Fri, 12 Jul 2024

Package cmhc updated to version 0.2.8 with previous version 0.2.7 dated 2023-12-13

Title: Access, Retrieve, and Work with CMHC Data
Description: Wrapper around the Canadian Mortgage and Housing Corporation (CMHC) web interface. It enables programmatic and reproducible access to a wide variety of housing data from CMHC.
Author: Jens von Bergmann
Maintainer: Jens von Bergmann <jens@mountainmath.ca>

Diff between cmhc versions 0.2.7 dated 2023-12-13 and 0.2.8 dated 2024-07-12

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Package lqr updated to version 5.2 with previous version 5.1 dated 2024-06-28

Title: Robust Linear Quantile Regression
Description: It fits a robust linear quantile regression model using a new family of zero-quantile distributions for the error term. Missing values and censored observations can be handled as well. This family of distribution includes skewed versions of the Normal, Student's t, Laplace, Slash and Contaminated Normal distribution. It also performs logistic quantile regression for bounded responses as shown in Galarza et.al.(2020) <doi:10.1007/s13571-020-00231-0>. It provides estimates and full inference. It also provides envelopes plots for assessing the fit and confidences bands when several quantiles are provided simultaneously.
Author: Christian E. Galarza <chedgala@espol.edu.ec>, Luis Benites <lbenitess@pucp.edu.pe>, Marcelo Bourguignon <m.p.bourguignon@gmail.com>, Victor H. Lachos <hlachos@uconn.edu>
Maintainer: Christian E. Galarza <cgalarza88@gmail.com>

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Package qrNLMM updated to version 3.4 with previous version 3.3 dated 2022-08-18

Title: Quantile Regression for Nonlinear Mixed-Effects Models
Description: Quantile regression (QR) for Nonlinear Mixed-Effects Models via the asymmetric Laplace distribution (ALD). It uses the Stochastic Approximation of the EM (SAEM) algorithm for deriving exact maximum likelihood estimates and full inference results for the fixed-effects and variance components. It also provides prediction and graphical summaries for assessing the algorithm convergence and fitting results.
Author: Christian E. Galarza <chedgala@espol.edu.ec> and Victor H. Lachos <hlachos@uconn.edu>
Maintainer: Christian E. Galarza <cgalarza88@gmail.com>

Diff between qrNLMM versions 3.3 dated 2022-08-18 and 3.4 dated 2024-07-12

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Package missRanger updated to version 2.5.0 with previous version 2.4.0 dated 2023-11-19

Title: Fast Imputation of Missing Values
Description: Alternative implementation of the beautiful 'MissForest' algorithm used to impute mixed-type data sets by chaining random forests, introduced by Stekhoven, D.J. and Buehlmann, P. (2012) <doi:10.1093/bioinformatics/btr597>. Under the hood, it uses the lightning fast random forest package 'ranger'. Between the iterative model fitting, we offer the option of using predictive mean matching. This firstly avoids imputation with values not already present in the original data (like a value 0.3334 in 0-1 coded variable). Secondly, predictive mean matching tries to raise the variance in the resulting conditional distributions to a realistic level. This would allow, e.g., to do multiple imputation when repeating the call to missRanger(). A formula interface allows to control which variables should be imputed by which.
Author: Michael Mayer [aut, cre]
Maintainer: Michael Mayer <mayermichael79@gmail.com>

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Package mirtCAT updated to version 1.14 with previous version 1.13 dated 2023-10-17

Title: Computerized Adaptive Testing with Multidimensional Item Response Theory
Description: Provides tools to generate HTML interfaces for adaptive and non-adaptive tests using the shiny package (Chalmers (2016) <doi:10.18637/jss.v071.i05>). Suitable for applying unidimensional and multidimensional computerized adaptive tests (CAT) using item response theory methodology and for creating simple questionnaires forms to collect response data directly in R. Additionally, optimal test designs (e.g., "shadow testing") are supported for tests that contain a large number of item selection constraints. Finally, package contains tools useful for performing Monte Carlo simulations for studying test item banks.
Author: Phil Chalmers [aut, cre] , Magnus Nordmo [ctb]
Maintainer: Phil Chalmers <rphilip.chalmers@gmail.com>

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Package kernelshap updated to version 0.6.0 with previous version 0.5.0 dated 2024-05-26

Title: Kernel SHAP
Description: Efficient implementation of Kernel SHAP, see Lundberg and Lee (2017), and Covert and Lee (2021) <http://proceedings.mlr.press/v130/covert21a>. Furthermore, for up to 14 features, exact permutation SHAP values can be calculated. The package plays well together with meta-learning packages like 'tidymodels', 'caret' or 'mlr3'. Visualizations can be done using the R package 'shapviz'.
Author: Michael Mayer [aut, cre] , David Watson [aut] , Przemyslaw Biecek [ctb]
Maintainer: Michael Mayer <mayermichael79@gmail.com>

Diff between kernelshap versions 0.5.0 dated 2024-05-26 and 0.6.0 dated 2024-07-12

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Package genMCMCDiag updated to version 0.2.2 with previous version 0.2.1 dated 2024-05-10

Title: Generalized Convergence Diagnostics for Difficult MCMC Algorithms
Description: Trace plots and convergence diagnostics for Markov Chain Monte Carlo (MCMC) algorithms on highly multivariate or unordered spaces. Methods outlined in a forthcoming paper.
Author: Luke Duttweiler [aut, cre, cph]
Maintainer: Luke Duttweiler <lduttweiler@hsph.harvard.edu>

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Package adaR updated to version 0.3.3 with previous version 0.3.2 dated 2024-02-08

Title: A Fast 'WHATWG' Compliant URL Parser
Description: A wrapper for 'ada-url', a 'WHATWG' compliant and fast URL parser written in modern 'C++'. Also contains auxiliary functions such as a public suffix extractor.
Author: David Schoch [aut, cre] , Chung-hong Chan [aut] , Yagiz Nizipli [ctb, cph] , Daniel Lemire [ctb, cph]
Maintainer: David Schoch <david@schochastics.net>

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Package qrLMM updated to version 2.3 with previous version 2.2 dated 2022-10-25

Title: Quantile Regression for Linear Mixed-Effects Models
Description: Quantile regression (QR) for Linear Mixed-Effects Models via the asymmetric Laplace distribution (ALD). It uses the Stochastic Approximation of the EM (SAEM) algorithm for deriving exact maximum likelihood estimates and full inference results for the fixed-effects and variance components. It also provides graphical summaries for assessing the algorithm convergence and fitting results.
Author: Christian E. Galarza <cgalarza88@gmail.com> and Victor H. Lachos <hlachos@ime.unicamp.br>
Maintainer: Christian E. Galarza <cgalarza88@gmail.com>

Diff between qrLMM versions 2.2 dated 2022-10-25 and 2.3 dated 2024-07-12

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Package kayadata updated to version 1.4.0 with previous version 1.3.0 dated 2023-07-17

Title: Kaya Identity Data for Nations and Regions
Description: Provides data for Kaya identity variables (population, gross domestic product, primary energy consumption, and energy-related CO2 emissions) for the world and for individual nations, and utility functions for looking up data, plotting trends of Kaya variables, and plotting the fuel mix for a given country or region. The Kaya identity (Yoichi Kaya and Keiichi Yokobori, "Environment, Energy, and Economy: Strategies for Sustainability" (United Nations University Press, 1998) and <https://en.wikipedia.org/wiki/Kaya_identity>) expresses a nation's or region's greenhouse gas emissions in terms of its population, per-capita Gross Domestic Product, the energy intensity of its economy, and the carbon-intensity of its energy supply.
Author: Jonathan Gilligan [cre, aut]
Maintainer: Jonathan Gilligan <jonathan.gilligan@vanderbilt.edu>

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Package damAOI updated to version 0.1 with previous version 0.0 dated 2024-02-07

Title: Create an 'Area of Interest' Around a Constructed Dam for Comparative Impact Evaluations
Description: Define a spatial 'Area of Interest' (AOI) around a constructed dam using hydrology data. Dams have environmental and social impacts, both positive and negative. Current analyses of dams have no consistent way to specify at what spatial extent we should evaluate these impacts. 'damAOI' implements methods to adjust reservoir polygons to match satellite-observed surface water areas, plot upstream and downstream rivers using elevation data and accumulated river flow, and draw buffers clipped by river basins around reservoirs and relevant rivers. This helps to consistently determine the areas which could be impacted by dam construction, facilitating comparative analysis and informed infrastructure investments.
Author: Chris Littleboy [aut, cre] , Isabel Jones [ctb, fnd]
Maintainer: Chris Littleboy <chris.littleboy@stir.ac.uk>

Diff between damAOI versions 0.0 dated 2024-02-07 and 0.1 dated 2024-07-12

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New package SmithWilsonYieldCurve with initial version 1.1.1
Package: SmithWilsonYieldCurve
Title: Smith-Wilson Yield Curve Construction
Version: 1.1.1
Date: 2024-07-11
Description: Constructs a yield curve by the Smith-Wilson method from a table of libor and swap rates. Now updated to take bond coupons and prices in the same table.
License: GPL-3
Suggests: testthat
Packaged: 2024-07-11 06:53:34 UTC; philj
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2024-07-12 15:20:05 UTC
Author: Phil Joubert [aut, cre]
Maintainer: Phil Joubert <phil.joubert@gmail.com>

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New package SCIntRuler with initial version 0.99.6
Package: SCIntRuler
Title: Guiding the Integration of Multiple Single-Cell RNA-Seq Datasets
Version: 0.99.6
Maintainer: Yue Lyu <yuelyu0521@gmail.com>
Description: The accumulation of single-cell RNA-seq ('scRNA-seq') studies highlights the potential benefits of integrating multiple datasets. By augmenting sample sizes and enhancing analytical robustness, integration can lead to more insightful biological conclusions. However, challenges arise due to the inherent diversity and batch discrepancies within and across studies. 'SCIntRuler', a novel R package, addresses these challenges by guiding the integration of multiple 'scRNA-seq' datasets.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: Rcpp, Matrix, batchelor, base, Seurat, SeuratObject, MatrixGenerics, SingleCellExperiment, SummarizedExperiment, dplyr, coin, harmony, ggplot2, gridExtra, cowplot, magrittr, stats
LinkingTo: Rcpp
URL: https://github.com/yuelyu21/SCIntRuler, https://yuelyu21.github.io/SCIntRuler/
BugReports: https://github.com/yuelyu21/SCIntRuler/issues
Suggests: BiocStyle, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Depends: R (>= 4.3.0)
LazyData: true
LazyDataCompression: xz
NeedsCompilation: yes
Packaged: 2024-07-11 06:55:10 UTC; a98455
Author: Yue Lyu [aut, cre]
Repository: CRAN
Date/Publication: 2024-07-12 15:20:08 UTC

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Package pdynmc updated to version 0.9.11 with previous version 0.9.10 dated 2023-11-24

Title: Moment Condition Based Estimation of Linear Dynamic Panel Data Models
Description: Linear dynamic panel data modeling based on linear and nonlinear moment conditions as proposed by Holtz-Eakin, Newey, and Rosen (1988) <doi:10.2307/1913103>, Ahn and Schmidt (1995) <doi:10.1016/0304-4076(94)01641-C>, and Arellano and Bover (1995) <doi:10.1016/0304-4076(94)01642-D>. Estimation of the model parameters relies on the Generalized Method of Moments (GMM) and instrumental variables (IV) estimation, numerical optimization (when nonlinear moment conditions are employed) and the computation of closed form solutions (when estimation is based on linear moment conditions). One-step, two-step and iterated estimation is available. For inference and specification testing, Windmeijer (2005) <doi:10.1016/j.jeconom.2004.02.005> and doubly corrected standard errors (Hwang, Kang, Lee, 2021 <doi:10.1016/j.jeconom.2020.09.010>) are available. Additionally, serial correlation tests, tests for overidentification, and Wald tests are provided. Functions for visualiz [...truncated...]
Author: Markus Fritsch [aut, cre], Joachim Schnurbus [aut], Andrew Adrian Yu Pua [aut]
Maintainer: Markus Fritsch <Markus.Fritsch@uni-Passau.de>

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Package multe updated to version 1.1.0 with previous version 1.0.1 dated 2024-06-19

Title: Multiple Treatment Effects Regression
Description: Implements contamination bias diagnostics and alternative estimators for regressions with multiple treatments. The implementation is based on Goldsmith-Pinkham, Hull, and Kolesár (2024) <doi:10.48550/arXiv.2106.05024>.
Author: Michal Kolesar [aut, cre] , Paul Goldsmith-Pinkham [ctb], Peter Hull [ctb]
Maintainer: Michal Kolesar <kolesarmi@googlemail.com>

Diff between multe versions 1.0.1 dated 2024-06-19 and 1.1.0 dated 2024-07-12

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Package mlr3resampling updated to version 2024.7.7 with previous version 2024.7.3 dated 2024-07-05

Title: Resampling Algorithms for 'mlr3' Framework
Description: A supervised learning algorithm inputs a train set, and outputs a prediction function, which can be used on a test set. If each data point belongs to a group (such as geographic region, year, etc), then how do we know if it is possible to train on one group, and predict accurately on another group? Cross-validation can be used to determine the extent to which this is possible, by first assigning fold IDs from 1 to K to all data (possibly using stratification, usually by group and label). Then we loop over test sets (group/fold combinations), train sets (same group, other groups, all groups), and compute test/prediction accuracy for each combination. Comparing test/prediction accuracy between same and other, we can determine the extent to which it is possible (perfect if same/other have similar test accuracy for each group; other is usually somewhat less accurate than same; other can be just as bad as featureless baseline when the groups have different patterns). For more information, [...truncated...]
Author: Toby Hocking [aut, cre] , Michel Lang [ctb] , Bernd Bischl [ctb] , Jakob Richter [ctb] , Patrick Schratz [ctb] , Giuseppe Casalicchio [ctb] , Stefan Coors [ctb] , Quay Au [ctb] , Martin Binder [ctb], Florian Pfisterer [ctb] , Raphael Sonabend [ctb] , [...truncated...]
Maintainer: Toby Hocking <toby.hocking@r-project.org>

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New package governor with initial version 0.1.2
Package: governor
Title: Speed Limiter to Control Rate of Execution of Loops
Version: 0.1.2
Maintainer: Mike Cheng <mikefc@coolbutuseless.com>
Description: Speed limiter for controlling rate of execution of loops. It can be necessary to limit the rate of execution of a loop or repeated function call e.g. to show or gather data only at particular intervals. This package includes two methods for limiting this execution rate; speed governors and timers. A speed governor will insert pauses during execution to meet a user-specified loop time. Timers are alarm clocks which will indicate whether a certain time has passed. These mechanisms are implemented in 'C' to minimize processing overhead.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/coolbutuseless/governor
BugReports: https://github.com/coolbutuseless/governor/issues
NeedsCompilation: yes
Packaged: 2024-07-11 08:01:15 UTC; mike
Author: Mike Cheng [aut, cre, cph]
Repository: CRAN
Date/Publication: 2024-07-12 15:20:01 UTC

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Package glmnetr updated to version 0.5-2 with previous version 0.5-1 dated 2024-05-12

Title: Nested Cross Validation for the Relaxed Lasso and Other Machine Learning Models
Description: Cross validation informed Relaxed LASSO, Artificial Neural Network (ANN), gradient boosting machine ('xgboost'), Random Forest ('RandomForestSRC'), Oblique Random Forest ('aorsf'), Recursive Partitioning ('RPART') or step wise regression models are fit. Cross validation leave out samples (leading to nested cross validation) or bootstrap out-of-bag samples are used to evaluate and compare performances between these models with results presented in tabular or graphical means. Calibration plots can also be generated, again based upon (outer nested) cross validation or bootstrap leave out (out of bag) samples. For some datasets, for example when the design matrix is not of full rank, 'glmnet' may have very long run times when fitting the relaxed lasso model, from our experience when fitting Cox models on data with many predictors and many patients, making it difficult to get solutions from either glmnet() or cv.glmnet(). This may be remedied by using the 'path=TRUE' option when calling [...truncated...]
Author: Walter K Kremers [aut, cre] , Nicholas B Larson [ctb]
Maintainer: Walter K Kremers <kremers.walter@mayo.edu>

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New package WES with initial version 1.0.0
Package: WES
Title: Tools for Analyzing Wastewater and Environmental Sampling Data
Version: 1.0.0
Date: 2024-07-03
Description: Provides reproducible functions for collating and analyzing data from environmental sampling studies. Environmental Sampling (ES) of infectious diseases involves collecting samples from various sources (such as sewage, water, air, soil, or surfaces) to monitor the presence of pathogens in the environment. Analysis of ES data often requires the calculation of Real-Time Quantitative PCR (qPCR) variables, normalizing ES observations, and analyzing sampling site characteristics. To help reduce the complexity of these analyses we have implemented tools that assist with establishing standardized ES data formats, absolute and relative quantification of qPCR data, estimation of qPCR amplification efficiency, and collating open-source spatial data for sampling sites.
URL: https://www.r-wes.com/
License: CC BY 4.0
Encoding: UTF-8
LazyData: true
Imports: glue, foreach, data.table, dplyr, HDInterval, zoo, openmeteo, chirps, whitebox, exactextractr, elevatr, raster, sp, sf, rworldmap, stars, RCurl, XML, httr, jsonlite
Depends: R (>= 4.1.1), stats, graphics, grDevices, utils
Suggests: rmarkdown, rworldxtra, progress
NeedsCompilation: no
Packaged: 2024-07-11 02:31:38 UTC; johngiles
Author: John R Giles [aut, cre]
Maintainer: John R Giles <john.giles@gatesfoundation.org>
Repository: CRAN
Date/Publication: 2024-07-12 14:00:06 UTC

More information about WES at CRAN
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New package tidygate with initial version 1.0.13
Package: tidygate
Title: Interactively Gate Points
Version: 1.0.13
Maintainer: Stefano Mangiola <mangiolastefano@gmail.com>
Description: Interactively gate points on a scatter plot. Interactively drawn gates are recorded and can be applied programmatically to reproduce results exactly. Programmatic gating is based on the package gatepoints by Wajid Jawaid (who is also an author of this package).
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.6.0)
Imports: utils, graphics, lifecycle, scales, magrittr, tibble, dplyr, purrr, rlang, tidyr, viridis, grDevices, RColorBrewer, stringr, shiny, plotly, ggplot2
Suggests: testthat, markdown, knitr, readr
VignetteBuilder: knitr
Biarch: true
URL: https://github.com/stemangiola/tidygate
BugReports: https://github.com/stemangiola/tidygate/issues
NeedsCompilation: no
Packaged: 2024-07-11 00:17:21 UTC; mangiola.s
Author: Stefano Mangiola [aut, cre], Wajid Jawaid [ctb], William Hutchison [aut]
Repository: CRAN
Date/Publication: 2024-07-12 13:30:01 UTC

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Package simpleboot updated to version 1.1-8 with previous version 1.1-7 dated 2019-02-20

Title: Simple Bootstrap Routines
Description: Simple bootstrap routines.
Author: Roger D. Peng <roger.peng@austin.utexas.edu>
Maintainer: Roger D. Peng <roger.peng@austin.utexas.edu>

Diff between simpleboot versions 1.1-7 dated 2019-02-20 and 1.1-8 dated 2024-07-12

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New package sdtmchecks with initial version 1.0.0
Package: sdtmchecks
Title: Data Quality Checks for Study Data Tabulation Model (SDTM) Datasets
Version: 1.0.0
Description: A series of checks to identify common issues in Study Data Tabulation Model (SDTM) datasets. These checks are intended to be generalizable, actionable, and meaningful for analysis.
License: Apache License (>= 2)
Encoding: UTF-8
Language: en-US
LazyData: true
Imports: dplyr (>= 1.1.1), tidyselect, openxlsx
Suggests: knitr, rmarkdown (>= 2.7), testthat, DT
VignetteBuilder: knitr
URL: https://pharmaverse.github.io/sdtmchecks/, https://github.com/pharmaverse/sdtmchecks
BugReports: https://github.com/pharmaverse/sdtmchecks/issues
Repository: CRAN
NeedsCompilation: no
Packaged: 2024-07-11 01:33:03 UTC; harric17
Author: Will Harris [aut, cre], Sara Bodach [aut], Edgar Manukyan [aut], Adrian Waddell [aut], Ross Farrugia [aut], F. Hoffmann-La Roche AG [cph, fnd]
Maintainer: Will Harris <harric17@gene.com>
Date/Publication: 2024-07-12 13:50:02 UTC

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Package RCzechia updated to version 1.12.2 with previous version 1.12.0 dated 2023-10-29

Title: Spatial Objects of the Czech Republic
Description: Administrative regions and other spatial objects of the Czech Republic.
Author: Jindra Lacko [aut, cre] , Nick Bearman [rev]
Maintainer: Jindra Lacko <jindra.lacko@gmail.com>

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Package bamdit updated to version 3.4.1 with previous version 3.4.0 dated 2022-04-04

Title: Bayesian Meta-Analysis of Diagnostic Test Data
Description: Provides a new class of Bayesian meta-analysis models that incorporates a model for internal and external validity bias. In this way, it is possible to combine studies of diverse quality and different types. For example, we can combine the results of randomized control trials (RCTs) with the results of observational studies (OS).
Author: Pablo Emilio Verde [aut, cre]
Maintainer: Pablo Emilio Verde <pabloemilio.verde@hhu.de>

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Package adestr updated to version 1.0.0 with previous version 0.5.0 dated 2023-09-27

Title: Estimation in Optimal Adaptive Two-Stage Designs
Description: Methods to evaluate the performance characteristics of various point and interval estimators for optimal adaptive two-stage designs as described in Meis et al. (2024) <doi:10.1002/sim.10020>. Specifically, this package is written to work with trial designs created by the 'adoptr' package (Kunzmann et al. (2021) <doi:10.18637/jss.v098.i09>; Pilz et al. (2021) <doi:10.1002/sim.8953>)). Apart from the a priori evaluation of performance characteristics, this package also allows for the evaluation of the implemented estimators on real datasets, and it implements methods to calculate p-values.
Author: Jan Meis [aut, cre] , Martin Maechler [cph] .)
Maintainer: Jan Meis <meis@imbi.uni-heidelberg.de>

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Package ura updated to version 1.0.1 with previous version 1.0.0 dated 2023-09-13

Title: Monitoring Rater Reliability
Description: Provides researchers with a simple set of diagnostic tools for monitoring the progress and reliability of raters conducting content coding tasks. Goehring (2024) <https://bengoehring.github.io/improving-content-analysis-tools-for-working-with-undergraduate-research-assistants.pdf> argues that supervisors---especially supervisors of small teams---should utilize computational tools to monitor reliability in real time. As such, this package provides easy-to-use functions for calculating inter-rater reliability statistics and measuring the reliability of one coder compared to the rest of the team.
Author: Benjamin Goehring [aut, cre]
Maintainer: Benjamin Goehring <bengoehr@umich.edu>

Diff between ura versions 1.0.0 dated 2023-09-13 and 1.0.1 dated 2024-07-12

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Package stgam updated to version 0.0.1.1 with previous version 0.0.1.0 dated 2024-06-25

Title: Spatially and Temporally Varying Coefficient Models Using Generalized Additive Models
Description: A framework for specifying spatially, temporally and spatial-and-temporally varying coefficient models using Generalized Additive Models with Gaussian Process smooths. The smooths are parameterised with location and / or time attributes. Importantly the framework supports the investigation of the presence and nature of any space-time dependencies in the data, allows the user to evaluate different model forms (specifications) and to pick the most probable model or to combine multiple varying coefficient models using Bayesian Model Averaging. For more details see: Brunsdon et al (2023) <doi:10.4230/LIPIcs.GIScience.2023.17>, Comber et al (2023) <doi:10.4230/LIPIcs.GIScience.2023.22> and Comber et al (2024) <doi:10.1080/13658816.2023.2270285>.
Author: Lex Comber [aut, cre], Paul Harris [ctb], Chris Brunsdon [ctb]
Maintainer: Lex Comber <a.comber@leeds.ac.uk>

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Package hstats updated to version 1.2.0 with previous version 1.1.2 dated 2024-02-03

Title: Interaction Statistics
Description: Fast, model-agnostic implementation of different H-statistics introduced by Jerome H. Friedman and Bogdan E. Popescu (2008) <doi:10.1214/07-AOAS148>. These statistics quantify interaction strength per feature, feature pair, and feature triple. The package supports multi-output predictions and can account for case weights. In addition, several variants of the original statistics are provided. The shape of the interactions can be explored through partial dependence plots or individual conditional expectation plots. 'DALEX' explainers, meta learners ('mlr3', 'tidymodels', 'caret') and most other models work out-of-the-box.
Author: Michael Mayer [aut, cre] , Przemyslaw Biecek [ctb]
Maintainer: Michael Mayer <mayermichael79@gmail.com>

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Package fitdistrplus updated to version 1.2-1 with previous version 1.1-11 dated 2023-04-25

Title: Help to Fit of a Parametric Distribution to Non-Censored or Censored Data
Description: Extends the fitdistr() function (of the MASS package) with several functions to help the fit of a parametric distribution to non-censored or censored data. Censored data may contain left censored, right censored and interval censored values, with several lower and upper bounds. In addition to maximum likelihood estimation (MLE), the package provides moment matching (MME), quantile matching (QME), maximum goodness-of-fit estimation (MGE) and maximum spacing estimation (MSE) methods (available only for non-censored data). Weighted versions of MLE, MME, QME and MSE are available. See e.g. Casella & Berger (2002), Statistical inference, Pacific Grove, for a general introduction to parametric estimation.
Author: Marie-Laure Delignette-Muller [aut] , Christophe Dutang [aut] , Regis Pouillot [ctb], Jean-Baptiste Denis [ctb], Aurelie Siberchicot [aut, cre]
Maintainer: Aurelie Siberchicot <aurelie.siberchicot@univ-lyon1.fr>

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New package sampcompR with initial version 0.2.0
Package: sampcompR
Title: Comparing and Visualizing Differences Between Surveys
Version: 0.2.0
Description: Easily analyze and visualize differences between samples (e.g., benchmark comparisons, nonresponse comparisons in surveys) on three levels. The comparisons can be univariate, bivariate or multivariate. On univariate level the variables of interest of a survey and a comparison survey (i.e. benchmark) are compared, by calculating one of several difference measures (e.g., relative difference in mean), and an average difference between the surveys. On bivariate level a function can calculate significant differences in correlations for the surveys. And on multivariate levels a function can calculate significant differences in model coefficients between the surveys of comparison. All of those differences can be easily plotted and outputted as a table. For more detailed information on the methods and example use see Rohr, B., Silber, H., & Felderer, B. (2024). „Comparing the Accuracy of Univariate, Bivariate, and Multivariate Estimates across Probability and Non-Probability Surveys with [...truncated...]
License: GPL-3
Encoding: UTF-8
Imports: boot, boot.pval, data.table, dplyr, forcats, furrr, future, ggplot2, Hmisc, lmtest, magrittr, psych, purrr, readr, reshape2, sandwich, stats, survey, svrep, tibble, tidyr,
Suggests: testthat (>= 3.0.0), wooldridge, jtools, utils, parallel
NeedsCompilation: no
Packaged: 2024-07-10 08:27:27 UTC; rohrbn
Author: Bjoern Rohr [aut, cre, cph]
Maintainer: Bjoern Rohr <bjoern.rohr@gesis.org>
Repository: CRAN
Date/Publication: 2024-07-12 11:20:03 UTC

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New package mergenstudio with initial version 1.0
Package: mergenstudio
Title: 'Mergen' Studio: An 'RStudio' Addin Wrapper for the 'Mergen' Package
Version: 1.0
Maintainer: Jacqueline Jansen <jacqueline-98@hotmail.com>
Description: An 'RStudio' Addin wrapper for the 'mergen' package. This package employs artificial intelligence to convert data analysis questions into executable code, explanations, and algorithms. This package makes it easier to use Large Language Models in your development environment by providing a chat-like interface, while also allowing you to inspect and execute the returned code.
License: MIT + file LICENSE
Depends: R (>= 4.0)
Imports: mergen, assertthat, bslib (>= 0.4.2), cli, colorspace, fontawesome, glue, grDevices, htmltools, htmlwidgets, httr2, ids, jsonlite, magrittr, purrr, rlang, rstudioapi (>= 0.12), shiny, shiny.i18n, shinyjs, shinyFiles, fs, stringr (>= 1.5.0), rvest, utils, waiter, yaml, rmarkdown, methods
Encoding: UTF-8
Language: en-US
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2024-07-10 11:35:56 UTC; jacquelinejansen
Author: Jacqueline Jansen [aut, cre], Artuer Manukyan [aut], Nour Alkhoury [aut], Altuna Akalin [aut]
Repository: CRAN
Date/Publication: 2024-07-12 11:30:02 UTC

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New package drglm with initial version 1.0
Package: drglm
Title: Fitting Linear and Generalized Linear Models in "Divide and Recombine" Approach to Large Data Sets
Version: 1.0
Maintainer: Md. Mahadi Hassan Nayem <mhnayem.cu.stat@outlook.com>
Depends: R (>= 3.5.0)
Imports: nnet, speedglm, stats
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
Description: To overcome the memory limitations for fitting linear (LM) and Generalized Linear Models (GLMs) to large data sets, this package implements the Divide and Recombine (D&R) strategy. It basically divides the entire large data set into suitable subsets manageable in size and then fits model to each subset. Finally, results from each subset are aggregated to obtain the final estimate. This package also supports fitting GLMs to data sets that cannot fit into memory and provides methods for fitting GLMs under linear regression, binomial regression, Poisson regression, and multinomial logistic regression settings. Respective models are fitted using different D&R strategies as described by: Xi, Lin, and Chen (2009) <doi:10.1109/TKDE.2008.186>, Xi, Lin and Chen (2006) <doi:10.1109/TKDE.2006.196>, Zuo and Li (2018) <doi:10.4236/ojs.2018.81003>, Karim, M.R., Islam, M.A. (2019) <doi:10.1007/978-981-13-9776-9>.
License: GPL (>= 3)
Encoding: UTF-8
VignetteBuilder: knitr
URL: https://nayemmh.github.io/drglm/
NeedsCompilation: no
Packaged: 2024-07-10 14:27:38 UTC; mhnay
Author: Md. Mahadi Hassan Nayem [aut, cre]
Repository: CRAN
Date/Publication: 2024-07-12 11:40:02 UTC

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New package docket with initial version 1.33
Package: docket
Title: Insert R Data into 'Word' Documents
Version: 1.33
Description: Populate data from an R environment into '.doc' and '.docx' templates. Create a template document in a program such as 'Word', and add strings encased in guillemet characters to create flags («example»). Use getDictionary() to create a dictionary of flags and replacement values, then call docket() to generate a populated document.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: stringr, XML, xml2, zip
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/JonathanConrad98/docket
BugReports: https://github.com/JonathanConrad98/docket/issues
NeedsCompilation: no
Packaged: 2024-07-10 20:48:35 UTC; Jonra
Author: Jonathan Conrad [aut, cre], Ian Conrad [ctb]
Maintainer: Jonathan Conrad <JonathanGConrad@gmail.com>
Repository: CRAN
Date/Publication: 2024-07-12 11:50:02 UTC

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New package CPoptim with initial version 0.1.0
Package: CPoptim
Title: Convex Partition Optimisation
Version: 0.1.0
Author: Erick G.G. de Paz [aut, cre] , Humberto Vaquera Huerta [aut] , Francisco Javier Albores Velasco [aut] , John R. Bauer Mengelberg [aut] , Juan Manuel Romero Padilla [aut]
Maintainer: Erick G.G. de Paz <giles.erick@colpos.mx>
Description: Convex Partition is a black-box optimisation algorithm for single objective real-parameters functions. The basic principle is to progressively estimate and exploit a regression tree similar to a CART (Classification and Regression Tree) of the objective function. For more details see 'de Paz' (2024) <doi:10.1007/978-3-031-62836-8_3> and 'Loh' (2011) <doi:10.1002/widm.8> .
License: GPL-2
Encoding: UTF-8
NeedsCompilation: yes
Repository: CRAN
Date: 2024-07-07
Depends: R (>= 2.10.0)
Packaged: 2024-07-10 00:04:28 UTC; erickdepaz
Date/Publication: 2024-07-12 11:10:02 UTC

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Package duckplyr updated to version 0.4.1 with previous version 0.4.0 dated 2024-05-21

Title: A 'DuckDB'-Backed Version of 'dplyr'
Description: A drop-in replacement for 'dplyr', powered by 'DuckDB' for performance. Also defines a set of generics that provide a low-level implementer's interface for the high-level user interface of 'dplyr'.
Author: Hannes Muehleisen [aut] , Kirill Mueller [aut, cre] , Posit Software, PBC [cph, fnd]
Maintainer: Kirill Mueller <kirill@cynkra.com>

Diff between duckplyr versions 0.4.0 dated 2024-05-21 and 0.4.1 dated 2024-07-12

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Package deseats updated to version 1.1.0 with previous version 1.0.0 dated 2023-11-08

Title: Data-Driven Locally Weighted Regression for Trend and Seasonality in TS
Description: Various methods for the identification of trend and seasonal components in time series (TS) are provided. Among them is a data-driven locally weighted regression approach with automatically selected bandwidth for equidistant short-memory time series. The approach is a combination / extension of the algorithms by Feng (2013) <doi:10.1080/02664763.2012.740626> and Feng, Y., Gries, T., and Fritz, M. (2020) <doi:10.1080/10485252.2020.1759598> and a brief description of this new method is provided in the package documentation. Furthermore, the package allows its users to apply the base model of the Berlin procedure, version 4.1, as described in Speth (2004) <https://www.destatis.de/DE/Methoden/Saisonbereinigung/BV41-methodenbericht-Heft3_2004.pdf?__blob=publicationFile>. Permission to include this procedure was kindly provided by the Federal Statistical Office of Germany.
Author: Yuanhua Feng [aut] , Dominik Schulz [aut, cre]
Maintainer: Dominik Schulz <dominik.schulz@uni-paderborn.de>

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Package WeibullR.shiny updated to version 0.2.1 with previous version 0.2.0 dated 2023-10-18

Title: A 'Shiny' App for Weibull Analysis from 'WeibullR'
Description: A 'Shiny' web application for life data analysis that depends on 'WeibullR' by David Silkworth and Jurgen Symynck (2022) <https://CRAN.R-project.org/package=WeibullR>, an R package for Weibull analysis.
Author: Paul Govan [aut, cre, cph]
Maintainer: Paul Govan <paul.govan2@gmail.com>

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Package CodelistGenerator updated to version 3.1.0 with previous version 3.0 dated 2024-05-31

Title: Identify Relevant Clinical Codes and Evaluate Their Use
Description: Generate a candidate code list for the Observational Medical Outcomes Partnership (OMOP) common data model based on string matching. For a given search strategy, a candidate code list will be returned.
Author: Edward Burn [aut, cre] , Marti Catala [ctb] , Xihang Chen [ctb] , Mike Du [ctb] , Danielle Newby [ctb]
Maintainer: Edward Burn <edward.burn@ndorms.ox.ac.uk>

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Package BayesianNetwork updated to version 0.3.2 with previous version 0.3 dated 2023-06-26

Title: Bayesian Network Modeling and Analysis
Description: A "Shiny"" web application for creating interactive Bayesian Network models, learning the structure and parameters of Bayesian networks, and utilities for classic network analysis.
Author: Paul Govan [aut, cre, cph]
Maintainer: Paul Govan <paul.govan2@gmail.com>

Diff between BayesianNetwork versions 0.3 dated 2023-06-26 and 0.3.2 dated 2024-07-12

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