, Stroup WW, Freund RJ (2002, ISBN:0-471-22174-0).
Author: Kyun-Seop Bae [aut]
Maintainer: Kyun-Seop Bae <k@acr.kr>

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Package DIRECT updated to version 1.1.0 with previous version 1.0.1 dated 2016-04-01

Title: Bayesian Clustering of Multivariate Data Under the Dirichlet-Process Prior
Description: A Bayesian clustering method for replicated time series or replicated measurements from multiple experimental conditions, e.g., time-course gene expression data. It estimates the number of clusters directly from the data using a Dirichlet-process prior. See Fu, A. Q., Russell, S., Bray, S. and Tavare, S. (2013) Bayesian clustering of replicated time-course gene expression data with weak signals. The Annals of Applied Statistics. 7(3) 1334-1361. <doi:10.1214/13-AOAS650>.
Author: Audrey Qiuyan Fu, Steven Russell, Sarah J. Bray and Simon Tavare
Maintainer: Audrey Q. Fu <audreyqyfu@gmail.com>

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Package shinySbm updated to version 0.1.5 with previous version 0.1.4 dated 2023-09-07

Title: 'shiny' Application to Use the Stochastic Block Model
Description: A 'shiny' interface for a simpler use of the 'sbm' R package. It also contains useful functions to easily explore the 'sbm' package results. With this package you should be able to use the stochastic block model without any knowledge in R, get automatic reports and nice visuals, as well as learning the basic functions of 'sbm'.
Author: Theodore Vanrenterghem [cre, aut], Julie Aubert [aut] , Saint-Clair Chabert-Liddell [aut] , grossBM team [ctb], Golem User [cph]
Maintainer: Theodore Vanrenterghem <shiny.sbm.dev@gmail.com>

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Package NMdata updated to version 0.1.1 with previous version 0.1.0 dated 2023-07-07

Title: Preparation, Checking and Post-Processing Data for PK/PD Modeling
Description: Efficient tools for preparation, checking and post-processing of data in PK/PD (pharmacokinetics/pharmacodynamics) modeling, with focus on use of Nonmem. Attention is paid to ensure consistency, traceability, and Nonmem compatibility of Data. Rigorously checks final Nonmem datasets. Implemented in 'data.table', but easily integrated with 'base' and 'tidyverse'.
Author: Philip Delff [aut, cre]
Maintainer: Philip Delff <philip@delff.dk>

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Package gdi updated to version 1.5.4 with previous version 1.4.1 dated 2023-08-07

Title: Volumetric Analysis using Graphic Double Integration
Description: Tools implementing an automated version of the graphic double integration technique (GDI) for volume implementation, and some other related utilities for paleontological image-analysis. GDI was first employed by Jerison (1973) <ISBN:9780323141086> and Hurlburt (1999) <doi:10.1080/02724634.1999.10011145> and is primarily used for volume or mass estimation of (extinct) animals. The package 'gdi' aims to make this technique as convenient and versatile as possible. The core functions of 'gdi' provide utilities for automatically measuring diameters from digital silhouettes provided as image files and calculating volume via graphic double integration with simple elliptical, superelliptical (following Motani 2001 <doi:10.1666/0094-8373(2001)027%3C0735:EBMFST%3E2.0.CO;2>) or complex cross-sectional models. Additionally, the package provides functions for estimating the center of mass position (COM), the moment of inertia (I) for 3D shapes and the second moment of area (Ix) of [...truncated...]
Author: Darius Nau [aut, cre]
Maintainer: Darius Nau <dariusnau@gmx.at>

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Package disaggregation updated to version 0.2.1 with previous version 0.2.0 dated 2023-04-28

Title: Disaggregation Modelling
Description: Fits disaggregation regression models using 'TMB' ('Template Model Builder'). When the response data are aggregated to polygon level but the predictor variables are at a higher resolution, these models can be useful. Regression models with spatial random fields. The package is described in detail in Nandi et al. (2023) <doi:10.18637/jss.v106.i11>.
Author: Anita Nandi [aut] , Tim Lucas [aut, cre] , Rohan Arambepola [aut], Andre Python [aut]
Maintainer: Tim Lucas <timcdlucas@gmail.com>

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Package spatsoc updated to version 0.2.2 with previous version 0.1.16 dated 2021-02-24

Title: Group Animal Relocation Data by Spatial and Temporal Relationship
Description: Detects spatial and temporal groups in GPS relocations (Robitaille et al. (2019) <doi:10.1111/2041-210X.13215>). It can be used to convert GPS relocations to gambit-of-the-group format to build proximity-based social networks In addition, the randomizations function provides data-stream randomization methods suitable for GPS data.
Author: Alec L. Robitaille [aut, cre] , Quinn Webber [aut] , Eric Vander Wal [aut]
Maintainer: Alec L. Robitaille <robit.alec@gmail.com>

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Package flextable updated to version 0.9.3 with previous version 0.9.2 dated 2023-06-18

Title: Functions for Tabular Reporting
Description: Use a grammar for creating and customizing pretty tables. The following formats are supported: 'HTML', 'PDF', 'RTF', 'Microsoft Word', 'Microsoft PowerPoint' and R 'Grid Graphics'. 'R Markdown', 'Quarto' and the package 'officer' can be used to produce the result files. The syntax is the same for the user regardless of the type of output to be produced. A set of functions allows the creation, definition of cell arrangement, addition of headers or footers, formatting and definition of cell content with text and or images. The package also offers a set of high-level functions that allow tabular reporting of statistical models and the creation of complex cross tabulations.
Author: David Gohel [aut, cre], ArData [cph], Clementine Jager [ctb], Panagiotis Skintzos [aut], Quentin Fazilleau [ctb], Maxim Nazarov [ctb] , Titouan Robert [ctb], Michael Barrowman [ctb] , Atsushi Yasumoto [ctb] , Paul Julian [ctb] , Sean Browning [ctb] , [...truncated...]
Maintainer: David Gohel <david.gohel@ardata.fr>

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New package maldipickr with initial version 1.1.1
Package: maldipickr
Title: Dereplicate and Cherry-Pick Mass Spectrometry Spectra
Version: 1.1.1
Description: Convenient wrapper functions for the analysis of matrix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF) spectra data in order to select only representative spectra (also called cherry-pick). The package covers the preprocessing and dereplication steps (based on Strejcek, Smrhova, Junkova and Uhlik (2018) <doi:10.3389/fmicb.2018.01294>) needed to cluster MALDI-TOF spectra before the final cherry-picking step. It enables the easy exclusion of spectra and/or clusters to accommodate complex cherry-picking strategies. Alternatively, cherry-picking using taxonomic identification MALDI-TOF data is made easy with functions to import inconsistently formatted reports.
License: GPL (>= 3)
URL: https://github.com/ClavelLab/maldipickr
BugReports: https://github.com/ClavelLab/maldipickr/issues
Imports: dplyr, magrittr, MALDIquant, readBrukerFlexData, rlang, stats, tibble, tidyr, tidyselect, tools, utils
Suggests: knitr, rmarkdown, spelling, testthat
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2023-09-07 08:57:07 UTC; rstudio
Author: Charlie Pauvert [aut, cre, cph] , David Wylensek [ctb] , Selina Nuechtern [ctb], Thomas Clavel [ctb, fnd, cph]
Maintainer: Charlie Pauvert <cpauvert@ukaachen.de>
Repository: CRAN
Date/Publication: 2023-09-07 18:10:02 UTC

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Package Directional updated to version 6.2 with previous version 6.1 dated 2023-07-17

Title: A Collection of Functions for Directional Data Analysis
Description: A collection of functions for directional data (including massive data, with millions of observations) analysis. Hypothesis testing, discriminant and regression analysis, MLE of distributions and more are included. The standard textbook for such data is the "Directional Statistics" by Mardia, K. V. and Jupp, P. E. (2000). Other references include a) Phillip J. Paine, Simon P. Preston Michail Tsagris and Andrew T. A. Wood (2018). An elliptically symmetric angular Gaussian distribution. Statistics and Computing 28(3): 689-697. <doi:10.1007/s11222-017-9756-4>. b) Tsagris M. and Alenazi A. (2019). Comparison of discriminant analysis methods on the sphere. Communications in Statistics: Case Studies, Data Analysis and Applications 5(4):467--491. <doi:10.1080/23737484.2019.1684854>. c) P. J. Paine, S. P. Preston, M. Tsagris and Andrew T. A. Wood (2020). Spherical regression models with general covariates and anisotropic errors. Statistics and Computing 30(1): 153--165. <doi:10. [...truncated...]
Author: Michail Tsagris, Giorgos Athineou, Christos Adam, Anamul Sajib, Eli Amson, Micah J. Waldstein
Maintainer: Michail Tsagris <mtsagris@uoc.gr>

Diff between Directional versions 6.1 dated 2023-07-17 and 6.2 dated 2023-09-07

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New package aphylo with initial version 0.3-3
Package: aphylo
Title: Statistical Inference and Prediction of Annotations in Phylogenetic Trees
Version: 0.3-3
Description: Implements a parsimonious evolutionary model to analyze and predict gene-functional annotations in phylogenetic trees as described in Vega Yon et al. (2021) <doi:10.1371/journal.pcbi.1007948>. Focusing on computational efficiency, 'aphylo' makes it possible to estimate pooled phylogenetic models, including thousands (hundreds) of annotations (trees) in the same run. The package also provides the tools for visualization of annotated phylogenies, calculation of posterior probabilities (prediction) and goodness-of-fit assessment featured in Vega Yon et al. (2021).
Depends: R (>= 3.5.0), ape (>= 5.0)
LazyData: true
Imports: Rcpp (>= 0.12.1), Matrix, methods, coda, fmcmc, utils, MASS, xml2
Suggests: covr, knitr, tinytest, AUC, rmarkdown,
VignetteBuilder: knitr
LinkingTo: Rcpp
Encoding: UTF-8
URL: https://github.com/USCbiostats/aphylo
BugReports: https://github.com/USCbiostats/aphylo/issues
Classification/MSC: 90C35, 90B18, 91D30
License: MIT + file LICENSE
NeedsCompilation: yes
Packaged: 2023-09-07 16:26:53 UTC; george
Author: George Vega Yon [aut, cre] , National Cancer Institute [fnd] , USC Biostatistics [cph]
Maintainer: George Vega Yon <g.vegayon@gmail.com>
Repository: CRAN
Date/Publication: 2023-09-07 18:40:02 UTC

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Package treespace updated to version 1.1.4.3 with previous version 1.1.4.2 dated 2023-04-06

Title: Statistical Exploration of Landscapes of Phylogenetic Trees
Description: Tools for the exploration of distributions of phylogenetic trees. This package includes a 'shiny' interface which can be started from R using treespaceServer(). For further details see Jombart et al. (2017) <DOI:10.1111/1755-0998.12676>.
Author: Thibaut Jombart [aut] , Michelle Kendall [aut, cre] , Jacob Almagro-Garcia [aut] , Caroline Colijn [aut]
Maintainer: Michelle Kendall <michelle.kendall@warwick.ac.uk>

Diff between treespace versions 1.1.4.2 dated 2023-04-06 and 1.1.4.3 dated 2023-09-07

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Package stRoke updated to version 23.9.1 with previous version 23.6.3 dated 2023-07-03

Title: Clinical Stroke Research
Description: This is an R-toolbox of custom functions for convenient data management and analysis in clinical health research and teaching. The package is mainly collected for personal use, but any use beyond that is encouraged. This package has migrated functions from 'agdamsbo/daDoctoR', and new functions has been added. Version follows months and year. See NEWS/Changelog for release notes. This package includes sampled data from the TALOS trial (Kraglund et al (2018) <doi:10.1161/STROKEAHA.117.020067>). The win_prob() function is based on work by Zou et al (2022) <doi:10.1161/STROKEAHA.121.037744>. The age_calc() function is based on work by Becker (2020) <doi:10.18637/jss.v093.i02>.
Author: Andreas Gammelgaard Damsbo [aut, cre]
Maintainer: Andreas Gammelgaard Damsbo <agdamsbo@clin.au.dk>

Diff between stRoke versions 23.6.3 dated 2023-07-03 and 23.9.1 dated 2023-09-07

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Package RegCombin updated to version 0.3.1 with previous version 0.2.1 dated 2023-03-01

Title: Partially Linear Regression under Data Combination
Description: We implement linear regression when the outcome of interest and some of the covariates are observed in two different datasets that cannot be linked, based on D'Haultfoeuille, Gaillac, Maurel (2022) <doi:10.3386/w29953>. The package allows for common regressors observed in both datasets, and for various shape constraints on the effect of covariates on the outcome of interest. It also provides the tools to perform a test of point identification. See the associated vignette <https://github.com/cgaillac/RegCombin/blob/master/RegCombin_vignette.pdf> for theory and code examples.
Author: Xavier D'Haultfoeuille [aut], Christophe Gaillac [aut, cre], Arnaud Maurel [aut]
Maintainer: Christophe Gaillac <christophe.gaillac@economics.ox.ac.uk>

Diff between RegCombin versions 0.2.1 dated 2023-03-01 and 0.3.1 dated 2023-09-07

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Package qspray updated to version 2.1.1 with previous version 2.1.0 dated 2023-08-07

Title: Multivariate Polynomials with Rational Coefficients
Description: Symbolic calculation and evaluation of multivariate polynomials with rational coefficients. This package is strongly inspired by the 'spray' package. It also provides a function to compute Gröbner bases (reference <doi:10.1007/978-3-319-16721-3>).
Author: Stephane Laurent [aut, cre], Robin Hankin [ctb, cph]
Maintainer: Stephane Laurent <laurent_step@outlook.fr>

Diff between qspray versions 2.1.0 dated 2023-08-07 and 2.1.1 dated 2023-09-07

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Package emplik updated to version 1.3-1 with previous version 1.3 dated 2023-04-03

Title: Empirical Likelihood Ratio for Censored/Truncated Data
Description: Empirical likelihood ratio tests for means/quantiles/hazards from possibly censored and/or truncated data. Now does regression too. This version contains some C code.
Author: Mai Zhou. . Yifan Yang for some C code.)
Maintainer: Mai Zhou <maizhou@gmail.com>

Diff between emplik versions 1.3 dated 2023-04-03 and 1.3-1 dated 2023-09-07

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Package sisireg updated to version 1.1.0 with previous version 1.0.0 dated 2022-01-04

Title: Sign-Simplicity-Regression-Solver
Description: Implementation of the SSR-Algorithm. The Sign-Simplicity-Regression model is a nonparametric statistical model which is based on residual signs and simplicity assumptions on the regression function. Goal is to calculate the most parsimonious regression function satisfying the statistical adequacy requirements. Theory and functions are specified in Metzner (2020, ISBN: 979-8-68239-420-3, "Trendbasierte Prognostik") and Metzner (2021, ISBN: 979-8-59347-027-0, "Adäquates Maschinelles Lernen").
Author: Lars Metzner [aut, cre]
Maintainer: Lars Metzner <lars.metzner@ppi.de>

Diff between sisireg versions 1.0.0 dated 2022-01-04 and 1.1.0 dated 2023-09-07

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Package RobustCalibration updated to version 0.5.4 with previous version 0.5.3 dated 2022-09-18

Title: Robust Calibration of Imperfect Mathematical Models
Description: Implements full Bayesian analysis for calibrating mathematical models with new methodology for modeling the discrepancy function. It allows for emulation, calibration and prediction using complex mathematical model outputs and experimental data. See the reference: Mengyang Gu and Long Wang (2018) <arXiv:1707.08215>, Mengyang Gu, Fangzheng Xie and Long Wang (2021) <arXiv:1807.03829>, Mengyang Gu, Kyle Anderson and Erika McPhillips (2021) <arXiv:1810.11664>.
Author: Mengyang Gu [aut, cre]
Maintainer: Mengyang Gu <mengyang@pstat.ucsb.edu>

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New package neuralGAM with initial version 1.0.0
Package: neuralGAM
Title: Interpretable Neural Network Based on Generalized Additive Models
Version: 1.0.0
Maintainer: Ines Ortega-Fernandez <iortega@gradiant.org>
Description: Neural network framework based on Generalized Additive Models from Hastie & Tibshirani (1990, ISBN:9780412343902), which trains a different neural network to estimate the contribution of each feature to the response variable. The networks are trained independently leveraging the local scoring and backfitting algorithms to ensure that the Generalized Additive Model converges and it is additive. The resultant Neural Network is a highly accurate and interpretable deep learning model, which can be used for high-risk AI practices where decision-making should be based on accountable and interpretable algorithms.
License: MPL-2.0
BugReports: https://github.com/inesortega/neuralGAM/issues
Encoding: UTF-8
Imports: tensorflow, keras, ggplot2, magrittr, reticulate, formula.tools, gridExtra
SystemRequirements: Python (>= 3.9), TensorFlow (https://www.tensorflow.org/)
Suggests: covr, testthat (>= 3.0.0), fs, withr
URL: https://inesortega.github.io/neuralGAM/
NeedsCompilation: no
Packaged: 2023-09-07 10:46:42 UTC; inesortega
Author: Ines Ortega-Fernandez [aut, cre, cph] , Marta Sestelo [aut, cph]
Repository: CRAN
Date/Publication: 2023-09-07 15:50:02 UTC

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Package lidR updated to version 4.0.4 with previous version 4.0.3 dated 2023-03-09

Title: Airborne LiDAR Data Manipulation and Visualization for Forestry Applications
Description: Airborne LiDAR (Light Detection and Ranging) interface for data manipulation and visualization. Read/write 'las' and 'laz' files, computation of metrics in area based approach, point filtering, artificial point reduction, classification from geographic data, normalization, individual tree segmentation and other manipulations.
Author: Jean-Romain Roussel [aut, cre, cph], David Auty [aut, ctb] , Florian De Boissieu [ctb] , Andrew Sanchez Meador [ctb] for segment_snags), Bourdon Jean-Francois [ctb] for track_sensor), Gatziolis Demetrios [ctb] for track_sensor), Leon Steinmeier [c [...truncated...]
Maintainer: Jean-Romain Roussel <jean-romain.roussel.1@ulaval.ca>

Diff between lidR versions 4.0.3 dated 2023-03-09 and 4.0.4 dated 2023-09-07

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Package cpfa updated to version 1.0-6 with previous version 1.0-5 dated 2023-08-07

Title: Classification with Parallel Factor Analysis
Description: Classification using Richard A. Harshman's Parallel Factor Analysis-1 (Parafac) model or Parallel Factor Analysis-2 (Parafac2) model fit to a three-way or four-way data array/tensor. See Harshman and Lundy (1994): <doi:10.1016/0167-9473(94)90132-5>. Uses component weights from one mode of the Parafac or Parafac2 model as features to tune parameters for one or more classification methods via a k-fold cross-validation procedure. Supports penalized logistic regression, support vector machine, random forest, and feed-forward neural network. Supports binary and multiclass classification. Predicts class labels or class probabilities and calculates multiple classification performance measures. Parallel computing is implemented via the 'parallel' and 'doParallel' packages.
Author: Matthew A. Snodgress <snodg031@umn.edu>
Maintainer: Matthew A. Snodgress <snodg031@umn.edu>

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Package ssdtools updated to version 1.0.6 with previous version 1.0.5 dated 2023-08-29

Title: Species Sensitivity Distributions
Description: Species sensitivity distributions are cumulative probability distributions which are fitted to toxicity concentrations for different species as described by Posthuma et al.(2001) <isbn:9781566705783>. The ssdtools package uses Maximum Likelihood to fit distributions such as the gamma, log-logistic, log-normal and Weibull to censored and/or weighted data. Multiple distributions can be averaged using Akaike Information Criteria. Confidence intervals on hazard concentrations and proportions are produced by parametric bootstrapping.
Author: Joe Thorley [aut, cre, ctr] , Carl Schwarz [aut, ctr], Rebecca Fisher [ctb], David Fox [ctb], Angeline Tillmanns [ctb], Ali Azizishirazi [ctb], Kathleen McTavish [ctb], Heather Thompson [ctb], Doug Spry [ctb], Rick van Dam [ctb], Graham Batley [ctb], [...truncated...]
Maintainer: Joe Thorley <joe@poissonconsulting.ca>

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Package TreatmentPatterns updated to version 2.5.1 with previous version 2.5.0 dated 2023-08-16

Title: Analyzes Real-World Treatment Patterns of a Study Population of Interest
Description: Computes treatment patterns within a given cohort using the Observational Medical Outcomes Partnership (OMOP) common data model (CDM). As described in Markus, Verhamme, Kors, and Rijnbeek (2022) <doi:10.1016/j.cmpb.2022.107081>.
Author: Aniek Markus [aut] , Maarten van Kessel [cre]
Maintainer: Maarten van Kessel <m.l.vankessel@erasmusmc.nl>

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Package spdesign updated to version 0.0.2 with previous version 0.0.1 dated 2023-08-17

Title: Designing Stated Preference Experiments
Description: Contemporary software commonly used to design stated preference experiments are expensive and the code is closed source. This is a free software package with an easy to use interface to make flexible stated preference experimental designs using state-of-the-art methods. For an overview of stated choice experimental design theory, see e.g., Rose, J. M. & Bliemer, M. C. J. (2014) in Hess S. & Daly. A. <doi:10.4337/9781781003152>. The package website can be accessed at <https://spdesign.edsandorf.me>. We acknowledge funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant INSPiRE (Grant agreement ID: 793163).
Author: Erlend Dancke Sandorf [aut, cre], Danny Campbell [aut]
Maintainer: Erlend Dancke Sandorf <erlend.dancke.sandorf@nmbu.no>

Diff between spdesign versions 0.0.1 dated 2023-08-17 and 0.0.2 dated 2023-09-07

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Package obfuscatoR updated to version 0.2.2 with previous version 0.2.1 dated 2020-11-19

Title: Obfuscation Game Designs
Description: When people make decisions, they may do so using a wide variety of decision rules. The package allows users to easily create obfuscation games to test the obfuscation hypothesis. It provides an easy to use interface and multiple options designed to vary the difficulty of the game and tailor it to the user's needs. For more detail: Chorus et al., 2021, Obfuscation maximization-based decision-making: Theory, methodology and first empirical evidence, Mathematical Social Sciences, 109, 28-44, <doi:10.1016/j.mathsocsci.2020.10.002>.
Author: Erlend Dancke Sandorf [aut, cre], Caspar Chorus [aut], Sander van Cranenburgh [aut]
Maintainer: Erlend Dancke Sandorf <erlend.dancke.sandorf@nmbu.no>

Diff between obfuscatoR versions 0.2.1 dated 2020-11-19 and 0.2.2 dated 2023-09-07

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Package MTA updated to version 0.5.0 with previous version 0.4.1 dated 2022-06-03

Title: Multiscalar Territorial Analysis
Description: Build multiscalar territorial analysis based on various contexts.
Author: Ronan Ysebaert [aut], Nicolas Lambert [aut], Timothee Giraud [aut, cre]
Maintainer: Timothee Giraud <timothee.giraud@cnrs.fr>

Diff between MTA versions 0.4.1 dated 2022-06-03 and 0.5.0 dated 2023-09-07

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Package x13binary updated to version 1.1.57-4 with previous version 1.1.57-3 dated 2022-02-06

Title: Provide the 'x13ashtml' Seasonal Adjustment Binary
Description: The US Census Bureau provides a seasonal adjustment program now called 'X-13ARIMA-SEATS' building on both earlier programs called X-11 and X-12 as well as the SEATS program by the Bank of Spain. The US Census Bureau offers both source and binary versions -- which this package integrates for use by other R packages.
Author: Dirk Eddelbuettel and Christoph Sax
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package thunder updated to version 1.1.2 with previous version 1.1.1 dated 2023-04-05

Title: Computation and Visualisation of Atmospheric Convective Parameters
Description: Allow to compute and visualise convective parameters commonly used in the operational prediction of severe convective storms. Core algorithm is based on a highly optimized 'C++' code linked into 'R' via 'Rcpp'. Highly efficient engine allows to derive thermodynamic and kinematic parameters from large numerical datasets such as reanalyses or operational Numerical Weather Prediction models in a reasonable amount of time. Package has been developed since 2017 by research meteorologists specializing in severe thunderstorms. The most relevant methods used in the package based on the following publications Stipanuk (1973) <https://apps.dtic.mil/sti/pdfs/AD0769739.pdf>, McCann et al. (1994) <doi:10.1175/1520-0434(1994)009%3C0532:WNIFFM%3E2.0.CO;2>, Bunkers et al. (2000) <doi:10.1175/1520-0434(2000)015%3C0061:PSMUAN%3E2.0.CO;2>, Corfidi et al. (2003) <doi:10.1175/1520-0434(2003)018%3C0997:CPAMPF%3E2.0.CO;2>, Showalter (1953) <doi:10.1175/1520-0477-34.6.250>, Coffe [...truncated...]
Author: Bartosz Czernecki [aut, cre] , Mateusz Taszarek [aut] , Piotr Szuster [aut] , Doug Nychka [ctb], Eric Gilleland [ctb], Liangying Zhang [ctb], Tim Hoar [ctb]
Maintainer: Bartosz Czernecki <nwp@amu.edu.pl>

Diff between thunder versions 1.1.1 dated 2023-04-05 and 1.1.2 dated 2023-09-07

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Package stranslate updated to version 0.1.1 with previous version 0.1.0 dated 2023-08-12

Title: Simple Translation Between Different Languages
Description: Message translation is often managed with 'po' files and the 'gettext' programme, but sometimes another solution is needed. In contrast to 'po' files, a more flexible approach is used as in the Fluent <https://projectfluent.org/> project with R Markdown snippets. The key-value approach allows easier handling of the translated messages.
Author: Sigbert Klinke [aut, cre]
Maintainer: Sigbert Klinke <sigbert@hu-berlin.de>

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Package prefio updated to version 0.1.1 with previous version 0.1.0 dated 2023-03-08

Title: Structures for Preference Data
Description: Convenient structures for creating, sourcing, reading, writing and manipulating ordinal preference data. Methods for writing to/from PrefLib formats. See Nicholas Mattei and Toby Walsh "PrefLib: A Library of Preference Data" (2013) <doi:10.1007/978-3-642-41575-3_20>.
Author: Floyd Everest [aut, cre] , Heather Turner [aut] , Damjan Vukcevic [aut]
Maintainer: Floyd Everest <me@floydeverest.com>

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Package qgg updated to version 1.1.2 with previous version 1.1.1 dated 2022-08-08

Title: Statistical Tools for Quantitative Genetic Analyses
Description: Provides an infrastructure for efficient processing of large-scale genetic and phenotypic data including core functions for: 1) fitting linear mixed models, 2) constructing marker-based genomic relationship matrices, 3) estimating genetic parameters (heritability and correlation), 4) performing genomic prediction and genetic risk profiling, and 5) single or multi-marker association analyses. Rohde et al. (2019) <doi:10.1101/503631>.
Author: Peter Soerensen [aut, cre], Palle Duun Rohde [aut], Izel Fourie Soerensen [aut]
Maintainer: Peter Soerensen <peter.sorensen@r-qgg.org>

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Package modelSSE updated to version 0.1-3 with previous version 0.1-2 dated 2023-08-28

Title: Modelling Infectious Disease Superspreading from Contact Tracing Data
Description: Comprehensive analytical tools are provided to characterize infectious disease superspreading from contact tracing surveillance data. The underlying theoretical frameworks of this toolkit include branching process with transmission heterogeneity (Lloyd-Smith et al. (2005) <doi:10.1038/nature04153>), case cluster size distribution (Nishiura et al. (2012) <doi:10.1016/j.jtbi.2011.10.039>, Blumberg et al. (2014) <doi:10.1371/journal.ppat.1004452>, and Kucharski and Althaus (2015) <doi:10.2807/1560-7917.ES2015.20.25.21167>), and decomposition of reproduction number (Zhao et al. (2022) <doi:10.1371/journal.pcbi.1010281>).
Author: Shi Zhao [aut, cre]
Maintainer: Shi Zhao <zhaoshi.cmsa@gmail.com>

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 man/d_outbreakdistn.Rd       |    6 +++---
 man/d_reproductiondistn.Rd   |    2 +-
 7 files changed, 37 insertions(+), 31 deletions(-)

More information about modelSSE at CRAN
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Package ineptR updated to version 0.2.1 with previous version 0.2.0 dated 2023-08-15

Title: Wrapper for Statistics Portugal API
Description: Set of wrapper and helper functions to facilitate interaction with the Statistics Portugal (Instituto Nacional de Estatistica - INE) API (<https://www.ine.pt/xportal/xmain?xpid=INE&xpgid=ine_api&INST=322751522&xlang=en>).
Author: Carlos Matos [aut, cre, cph]
Maintainer: Carlos Matos <carlosmdmatos@gmail.com>

Diff between ineptR versions 0.2.0 dated 2023-08-15 and 0.2.1 dated 2023-09-07

 DESCRIPTION         |   23 +++++++++--------
 MD5                 |   25 +++++++++++--------
 NAMESPACE           |    2 -
 NEWS.md             |    7 ++++-
 R/get_dim_info.R    |   15 ++++++++---
 R/get_dim_values.R  |   29 +++++++++-------------
 R/get_ine_data.R    |   68 ++++++++++++++++------------------------------------
 R/get_metadata.R    |    5 +++
 R/utils.R           |    7 +++--
 README.md           |    9 +++++-
 man/get_ine_data.Rd |    2 -
 tests               |only
 12 files changed, 97 insertions(+), 95 deletions(-)

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New package viralx with initial version 1.0.0
Package: viralx
Title: Explainers for Regression Models in HIV Research
Version: 1.0.0
Maintainer: Juan Pablo Acuna Gonzalez <22253567@uagro.mx>
Description: A dedicated viral-explainer model tool designed to empower researchers in the field of HIV research, particularly in viral load and CD4 (Cluster of Differentiation 4) lymphocytes regression modeling. Drawing inspiration from the 'tidymodels' framework for rigorous model building of Max Kuhn and Hadley Wickham (2020) <https://www.tidymodels.org>, and the 'DALEXtra' tool for explainability by Przemyslaw Biecek (2020) <arXiv:2009.13248>. It aims to facilitate interpretable and reproducible research in biostatistics and computational biology for the benefit of understanding HIV dynamics.
License: GPL (>= 3)
Encoding: UTF-8
Imports: DALEX, DALEXtra, dplyr, earth, Formula, parsnip, plotmo, plotrix, recipes, rsample, TeachingDemos, vdiffr, workflows
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2023-09-05 03:26:00 UTC; jp
Author: Juan Pablo Acuna Gonzalez [aut, cre]
Repository: CRAN
Date/Publication: 2023-09-07 09:00:02 UTC

More information about viralx at CRAN
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Package StanHeaders updated to version 2.26.28 with previous version 2.26.27 dated 2023-06-14

Title: C++ Header Files for Stan
Description: The C++ header files of the Stan project are provided by this package, but it contains little R code or documentation. The main reference is the vignette. There is a shared object containing part of the 'CVODES' library, but its functionality is not accessible from R. 'StanHeaders' is primarily useful for developers who want to utilize the 'LinkingTo' directive of their package's DESCRIPTION file to build on the Stan library without incurring unnecessary dependencies. The Stan project develops a probabilistic programming language that implements full or approximate Bayesian statistical inference via Markov Chain Monte Carlo or 'variational' methods and implements (optionally penalized) maximum likelihood estimation via optimization. The Stan library includes an advanced automatic differentiation scheme, 'templated' statistical and linear algebra functions that can handle the automatically 'differentiable' scalar types (and doubles, 'ints', etc.), and a parser for the Stan language. The [...truncated...]
Author: Ben Goodrich [cre, aut], Joshua Pritikin [ctb], Andrew Gelman [aut], Bob Carpenter [aut], Matt Hoffman [aut], Daniel Lee [aut], Michael Betancourt [aut], Marcus Brubaker [aut], Jiqiang Guo [aut], Peter Li [aut], Allen Riddell [aut], Marco Inacio [aut [...truncated...]
Maintainer: Ben Goodrich <benjamin.goodrich@columbia.edu>

Diff between StanHeaders versions 2.26.27 dated 2023-06-14 and 2.26.28 dated 2023-09-07

 DESCRIPTION                                           |    6 
 MD5                                                   |   16 
 R/Flags.R                                             |    4 
 inst/doc/stanmath.R                                   |    6 
 inst/doc/stanmath.Rmd                                 |   31 
 inst/doc/stanmath.html                                |  135 
 inst/include/stan/math/prim/prob/exponential_lpdf.hpp |    2 
 inst/stanc.js                                         |44826 ++++++++----------
 vignettes/stanmath.Rmd                                |   31 
 9 files changed, 22391 insertions(+), 22666 deletions(-)

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New package shinySbm with initial version 0.1.4
Package: shinySbm
Title: 'shiny' Application to Use the Stochastic Block Model
Version: 0.1.4
Description: A 'shiny' interface for a simpler use of the 'sbm' R package. It also contains useful functions to easily explore the 'sbm' package results. With this package you should be able to use the stochastic block model without any knowledge in R, get automatic reports and nice visuals, as well as learning the basic functions of 'sbm'.
BugReports: https://github.com/Jo-Theo/shinySbm/issues
License: MIT + file LICENSE
Depends: R (>= 3.50), sbm
Imports: colourpicker, config (>= 0.3.1), data.table, dplyr, DT, flextable, fresh, ggplot2, golem (>= 0.3.5), magrittr, parallel, patchwork, purrr, rmarkdown, shiny (>= 1.7.2), shinyalert, shinydashboard, stringr, visNetwork
Suggests: knitr, spelling, testthat (>= 3.0.0)
Encoding: UTF-8
Language: en-US
LazyData: true
NeedsCompilation: no
VignetteBuilder: knitr
Packaged: 2023-09-06 12:23:53 UTC; theod
Author: Theodore Vanrenterghem [cre, aut], Julie Aubert [aut] , Saint-Clair Chabert-Liddell [aut] , grossBM team [ctb], Golem User [cph]
Maintainer: Theodore Vanrenterghem <shiny.sbm.dev@gmail.com>
Repository: CRAN
Date/Publication: 2023-09-07 08:30:02 UTC

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Package riskRegression updated to version 2023.09.08 with previous version 2023.03.22 dated 2023-03-20

Title: Risk Regression Models and Prediction Scores for Survival Analysis with Competing Risks
Description: Implementation of the following methods for event history analysis. Risk regression models for survival endpoints also in the presence of competing risks are fitted using binomial regression based on a time sequence of binary event status variables. A formula interface for the Fine-Gray regression model and an interface for the combination of cause-specific Cox regression models. A toolbox for assessing and comparing performance of risk predictions (risk markers and risk prediction models). Prediction performance is measured by the Brier score and the area under the ROC curve for binary possibly time-dependent outcome. Inverse probability of censoring weighting and pseudo values are used to deal with right censored data. Lists of risk markers and lists of risk models are assessed simultaneously. Cross-validation repeatedly splits the data, trains the risk prediction models on one part of each split and then summarizes and compares the performance across splits.
Author: Thomas Alexander Gerds [aut, cre], Johan Sebastian Ohlendorff [aut], Paul Blanche [ctb], Rikke Mortensen [ctb], Marvin Wright [ctb], Nikolaj Tollenaar [ctb], John Muschelli [ctb], Ulla Brasch Mogensen [ctb], Brice Ozenne [aut]
Maintainer: Thomas Alexander Gerds <tag@biostat.ku.dk>

Diff between riskRegression versions 2023.03.22 dated 2023-03-20 and 2023.09.08 dated 2023-09-07

 riskRegression-2023.03.22/riskRegression/R/fitters.R                      |only
 riskRegression-2023.09.08/riskRegression/DESCRIPTION                      |    6 
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 riskRegression-2023.09.08/riskRegression/NAMESPACE                        |    6 
 riskRegression-2023.09.08/riskRegression/R/0onload.R                      |    6 
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 riskRegression-2023.09.08/riskRegression/R/AUC.competing.risks.R          |  154 +++-
 riskRegression-2023.09.08/riskRegression/R/AUC.survival.R                 |  118 +++
 riskRegression-2023.09.08/riskRegression/R/Brier.binary.R                 |   13 
 riskRegression-2023.09.08/riskRegression/R/Brier.competing.risks.R        |   29 
 riskRegression-2023.09.08/riskRegression/R/Brier.survival.R               |   27 
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 riskRegression-2023.09.08/riskRegression/R/as.data.table.predictCSC.R     |    9 
 riskRegression-2023.09.08/riskRegression/R/as.data.table.predictCox.R     |    9 
 riskRegression-2023.09.08/riskRegression/R/ate-pointEstimate.R            |    9 
 riskRegression-2023.09.08/riskRegression/R/ate.R                          |   39 -
 riskRegression-2023.09.08/riskRegression/R/autoplot.predictCSC.R          |    8 
 riskRegression-2023.09.08/riskRegression/R/calcCensoringWeightsCox.R      |   11 
 riskRegression-2023.09.08/riskRegression/R/computePerformance.R           |   14 
 riskRegression-2023.09.08/riskRegression/R/confint.ate.R                  |    6 
 riskRegression-2023.09.08/riskRegression/R/crossvalPerf.R                 |   26 
 riskRegression-2023.09.08/riskRegression/R/getCensoringWeights.R          |    6 
 riskRegression-2023.09.08/riskRegression/R/getCoxInfo.R                   |    8 
 riskRegression-2023.09.08/riskRegression/R/getInfluenceCurve.R            |    7 
 riskRegression-2023.09.08/riskRegression/R/getPerformanceData.R           |   13 
 riskRegression-2023.09.08/riskRegression/R/plotAUC.R                      |   13 
 riskRegression-2023.09.08/riskRegression/R/plotBrier.R                    |   17 
 riskRegression-2023.09.08/riskRegression/R/plotCalibration.R              |    8 
 riskRegression-2023.09.08/riskRegression/R/plotROC.R                      |    6 
 riskRegression-2023.09.08/riskRegression/R/plotRisk.R                     |  330 +++++-----
 riskRegression-2023.09.08/riskRegression/R/predict.CauseSpecificCox.R     |    4 
 riskRegression-2023.09.08/riskRegression/R/predict.riskRegression.R       |    5 
 riskRegression-2023.09.08/riskRegression/R/predictCox.R                   |   18 
 riskRegression-2023.09.08/riskRegression/R/predictCoxPL.R                 |   10 
 riskRegression-2023.09.08/riskRegression/R/predictRisk.R                  |  301 +++------
 riskRegression-2023.09.08/riskRegression/R/print.IPA.R                    |    6 
 riskRegression-2023.09.08/riskRegression/R/print.Score.R                  |    8 
 riskRegression-2023.09.08/riskRegression/R/print.influenceTest.R          |    8 
 riskRegression-2023.09.08/riskRegression/R/riskRegression-package.R       |   10 
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 riskRegression-2023.09.08/riskRegression/R/subjectWeights.R               |    1 
 riskRegression-2023.09.08/riskRegression/R/wglm.R                         |    6 
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 riskRegression-2023.09.08/riskRegression/man/Score.Rd                     |   32 
 riskRegression-2023.09.08/riskRegression/man/anova.ate.Rd                 |    2 
 riskRegression-2023.09.08/riskRegression/man/ate.Rd                       |    4 
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 riskRegression-2023.09.08/riskRegression/man/model.matrix.phreg.Rd        |    4 
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 riskRegression-2023.09.08/riskRegression/tests/testthat/test-iidCox.R     |   12 
 riskRegression-2023.09.08/riskRegression/tests/testthat/test-predictCox.R |   20 
 65 files changed, 1281 insertions(+), 826 deletions(-)

More information about riskRegression at CRAN
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Package rcontroll updated to version 0.1.1 with previous version 0.1.0 dated 2023-02-11

Title: Individual-Based Forest Growth Simulator 'TROLL'
Description: 'TROLL' is coded in C++ and it typically simulates hundreds of thousands of individuals over hundreds of years. The 'rcontroll' R package is a wrapper of 'TROLL'. 'rcontroll' includes functions that generate inputs for simulations and run simulations. Finally, it is possible to analyse the 'TROLL' outputs through tables, figures, and maps taking advantage of other R visualisation packages. 'rcontroll' also offers the possibility to generate a virtual LiDAR point cloud that corresponds to a snapshot of the simulated forest.
Author: Sylvain Schmitt [aut, cre] , Guillaume Salzet [aut] , Fabian Fischer [aut] , Isabelle Marechaux [aut] , Jerome Chave [aut]
Maintainer: Sylvain Schmitt <sylvain.m.schmitt@gmail.com>

Diff between rcontroll versions 0.1.0 dated 2023-02-11 and 0.1.1 dated 2023-09-07

 rcontroll-0.1.0/rcontroll/R/summary.trollsim.R            |only
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 rcontroll-0.1.1/rcontroll/MD5                             |  152 ++---
 rcontroll-0.1.1/rcontroll/NAMESPACE                       |    4 
 rcontroll-0.1.1/rcontroll/NEWS.md                         |  358 +++++++++++++
 rcontroll-0.1.1/rcontroll/R/TROLLv3_climatedaytime12.R    |   33 -
 rcontroll-0.1.1/rcontroll/R/TROLLv3_daytimevar.R          |   13 
 rcontroll-0.1.1/rcontroll/R/TROLLv3_input.R               |   10 
 rcontroll-0.1.1/rcontroll/R/TROLLv3_output.R              |   13 
 rcontroll-0.1.1/rcontroll/R/TROLLv3_pointcloud.R          |   12 
 rcontroll-0.1.1/rcontroll/R/TROLLv3_species.R             |    6 
 rcontroll-0.1.1/rcontroll/R/TROLLversion.R                |   11 
 rcontroll-0.1.1/rcontroll/R/autogif.R                     |  129 +++-
 rcontroll-0.1.1/rcontroll/R/autoplot.troll.R              |   46 +
 rcontroll-0.1.1/rcontroll/R/generate_climate.R            |  349 ++++++++++---
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 rcontroll-0.1.1/rcontroll/R/update_parameters.trollsim.R  |   15 
 rcontroll-0.1.1/rcontroll/R/zzz.R                         |    8 
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 80 files changed, 2795 insertions(+), 1469 deletions(-)

More information about rcontroll at CRAN
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Package DPQ updated to version 0.5-6 with previous version 0.5-5 dated 2023-06-23

Title: Density, Probability, Quantile ('DPQ') Computations
Description: Computations for approximations and alternatives for the 'DPQ' (Density (pdf), Probability (cdf) and Quantile) functions for probability distributions in R. Primary focus is on (central and non-central) beta, gamma and related distributions such as the chi-squared, F, and t. -- For several distribution functions, provide functions implementing formulas from Johnson, Kotz, and Kemp (1992) <doi:10.1002/bimj.4710360207> and Johnson, Kotz, and Balakrishnan (1995) for discrete or continuous distributions respectively. This is for the use of researchers in these numerical approximation implementations, notably for my own use in order to improve standard R pbeta(), qgamma(), ..., etc: {'"dpq"'-functions}.
Author: Martin Maechler [aut, cre] , Morten Welinder [ctb] ), Wolfgang Viechtbauer [ctb] , 2002), Ross Ihaka [ctb] , Marius Hofert [ctb] , lssum), R-core [ctb] , R Foundation [cph]
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>

Diff between DPQ versions 0.5-5 dated 2023-06-23 and 0.5-6 dated 2023-09-07

 DESCRIPTION                   |   14 +++--
 MD5                           |   80 +++++++++++++++----------------
 NAMESPACE                     |    3 -
 R/dgamma.R                    |   24 ++-------
 R/hyper-dist.R                |   48 ++++++++++++-------
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 build/partial.rdb             |binary
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 tests/hyper-dist-ex.R         |  106 ++++++++++++++++++++++++++++--------------
 tests/qPoisBinom-ex.R         |    3 -
 41 files changed, 433 insertions(+), 279 deletions(-)

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Package DatabaseConnector updated to version 6.2.4 with previous version 6.2.3 dated 2023-06-29

Title: Connecting to Various Database Platforms
Description: An R 'DataBase Interface' ('DBI') compatible interface to various database platforms ('PostgreSQL', 'Oracle', 'Microsoft SQL Server', 'Amazon Redshift', 'Microsoft Parallel Database Warehouse', 'IBM Netezza', 'Apache Impala', 'Google BigQuery', 'Snowflake', 'Spark', and 'SQLite'). Also includes support for fetching data as 'Andromeda' objects. Uses either 'Java Database Connectivity' ('JDBC') or other 'DBI' drivers to connect to databases.
Author: Martijn Schuemie [aut, cre], Marc Suchard [aut], Observational Health Data Science and Informatics [cph], Microsoft Inc. [cph] , PostgreSQL Global Development Group [cph] , Oracle Inc. [cph] , Amazon Inc. [cph]
Maintainer: Martijn Schuemie <schuemie@ohdsi.org>

Diff between DatabaseConnector versions 6.2.3 dated 2023-06-29 and 6.2.4 dated 2023-09-07

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 DatabaseConnector-6.2.4/DatabaseConnector/DESCRIPTION                                                         |   10 
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Package LDM updated to version 6.0.1 with previous version 6.0 dated 2023-09-04

Title: Testing Hypotheses About the Microbiome using the Linear Decomposition Model
Description: A single analysis path that includes distance-based ordination, global tests of any effect of the microbiome, and tests of the effects of individual taxa with false-discovery-rate (FDR) control. It accommodates both continuous and discrete covariates as well as interaction terms to be tested either singly or in combination, allows for adjustment of confounding covariates, and uses permutation-based p-values that can control for sample correlations. It can be applied to transformed data, and an omnibus test can combine results from analyses conducted on different transformation scales. It can also be used for testing presence-absence associations based on infinite number of rarefaction replicates, testing mediation effects of the microbiome, analyzing censored time-to-event outcomes, and for compositional analysis by fitting linear models to centered-log-ratio taxa count data.
Author: Yi-Juan Hu [aut, cre], Glen A Satten [aut]
Maintainer: Yi-Juan Hu <yijuan.hu@emory.edu>

Diff between LDM versions 6.0 dated 2023-09-04 and 6.0.1 dated 2023-09-07

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New package karyotapR with initial version 1.0.1
Package: karyotapR
Title: DNA Copy Number Analysis for Genome-Wide Tapestri Panels
Version: 1.0.1
Description: Analysis of DNA copy number in single cells using custom genome-wide targeted DNA sequencing panels for the Mission Bio Tapestri platform. Users can easily parse, manipulate, and visualize datasets produced from the automated 'Tapestri Pipeline', with support for normalization, clustering, and copy number calling. Functions are also available to deconvolute multiplexed samples by genotype and parsing barcoded reads from exogenous lentiviral constructs.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/joeymays/karyotapR, http://joeymays.xyz/karyotapR/
BugReports: https://github.com/joeymays/karyotapR/issues
Imports: circlize, cli, ComplexHeatmap, dbscan, dplyr, fitdistrplus, GenomicRanges, ggplot2, gtools, IRanges, magrittr, methods, purrr, rhdf5, rlang, S4Vectors, stats, SummarizedExperiment, tibble, tidyr, umap, viridisLite
Depends: R (>= 3.6), SingleCellExperiment
Suggests: Biostrings, knitr, rmarkdown, Rsamtools, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2023-09-07 00:46:54 UTC; jcm844
Author: Joseph Mays [aut, cre, cph]
Maintainer: Joseph Mays <josephcmays@gmail.com>
Repository: CRAN
Date/Publication: 2023-09-07 08:50:05 UTC

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New package jointCalib with initial version 0.1.0
Package: jointCalib
Title: A Joint Calibration of Totals and Quantiles
Version: 0.1.0
Description: A small package containing functions to perform a joint calibration of totals and quantiles. The calibration for totals is based on Deville and Särndal (1992) <doi:10.1080/01621459.1992.10475217>, the calibration for quantiles is based on Harms and Duchesne (2006) <https://www150.statcan.gc.ca/n1/en/catalogue/12-001-X20060019255>. The package uses standard calibration via the 'survey', 'sampling' or 'laeken' packages. In addition, entropy balancing via the 'ebal' package and empirical likelihood based on codes from Wu (2005) <https://www150.statcan.gc.ca/n1/pub/12-001-x/2005002/article/9051-eng.pdf> can be used. See the paper by Beręsewicz and Szymkowiak (2023) for details <arXiv:2308.13281>.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.5.0)
URL: https://github.com/ncn-foreigners/jointCalib, https://ncn-foreigners.github.io/jointCalib/
BugReports: https://github.com/ncn-foreigners/jointCalib/issues
Imports: laeken, sampling, mathjaxr, survey, MASS, ebal
NeedsCompilation: no
Packaged: 2023-09-06 11:40:07 UTC; berenz
Author: Maciej Beresewicz [aut, cre]
Maintainer: Maciej Beresewicz <maciej.beresewicz@ue.poznan.pl>
Repository: CRAN
Date/Publication: 2023-09-07 08:30:06 UTC

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Package HOasso updated to version 1.0.1 with previous version 1.0.0 dated 2023-08-11

Title: Higher Order Assortativity for Complex Networks
Description: Allows to evaluate Higher Order Assortativity of complex networks defined through objects of class 'igraph' from the package of the same name. The package returns a result also for directed and weighted graphs. References, Arcagni, A., Grassi, R., Stefani, S., & Torriero, A. (2017) <doi:10.1016/j.ejor.2017.04.028> Arcagni, A., Grassi, R., Stefani, S., & Torriero, A. (2021) <doi:10.1016/j.jbusres.2019.10.008> Arcagni, A., Cerqueti, R., & Grassi, R. (2023) <doi:10.48550/arXiv.2304.01737>.
Author: Alberto Arcagni [aut, cre], Roy Cerqueti [aut], Rosanna Grassi [aut]
Maintainer: Alberto Arcagni <alberto.arcagni@uniroma1.it>

Diff between HOasso versions 1.0.0 dated 2023-08-11 and 1.0.1 dated 2023-09-07

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Package genekitr updated to version 1.2.5 with previous version 1.2.2 dated 2023-05-23

Title: Gene Analysis Toolkit
Description: An analysis toolkit focused on genes. It mainly includes five features (search, convert, analysis, plot, and export). The user just needs to input feature id ('entrez', 'symbol', 'ensembl' or 'uniprot') to retrieve feature information and 'PubMed'<https://pubmed.ncbi.nlm.nih.gov/> records, to convert id types, to easily handle gene enrichment analysis and publication-level figures, to plot group interaction and export results as sheets in one 'excel' file to easily share and communicate with others.
Author: Yunze Liu [aut, cre]
Maintainer: Yunze Liu <jieandze1314@gmail.com>

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Package EFA.dimensions updated to version 0.1.7.9 with previous version 0.1.7.7 dated 2023-03-17

Title: Exploratory Factor Analysis Functions for Assessing Dimensionality
Description: Functions for eleven procedures for determining the number of factors, including functions for parallel analysis and the minimum average partial test. There are also functions for conducting principal components analysis, principal axis factor analysis, maximum likelihood factor analysis, image factor analysis, and extension factor analysis, all of which can take raw data or correlation matrices as input and with options for conducting the analyses using Pearson correlations, Kendall correlations, Spearman correlations, gamma correlations, or polychoric correlations. Varimax rotation, promax rotation, and Procrustes rotations can be performed. Additional functions focus on the factorability of a correlation matrix, the congruences between factors from different datasets, the assessment of local independence, the assessment of factor solution complexity, and internal consistency. Auerswald & Moshagen (2019, ISSN:1939-1463); Field, Miles, & Field (2012, ISBN:978-1-4462-0045-2); M [...truncated...]
Author: Brian P. O'Connor [aut, cre]
Maintainer: Brian P. O'Connor <brian.oconnor@ubc.ca>

Diff between EFA.dimensions versions 0.1.7.7 dated 2023-03-17 and 0.1.7.9 dated 2023-09-07

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New package defm with initial version 0.1-1
Package: defm
Title: Estimation and Simulation of Multi-Binary Response Models
Version: 0.1-1
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, stats
Depends: R (>= 2.10), stats4
Suggests: texreg
NeedsCompilation: yes
Packaged: 2023-09-06 21:40:07 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: 2023-09-07 08:30:07 UTC

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Package spatstat.model updated to version 3.2-6 with previous version 3.2-4 dated 2023-05-15

Title: Parametric Statistical Modelling and Inference for the 'spatstat' Family
Description: Functionality for parametric statistical modelling and inference for spatial data, mainly spatial point patterns, in the 'spatstat' family of packages. (Excludes analysis of spatial data on a linear network, which is covered by the separate package 'spatstat.linnet'.) Supports parametric modelling, formal statistical inference, and model validation. Parametric models include Poisson point processes, Cox point processes, Neyman-Scott cluster processes, Gibbs point processes and determinantal point processes. Models can be fitted to data using maximum likelihood, maximum pseudolikelihood, maximum composite likelihood and the method of minimum contrast. Fitted models can be simulated and predicted. Formal inference includes hypothesis tests (quadrat counting tests, Cressie-Read tests, Clark-Evans test, Berman test, Diggle-Cressie-Loosmore-Ford test, scan test, studentised permutation test, segregation test, ANOVA tests of fitted models, adjusted composite likelihood ratio test, envelope t [...truncated...]
Author: Adrian Baddeley [aut, cre, cph] , Rolf Turner [aut, cph] , Ege Rubak [aut, cph] , Kasper Klitgaard Berthelsen [ctb], Achmad Choiruddin [ctb, cph], Jean-Francois Coeurjolly [ctb], Ottmar Cronie [ctb], Tilman Davies [ctb], Julian Gilbey [ctb], Yongtao [...truncated...]
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>

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Package radiant.data updated to version 1.6.1 with previous version 1.6.0 dated 2023-09-06

Title: Data Menu for Radiant: Business Analytics using R and Shiny
Description: The Radiant Data menu includes interfaces for loading, saving, viewing, visualizing, summarizing, transforming, and combining data. It also contains functionality to generate reproducible reports of the analyses conducted in the application.
Author: Vincent Nijs [aut, cre], Niklas von Hertzen [aut]
Maintainer: Vincent Nijs <radiant@rady.ucsd.edu>

Diff between radiant.data versions 1.6.0 dated 2023-09-06 and 1.6.1 dated 2023-09-07

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Package mFD updated to version 1.0.5 with previous version 1.0.4 dated 2023-05-17

Title: Compute and Illustrate the Multiple Facets of Functional Diversity
Description: Computing functional traits-based distances between pairs of species for species gathered in assemblages allowing to build several functional spaces. The package allows to compute functional diversity indices assessing the distribution of species (and of their dominance) in a given functional space for each assemblage and the overlap between assemblages in a given functional space, see: Chao et al. (2018) <doi:10.1002/ecm.1343>, Maire et al. (2015) <doi:10.1111/geb.12299>, Mouillot et al. (2013) <doi:10.1016/j.tree.2012.10.004>, Mouillot et al. (2014) <doi:10.1073/pnas.1317625111>, Ricotta and Szeidl (2009) <doi:10.1016/j.tpb.2009.10.001>. Graphical outputs are included. Visit the 'mFD' website for more information, documentation and examples.
Author: Camille Magneville [aut, cre, cph] , Nicolas Loiseau [aut] , Camille Albouy [aut] , Nicolas Casajus [aut] , Thomas Claverie [aut] , Arthur Escalas [aut] , Fabien Leprieur [aut] , Eva Maire [aut] , David Mouillot [aut] , Sebastien Villeger [aut]
Maintainer: Camille Magneville <camille.magneville@gmail.com>

Diff between mFD versions 1.0.4 dated 2023-05-17 and 1.0.5 dated 2023-09-07

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New package daiR with initial version 0.9.9
Package: daiR
Title: Interface with Google Cloud Document AI API
Version: 0.9.9
Description: R interface for the Google Cloud Services 'Document AI API' <https://cloud.google.com/document-ai/> with additional tools for output file parsing and text reconstruction. 'Document AI' is a powerful server-based OCR processor that extracts text and tables from images and PDF files with high accuracy. 'daiR' gives R users programmatic access to this processor and additional tools to handle and visualize the output. See the package website <https://dair.info/> for more information and examples.
License: MIT + file LICENSE
URL: https://github.com/Hegghammer/daiR, https://dair.info
BugReports: https://github.com/Hegghammer/daiR/issues
Depends: R (>= 4.2.0)
Imports: base64enc, beepr, data.table, fs, gargle, glue, googleCloudStorageR, graphics, grDevices, httr, jsonlite, magick, pdftools, purrr, readtext, stats, stringr, utils, xml2
Suggests: knitr, ngram, rmarkdown, testthat (>= 3.1.10)
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2023-09-07 06:50:48 UTC; thomas
Author: Thomas Hegghammer [aut, cre]
Maintainer: Thomas Hegghammer <hegghammer@gmail.com>
Repository: CRAN
Date/Publication: 2023-09-07 07:10:13 UTC

More information about daiR at CRAN
Permanent link

Package bnlearn updated to version 4.9 with previous version 4.8.3 dated 2023-04-29

Title: Bayesian Network Structure Learning, Parameter Learning and Inference
Description: Bayesian network structure learning, parameter learning and inference. This package implements constraint-based (PC, GS, IAMB, Inter-IAMB, Fast-IAMB, MMPC, Hiton-PC, HPC), pairwise (ARACNE and Chow-Liu), score-based (Hill-Climbing and Tabu Search) and hybrid (MMHC, RSMAX2, H2PC) structure learning algorithms for discrete, Gaussian and conditional Gaussian networks, along with many score functions and conditional independence tests. The Naive Bayes and the Tree-Augmented Naive Bayes (TAN) classifiers are also implemented. Some utility functions (model comparison and manipulation, random data generation, arc orientation testing, simple and advanced plots) are included, as well as support for parameter estimation (maximum likelihood and Bayesian) and inference, conditional probability queries, cross-validation, bootstrap and model averaging. Development snapshots with the latest bugfixes are available from <https://www.bnlearn.com/>.
Author: Marco Scutari [aut, cre], Tomi Silander [ctb], Robert Ness [ctb]
Maintainer: Marco Scutari <scutari@bnlearn.com>

Diff between bnlearn versions 4.8.3 dated 2023-04-29 and 4.9 dated 2023-09-07

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 bnlearn-4.9/bnlearn/Changelog                                                  |   54 +
 bnlearn-4.9/bnlearn/DESCRIPTION                                                |   14 
 bnlearn-4.9/bnlearn/MD5                                                        |  271 +++----
 bnlearn-4.9/bnlearn/NAMESPACE                                                  |    5 
 bnlearn-4.9/bnlearn/R/aracne.R                                                 |    5 
 bnlearn-4.9/bnlearn/R/arc.strength.R                                           |   34 
 bnlearn-4.9/bnlearn/R/backend-indep.R                                          |   20 
 bnlearn-4.9/bnlearn/R/chow.liu.R                                               |    4 
 bnlearn-4.9/bnlearn/R/ci.test.R                                                |   12 
 bnlearn-4.9/bnlearn/R/classifiers.R                                            |    9 
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 bnlearn-4.9/bnlearn/R/cv.R                                                     |   19 
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 bnlearn-4.9/bnlearn/R/fast-iamb.R                                              |   14 
 bnlearn-4.9/bnlearn/R/fit.R                                                    |  186 ++++
 bnlearn-4.9/bnlearn/R/foreign-read.R                                           |   15 
 bnlearn-4.9/bnlearn/R/foreign-write.R                                          |    2 
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 bnlearn-4.9/bnlearn/R/frontend-strength.R                                      |   29 
 bnlearn-4.9/bnlearn/R/gRain.R                                                  |   14 
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 bnlearn-4.9/bnlearn/R/hill-climbing.R                                          |    4 
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 bnlearn-4.9/bnlearn/R/pcalgo.R                                                 |   10 
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 bnlearn-4.9/bnlearn/R/sanitization-misc.R                                      |    8 
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 bnlearn-4.9/bnlearn/R/simulation.R                                             |    2 
 bnlearn-4.9/bnlearn/R/tabu.R                                                   |   58 +
 bnlearn-4.9/bnlearn/R/test.R                                                   |   14 
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 bnlearn-4.9/bnlearn/R/utils-graph.R                                            |    6 
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 bnlearn-4.9/bnlearn/man/compare.Rd                                             |    6 
 bnlearn-4.9/bnlearn/man/cpdag.Rd                                               |    6 
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 bnlearn-4.9/bnlearn/man/mb.Rd                                                  |   24 
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 bnlearn-4.9/bnlearn/src/Makevars                                               |   20 
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Package cancerGI updated to version 1.0.1 with previous version 1.0.0 dated 2016-04-01

Title: Analyses of Cancer Gene Interaction
Description: Functions to perform the following analyses: i) inferring epistasis from RNAi double knockdown data; ii) identifying gene pairs of multiple mutation patterns; iii) assessing association between gene pairs and survival; and iv) calculating the smallworldness of a graph (e.g., a gene interaction network). Data and analyses are described in Wang, X., Fu, A. Q., McNerney, M. and White, K. P. (2014). Widespread genetic epistasis among breast cancer genes. Nature Communications. 5 4828. <doi:10.1038/ncomms5828>.
Author: Audrey Qiuyan Fu and Xiaoyue Wang
Maintainer: Audrey Q. Fu <audreyqyfu@gmail.com>

Diff between cancerGI versions 1.0.0 dated 2016-04-01 and 1.0.1 dated 2023-09-07

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 cancerGI-1.0.1/cancerGI/DESCRIPTION                                       |    8 +-
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 8 files changed, 37 insertions(+), 28 deletions(-)

More information about cancerGI at CRAN
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Package spatstat.explore updated to version 3.2-3 with previous version 3.2-1 dated 2023-05-13

Title: Exploratory Data Analysis for the 'spatstat' Family
Description: Functionality for exploratory data analysis and nonparametric analysis of spatial data, mainly spatial point patterns, in the 'spatstat' family of packages. (Excludes analysis of spatial data on a linear network, which is covered by the separate package 'spatstat.linnet'.) Methods include quadrat counts, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, ANOVA) are also supported.
Author: Adrian Baddeley [aut, cre, cph] , Rolf Turner [aut, cph] , Ege Rubak [aut, cph] , Kasper Klitgaard Berthelsen [ctb], Warick Brown [cph], Achmad Choiruddin [ctb], Jean-Francois Coeurjolly [ctb], Ottmar Cronie [ctb], Tilman Davies [ctb, cph], Julian Gi [...truncated...]
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>

Diff between spatstat.explore versions 3.2-1 dated 2023-05-13 and 3.2-3 dated 2023-09-07

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 20 files changed, 349 insertions(+), 161 deletions(-)

More information about spatstat.explore at CRAN
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Package IAPWS95 (with last version 1.2.3) was removed from CRAN

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

2023-09-05 1.2.3
2023-07-11 1.2.2
2023-03-28 1.2.1
2022-06-24 1.2.0

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Package retrodesign (with last version 0.2.0) was removed from CRAN

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

2023-08-24 0.2.0
2019-03-08 0.1.0

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