Mon, 11 Oct 2021

Package tangram.pipe updated to version 1.1.0 with previous version 1.0.0 dated 2021-07-05

Title: Row-by-Row Table Building
Description: Builds tables with customizable rows. Users can specify the type of data to use for each row, as well as how to handle missing data and the types of comparison tests to run on the table columns.
Author: Andrew Guide [aut, cre], Thomas Stewart [aut]
Maintainer: Andrew Guide <andrew.guide@vumc.org>

Diff between tangram.pipe versions 1.0.0 dated 2021-07-05 and 1.1.0 dated 2021-10-11

 DESCRIPTION                                          |    6 
 MD5                                                  |   72 
 NAMESPACE                                            |    8 
 R/binary_default.R                                   |  129 -
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 R/cat_row.R                                          |   35 
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 R/num_medianiqr.R                                    |only
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 R/num_row.R                                          |   35 
 R/print.tangram.pipe.R                               |   12 
 R/tangram_styling.R                                  |   15 
 R/tbl_out.R                                          |   26 
 R/tbl_start.R                                        |   28 
 build/vignette.rds                                   |binary
 inst/doc/Customizable-Table-Building.R               |  258 +--
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 man/tbl_start.Rd                                     |   21 
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 vignettes/Writing-User-Defined-Summary-Functions.Rmd |only
 47 files changed, 1897 insertions(+), 1565 deletions(-)

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Package patrick updated to version 0.1.0 with previous version 0.0.4 dated 2021-09-23

Title: Parameterized Unit Testing
Description: This is an extension of the 'testthat' package that lets you add parameters to your unit tests. Parameterized unit tests are often easier to read and more reliable, since they follow the DNRY (do not repeat yourself) rule.
Author: Michael Quinn [aut, cre]
Maintainer: Michael Quinn <msquinn@google.com>

Diff between patrick versions 0.0.4 dated 2021-09-23 and 0.1.0 dated 2021-10-11

 DESCRIPTION                           |    6 ++--
 MD5                                   |   16 +++++------
 NAMESPACE                             |    1 
 NEWS.md                               |    9 ++++++
 R/with_parameters.R                   |   46 ++++++++++++++++++++++++++--------
 README.md                             |    8 ++---
 man/patrick-package.Rd                |   13 +++++----
 man/with_parameters_test_that.Rd      |   21 +++++++++------
 tests/testthat/test-with_parameters.R |   37 ++++++++++++++++++++++++---
 9 files changed, 114 insertions(+), 43 deletions(-)

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Package dismo updated to version 1.3-5 with previous version 1.3-3 dated 2020-11-17

Title: Species Distribution Modeling
Description: Methods for species distribution modeling, that is, predicting the environmental similarity of any site to that of the locations of known occurrences of a species.
Author: Robert J. Hijmans, Steven Phillips, John Leathwick and Jane Elith
Maintainer: Robert J. Hijmans <r.hijmans@gmail.com>

Diff between dismo versions 1.3-3 dated 2020-11-17 and 1.3-5 dated 2021-10-11

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 dismo-1.3-5/dismo/R/bioclim.predict.R         |    2 
 dismo-1.3-5/dismo/R/biogeomancer.R            |    2 
 dismo-1.3-5/dismo/R/circleHull.predict.R      |    2 
 dismo-1.3-5/dismo/R/circles.predict.R         |    2 
 dismo-1.3-5/dismo/R/convHull.R                |   22 +++++-----
 dismo-1.3-5/dismo/R/ecocrop.R                 |    2 
 dismo-1.3-5/dismo/R/evaluate.R                |    2 
 dismo-1.3-5/dismo/R/gbif_old.R                |    6 +-
 dismo-1.3-5/dismo/R/maxent.R                  |    4 -
 dismo-1.3-5/dismo/R/maxent.predict.R          |   16 +++----
 dismo-1.3-5/dismo/R/randomPoints.R            |    9 ++--
 dismo-1.3-5/dismo/R/voronoi.R                 |   23 ++++++----
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 34 files changed, 99 insertions(+), 93 deletions(-)

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Package test2norm updated to version 0.2.0 with previous version 0.1.1 dated 2019-10-16

Title: Normative Standards for Cognitive Tests
Description: Package test2norm contains functions to generate formulas for normative standards applied to cognitive tests. It takes raw test scores (e.g., number of correct responses) and converts them to scaled scores and demographically adjusted scores, using methods described in Heaton et al. (2003) <doi:10.1016/B978-012703570-3/50010-9> & Heaton et al. (2009, ISBN:9780199702800). The scaled scores are calculated as quantiles of the raw test scores, scaled to have the mean of 10 and standard deviation of 3, such that higher values always correspond to better performance on the test. The demographically adjusted scores are calculated from the residuals of a model that regresses scaled scores on demographic predictors (e.g., age). The norming procedure makes use of the mfp() function from the 'mfp' package to explore nonlinear associations between cognition and demographic variables.
Author: Anya Umlauf
Maintainer: Anya Umlauf <aumlauf@health.ucsd.edu>

Diff between test2norm versions 0.1.1 dated 2019-10-16 and 0.2.0 dated 2021-10-11

 DESCRIPTION          |   20 ++++++++++----------
 MD5                  |   17 +++++++++++------
 NAMESPACE            |    2 ++
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 12 files changed, 45 insertions(+), 27 deletions(-)

More information about test2norm at CRAN
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Package RawHummus updated to version 0.2.0 with previous version 0.1.8 dated 2021-09-22

Title: Raw Data Quality Control Tool for LC-MS System
Description: Assess LC–MS system performance by visualizing instrument log files and monitoring raw quality control samples within a project.
Author: Yonghui Dong
Maintainer: Yonghui Dong <yonghui.dong@gmail.com>

Diff between RawHummus versions 0.1.8 dated 2021-09-22 and 0.2.0 dated 2021-10-11

 DESCRIPTION               |    6 
 MD5                       |    6 
 inst/shiny/Gui/Report.Rmd | 1186 +++++++++++++++++++++++-----------------------
 inst/shiny/Gui/server.R   |   52 +-
 4 files changed, 625 insertions(+), 625 deletions(-)

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Package raster updated to version 3.5-2 with previous version 3.4-13 dated 2021-06-18

Title: Geographic Data Analysis and Modeling
Description: Reading, writing, manipulating, analyzing and modeling of spatial data. The package implements basic and high-level functions for raster data and for vector data operations such as intersections. See the manual and tutorials on <https://rspatial.org/> to get started.
Author: Robert J. Hijmans [cre, aut] (<https://orcid.org/0000-0001-5872-2872>), Jacob van Etten [ctb], Michael Sumner [ctb], Joe Cheng [ctb], Dan Baston [ctb], Andrew Bevan [ctb], Roger Bivand [ctb], Lorenzo Busetto [ctb], Mort Canty [ctb], Ben Fasoli [ctb], David Forrest [ctb], Aniruddha Ghosh [ctb], Duncan Golicher [ctb], Josh Gray [ctb], Jonathan A. Greenberg [ctb], Paul Hiemstra [ctb], Kassel Hingee [ctb], Institute for Mathematics Applied Geosciences [cph], Charles Karney [ctb], Matteo Mattiuzzi [ctb], Steven Mosher [ctb], Babak Naimi [ctb], Jakub Nowosad [ctb], Edzer Pebesma [ctb], Oscar Perpinan Lamigueiro [ctb], Etienne B. Racine [ctb], Barry Rowlingson [ctb], Ashton Shortridge [ctb], Bill Venables [ctb], Rafael Wueest [ctb]
Maintainer: Robert J. Hijmans <r.hijmans@gmail.com>

Diff between raster versions 3.4-13 dated 2021-06-18 and 3.5-2 dated 2021-10-11

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 raster-3.5-2/raster/R/animate.R             |    2 
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 raster-3.5-2/raster/R/rasterToPoints.R      |    6 
 raster-3.5-2/raster/R/rasterToPolygons.R    |    6 
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 raster-3.5-2/raster/R/rasterizePolygons.R   |   37 ++--
 raster-3.5-2/raster/R/rotate.R              |    2 
 raster-3.5-2/raster/R/sampleRandom.R        |    2 
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 107 files changed, 596 insertions(+), 518 deletions(-)

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New package processanimateR with initial version 1.0.4
Package: processanimateR
Title: Process Map Token Replay Animation
Version: 1.0.4
Description: Provides animated process maps based on the 'procesmapR' package. Cases stored in event logs created with with 'bupaR' S3 class eventlog() are rendered as tokens (SVG shapes) and animated according to their occurrence times on top of the process map. For rendering SVG animations ('SMIL') and the 'htmlwidget' package are used.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
Imports: bupaR, processmapR (>= 0.3.1), rlang, magrittr, dplyr, tidyr, htmlwidgets, DiagrammeR (>= 1.0.0), grDevices, stringr, htmltools
Suggests: eventdataR, edeaR, testthat, knitr, rmarkdown, shiny, RColorBrewer, lubridate
URL: https://github.com/bupaverse/processanimateR/
BugReports: https://github.com/bupaverse/processanimateR/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-10-11 15:35:50 UTC; fmannhar
Author: Felix Mannhardt [aut, cre], Gert Janssenswillen [ctb]
Maintainer: Felix Mannhardt <f.mannhardt@tue.nl>
Repository: CRAN
Date/Publication: 2021-10-11 18:50:02 UTC

More information about processanimateR at CRAN
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New package heuristicsmineR with initial version 0.2.5
Package: heuristicsmineR
Title: Discovery of Process Models with the Heuristics Miner
Version: 0.2.5
Description: Provides the heuristics miner algorithm for process discovery as proposed by Weijters et al. (2011) <doi:10.1109/CIDM.2011.5949453>. The algorithm builds a causal net from an event log created with the 'bupaR' package. Event logs are a set of ordered sequences of events for which 'bupaR' provides the S3 class eventlog(). The discovered causal nets can be visualised as 'htmlwidgets' and it is possible to annotate them with the occurrence frequency or processing and waiting time of process activities.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp, BH
SystemRequirements: C++11
Depends: R (>= 2.10)
Imports: bupaR, processmapR (>= 0.3.1), rlang, magrittr, dplyr, tidyr, DiagrammeR (>= 1.0.0), petrinetR, purrr, scales, Rcpp, ggplot2, ggthemes, data.table, stringr
Suggests: eventdataR, svgPanZoom, DiagrammeRsvg
URL: https://github.com/bupaverse/heuristicsmineR
BugReports: https://github.com/bupaverse/heuristicsmineR/issues
NeedsCompilation: yes
Packaged: 2021-10-11 14:18:35 UTC; fmannhar
Author: Felix Mannhardt [aut, cre]
Maintainer: Felix Mannhardt <f.mannhardt@tue.nl>
Repository: CRAN
Date/Publication: 2021-10-11 18:50:05 UTC

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New package datapackage.r with initial version 1.3.4
Package: datapackage.r
Title: Data Package 'Frictionless Data'
Version: 1.3.4
Date: 2021-10-11
Maintainer: Kleanthis Koupidis <koupidis.okfgr@gmail.com>
Description: Work with 'Frictionless Data Packages' (<https://specs.frictionlessdata.io//data-package/>). Allows to load and validate any descriptor for a data package profile, create and modify descriptors and provides expose methods for reading and streaming data in the package. When a descriptor is a 'Tabular Data Package', it uses the 'Table Schema' package (<https://CRAN.R-project.org/package=tableschema.r>) and exposes its functionality, for each resource object in the resources field.
URL: https://github.com/frictionlessdata/datapackage-r
License: MIT + file LICENSE
BugReports: https://github.com/frictionlessdata/datapackage-r/issues
Encoding: UTF-8
Imports: config, future, httr, iterators, jsonlite, jsonvalidate, purrr, R6, R.utils, readr, rlist, stringr, tableschema.r, tools, urltools, utils, V8
Suggests: covr, curl, data.table, DBI, devtools, foreach, httptest, knitr, rmarkdown, RSQLite, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-10-11 15:19:18 UTC; akis_
Author: Kleanthis Koupidis [aut, cre], Lazaros Ioannidis [aut], Charalampos Bratsas [aut], Open Knowledge International [cph]
Repository: CRAN
Date/Publication: 2021-10-11 18:50:08 UTC

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Package cholera updated to version 0.7.9 with previous version 0.7.5 dated 2021-04-21

Title: Amend, Augment and Aid Analysis of John Snow's Cholera Map
Description: Amends errors, augments data and aids analysis of John Snow's map of the 1854 London cholera outbreak.
Author: Peter Li [aut, cre]
Maintainer: Peter Li <lindbrook@gmail.com>

Diff between cholera versions 0.7.5 dated 2021-04-21 and 0.7.9 dated 2021-10-11

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Package broman updated to version 0.76 with previous version 0.72-4 dated 2021-02-05

Title: Karl Broman's R Code
Description: Miscellaneous R functions, including functions related to graphics (mostly for base graphics), permutation tests, running mean/median, and general utilities.
Author: Karl W Broman [aut, cre] (<https://orcid.org/0000-0002-4914-6671>), Aimee Teo Broman [ctb] (<https://orcid.org/0000-0003-3783-2807>)
Maintainer: Karl W Broman <broman@wisc.edu>

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Package svMisc updated to version 1.2.3 with previous version 1.1.4 dated 2021-04-16

Title: 'SciViews' - Miscellaneous Functions
Description: Miscellaneous functions for 'SciViews' or general use: manage a temporary environment attached to the search path for temporary variables you do not want to save() or load(), test if 'Aqua', 'Mac', 'Win', ... Show progress bar, etc.
Author: Philippe Grosjean [aut, cre] (<https://orcid.org/0000-0002-2694-9471>), Romain Francois [ctb], Kamil Barton [ctb]
Maintainer: Philippe Grosjean <phgrosjean@sciviews.org>

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Package discoveR updated to version 2.2.6 with previous version 2.2.2 dated 2021-03-12

Title: Exploratory Data Analysis System
Description: Performs an exploratory data analysis through a 'shiny' interface. It includes basic methods such as the mean, median, mode, normality test, among others. It also includes clustering techniques such as Principal Components Analysis, Hierarchical Clustering and the K-Means Method.
Author: Oldemar Rodriguez [aut, cre], Diego Jiménez [ctb, prg]
Maintainer: Oldemar Rodriguez <oldemar.rodriguez@ucr.ac.cr>

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Package bhmbasket updated to version 0.9.3 with previous version 0.9.2 dated 2021-04-07

Title: Bayesian Hierarchical Models for Basket Trials
Description: Provides functions for the evaluation of basket trial designs with binary endpoints. Operating characteristics of a basket trial design are assessed by simulating trial data according to scenarios, analyzing the data with Bayesian hierarchical models (BHMs), and assessing decision probabilities on stratum and trial-level based on Go / No-go decision making. The package is build for high flexibility regarding decision rules, number of interim analyses, number of strata, and recruitment. The BHMs proposed by Berry et al. (2013) <doi:10.1177/1740774513497539> and Neuenschwander et al. (2016) <doi:10.1002/pst.1730>, as well as a model that combines both approaches are implemented. Functions are provided to implement Bayesian decision rules as for example proposed by Fisch et al. (2015) <doi:10.1177/2168479014533970>. In addition, posterior point estimates (mean/median) and credible intervals for response rates and some model parameters can be calculated. For simulated trial data, bias and mean squared errors of posterior point estimates for response rates can be provided.
Author: Stephan Wojciekowski [aut, cre]
Maintainer: Stephan Wojciekowski <stephan.wojciekowski@boehringer-ingelheim.com>

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Package tabnet updated to version 0.3.0 with previous version 0.2.0 dated 2021-06-22

Title: Fit 'TabNet' Models for Classification and Regression
Description: Implements the 'TabNet' model by Sercan O. Arik et al (2019) <arXiv:1908.07442> and provides a consistent interface for fitting and creating predictions. It's also fully compatible with the 'tidymodels' ecosystem.
Author: Daniel Falbel [aut, cre], RStudio [cph], Christophe Regouby [ctb]
Maintainer: Daniel Falbel <daniel@rstudio.com>

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Package PxWebApiData updated to version 0.7.0 with previous version 0.6.0 dated 2021-07-18

Title: PX-Web Data by API
Description: Function to read PX-Web data into R via API. The example code reads data from the three national statistical institutes, Statistics Norway, Statistics Sweden and Statistics Finland.
Author: Øyvind Langsrud [aut, cre], Jan Bruusgaard [aut], Solveig Bjørkholt [ctb], Susie Jentoft [ctb]
Maintainer: Øyvind Langsrud <oyl@ssb.no>

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Package dynamichazard updated to version 1.0.1 with previous version 1.0.0 dated 2021-09-07

Title: Dynamic Hazard Models using State Space Models
Description: Contains functions that lets you fit dynamic hazard models using state space models. The first implemented model is described in Fahrmeir (1992) <doi:10.1080/01621459.1992.10475232> and Fahrmeir (1994) <doi:10.1093/biomet/81.2.317>. Extensions hereof are available where the Extended Kalman filter is replaced by an unscented Kalman filter. See Christoffersen (2021) <doi:10.18637/jss.v099.i07> for more details. Particle filters and smoothers are also supported more general state space models.
Author: Benjamin Christoffersen [cre, aut] (<https://orcid.org/0000-0002-7182-1346>), Alan Miller [cph], Anthony Williams [cph], Boost developers [cph], R-core [cph]
Maintainer: Benjamin Christoffersen <boennecd@gmail.com>

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Package CCWeights updated to version 0.1.5 with previous version 0.1.3 dated 2021-06-11

Title: Perform Weighted Linear Regression for Calibration Curve
Description: Automated assessment and selection of weighting factors for accurate quantification using linear calibration curve. In addition, a 'shiny' App is provided, allowing users to analyze their data using an interactive graphical user interface, without any programming requirements.
Author: Yonghui Dong
Maintainer: Yonghui Dong <yonghui.dong@gmail.com>

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Package ChemoSpec updated to version 6.0.1 with previous version 5.3.21 dated 2021-07-06

Title: Exploratory Chemometrics for Spectroscopy
Description: A collection of functions for top-down exploratory data analysis of spectral data including nuclear magnetic resonance (NMR), infrared (IR), Raman, X-ray fluorescence (XRF) and other similar types of spectroscopy. Includes functions for plotting and inspecting spectra, peak alignment, hierarchical cluster analysis (HCA), principal components analysis (PCA) and model-based clustering. Robust methods appropriate for this type of high-dimensional data are available. ChemoSpec is designed for structured experiments, such as metabolomics investigations, where the samples fall into treatment and control groups. Graphical output is formatted consistently for publication quality plots. ChemoSpec is intended to be very user friendly and to help you get usable results quickly. A vignette covering typical operations is available.
Author: Bryan A. Hanson [aut, cre] (<https://orcid.org/0000-0003-3536-8246>), Mike Bostock [cph, ctb] (author of the d3.js library used by plotSpectraJS, http://d3js.org), Matt Keinsley [ctb] (author of initial AOV-PCA code), Tejasvi Gupta [ctb] (author of ggplot2 and plotly graphics)
Maintainer: Bryan A. Hanson <hanson@depauw.edu>

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Package factset.protobuf.stach.v2 (with last version 1.0.0) was removed from CRAN

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

2021-10-11 1.0.0

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Package GeneBook (with last version 1.0) was removed from CRAN

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

2019-08-01 1.0

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Package varTestnlme updated to version 1.1.0 with previous version 1.0.0 dated 2021-01-07

Title: Variance Components Testing for Linear and Nonlinear Mixed Effects Models
Description: An implementation of the Likelihood ratio Test (LRT) for testing that, in a (non)linear mixed effects model, the variances of a subset of the random effects are equal to zero. There is no restriction on the subset of variances that can be tested: for example, it is possible to test that all the variances are equal to zero. Note that the implemented test is asymptotic. This package should be used on model fits from packages 'nlme', 'lmer', and 'saemix'. Charlotte Baey, Paul-Henry Cournède and Estelle Kuhn (2019) <doi:10.1016/j.csda.2019.01.014>.
Author: Charlotte Baey [aut, cre] (<https://orcid.org/0000-0002-1413-1058>), Estelle Kuhn [aut]
Maintainer: Charlotte Baey <charlotte.baey@univ-lille.fr>

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Package pec updated to version 2021.10.11 with previous version 2020.11.17 dated 2020-11-16

Title: Prediction Error Curves for Risk Prediction Models in Survival Analysis
Description: Validation of risk predictions obtained from survival models and competing risk models based on censored data using inverse weighting and cross-validation. Most of the 'pec' functionality has been moved to 'riskRegression'.
Author: Thomas A. Gerds
Maintainer: Thomas A. Gerds <tag@biostat.ku.dk>

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Package sglg updated to version 0.2.0 with previous version 0.1.10 dated 2021-09-18

Title: Fitting Semi-Parametric Generalized log-Gamma Regression Models
Description: Set of tools to fit a linear multiple or semi-parametric regression models with the possibility of non-informative random right-censoring. Under this setup, the localization parameter of the response variable distribution is modeled by using linear multiple regression or semi-parametric functions, whose non-parametric components may be approximated by natural cubic spline or P-splines. The supported distribution for the model error is a generalized log-gamma distribution which includes the generalized extreme value and standard normal distributions as important special cases. Also, some numerical and graphical devices for diagnostic of the fitted models are offered.
Author: Carlos Alberto Cardozo Delgado <cardozorpackages@gmail.com> and G. Paula and L. Vanegas
Maintainer: Carlos Alberto Cardozo Delgado <cardozorpackages@gmail.com>

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Package AgroReg updated to version 1.2.0 with previous version 1.1.0 dated 2021-08-09

Title: Regression Analysis Linear and Nonlinear for Agriculture
Description: Linear and nonlinear regression analysis common in agricultural science articles (Archontoulis & Miguez (2015). <doi:10.2134/agronj2012.0506>). The package includes polynomial, exponential, gaussian, logistic, logarithmic, segmented, non-parametric models, among others. The functions return the model coefficients and their respective p values, coefficient of determination, root mean square error, AIC, BIC, as well as graphs with the equations automatically.
Author: Gabriel Danilo Shimizu [aut, cre] (<https://orcid.org/0000-0001-8524-508X>), Leandro Simoes Azeredo Goncalves [aut, ctb] (<https://orcid.org/0000-0001-9700-9375>)
Maintainer: Gabriel Danilo Shimizu <shimizu@uel.br>

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Package RGtk2 updated to version 2.20.36.1 with previous version 2.20.36 dated 2019-03-08

Title: R Bindings for Gtk 2.8.0 and Above
Description: Facilities in the R language for programming graphical interfaces using Gtk, the Gimp Tool Kit.
Author: Michael Lawrence <michafla@gene.com> and Duncan Temple Lang <duncan@wald.ucdavis.edu>
Maintainer: ORPHANED

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Package opdisDownsampling updated to version 0.6.1 with previous version 0.6.0 dated 2021-08-08

Title: Optimal Distribution Preserving Down-Sampling of Bio-Medical Data
Description: An optimized method for distribution-preserving class-proportional down-sampling of bio-medical data.
Author: Jorn Lotsch [aut,cre] (<https://orcid.org/0000-0002-5818-6958>), Sebastian Malkusch [aut] (<https://orcid.org/0000-0001-6766-140X>), Alfred Ultsch [aut] (<https://orcid.org/0000-0002-7845-3283>)
Maintainer: Jorn Lotsch <j.lotsch@em.uni-frankfurt.de>

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Package cairoDevice updated to version 2.28.2.1 with previous version 2.28.2 dated 2020-07-07

Title: Embeddable Cairo Graphics Device Driver
Description: This device uses Cairo and GTK to draw to the screen, file (png, svg, pdf, and ps) or memory (arbitrary GdkDrawable or Cairo context). The screen device may be embedded into RGtk2 interfaces and supports all interactive features of other graphics devices, including getGraphicsEvent().
Author: Michael Lawrence
Maintainer: ORPHANED

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Package NMAoutlier updated to version 0.1.18 with previous version 0.1.17 dated 2021-02-01

Title: Detecting Outliers in Network Meta-Analysis
Description: A set of functions providing several outlier (i.e., studies with extreme findings) and influential detection measures and methodologies in network meta-analysis : - simple outlier and influential detection measures - outlier and influential detection measures by considering study deletion (shift the mean) - plots for outlier and influential detection measures - Q-Q plot for network meta-analysis - Forward Search algorithm in network meta-analysis. - forward plots to monitor statistics in each step of the forward search algorithm - forward plots for summary estimates and their confidence intervals in each step of forward search algorithm.
Author: Maria Petropoulou [aut, cre] (<https://orcid.org/0000-0002-7147-3644>), Guido Schwarzer [aut] (<https://orcid.org/0000-0001-6214-9087>), Agapios Panos [aut], Dimitris Mavridis [aut] (<https://orcid.org/0000-0003-1041-4592>)
Maintainer: Maria Petropoulou <petropoulou@imbi.uni-freiburg.de>

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Package MHCtools updated to version 1.4.1 with previous version 1.4.0 dated 2021-09-14

Title: Analysis of MHC Data in Non-Model Species
Description: Twelve tools for bioinformatical processing and analysis of major histocompatibility complex (MHC) data. The functions are tailored for amplicon data sets that have been filtered using the 'dada2' method (for more information on 'dada2', visit <https://benjjneb.github.io/dada2/> ), but even other types of data sets can be analyzed. The DistCalc() function calculates Grantham, Sandberg, or p-distances from pairwise comparisons of all sequences in a data set, and mean distances of all pairwise comparisons within each sample in a data set. The function additionally outputs five tables with physico-chemical z-descriptor values (based on Sandberg et al. 1998) for each amino acid position in all sequences in the data set. These tables may be useful for further downstream analyses, such as estimation of MHC supertypes. The BootKmeans() function is a wrapper for the kmeans() function of the 'stats' package, which allows for bootstrapping. Bootstrapping k-estimates may be desirable in data sets, where e.g. BIC- vs. k-values do not produce clear inflection points ("elbows"). BootKmeans() performs multiple runs of kmeans() and estimates optimal k-values based on a user-defined threshold of BIC reduction. The method is an automated and bootstrapped version of visually inspecting elbow plots of BIC- vs. k-values. The ClusterMatch() function is a tool for evaluating whether different k-means() clustering models identify similar clusters, and summarize bootstrap model stats as means for different estimated values of k. It is designed to take files produced by the BootKmeans() function as input, but other data can be analysed if the descriptions of the required data formats are observed carefully. The HpltFind() function infers putative haplotypes from families in the data set. The GetHpltTable() and GetHpltStats() functions evaluate the accuracy of the haplotype inference. The PapaDiv() function compares parent pairs in the data set and calculate their joint MHC diversity, taking into account sequence variants that occur in both parents. The ReplMatch() function matches replicates in data sets in order to evaluate genotyping success. The GetReplTable() and GetReplStats() functions perform such an evaluation. The CreateFas() function creates a fasta file with all the sequences in the data set. The CreateSamplesFas() function creates individual fasta files for each sample in the data set.
Author: Jacob Roved [aut, cre]
Maintainer: Jacob Roved <jacob.roved@biol.lu.se>

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Package sets updated to version 1.0-19 with previous version 1.0-18 dated 2017-12-12

Title: Sets, Generalized Sets, Customizable Sets and Intervals
Description: Data structures and basic operations for ordinary sets, generalizations such as fuzzy sets, multisets, and fuzzy multisets, customizable sets, and intervals.
Author: David Meyer [aut, cre], Kurt Hornik [aut], Christian Buchta [ctb]
Maintainer: David Meyer <David.Meyer@R-project.org>

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Package riskRegression updated to version 2021.10.10 with previous version 2020.12.08 dated 2020-12-09

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], Paul Blanche [ctb], Rikke Mortensen [ctb], Marvin Wright [ctb], Nikolaj Tollenaar [ctb], John Muschelli [ctb], Ulla Brasch Mogensen [ctb], Johan Sebastian Ohlendorff [aut], Brice Ozenne [aut] (<https://orcid.org/0000-0001-9694-2956>)
Maintainer: Thomas Alexander Gerds <tag@biostat.ku.dk>

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Package easySdcTable updated to version 1.0.0 with previous version 0.9.0 dated 2021-09-10

Title: Easy Interface to the Statistical Disclosure Control Package 'sdcTable' Extended with the 'GaussSuppression' Method
Description: The main function, ProtectTable(), performs table suppression according to a frequency rule with a data set as the only required input. Within this function, protectTable(), protect_linked_tables() or runArgusBatchFile() in package 'sdcTable' is called. Lists of level-hierarchy (parameter 'dimList') and other required input to these functions are created automatically. The suppression method Gauss (default) is an additional method that is not available in 'sdcTable'. The function, PTgui(), starts a graphical user interface based on the 'shiny' package.
Author: Øyvind Langsrud [aut, cre]
Maintainer: Øyvind Langsrud <oyl@ssb.no>

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Package clue updated to version 0.3-60 with previous version 0.3-59 dated 2021-04-16

Title: Cluster Ensembles
Description: CLUster Ensembles.
Author: Kurt Hornik [aut, cre] (<https://orcid.org/0000-0003-4198-9911>), Walter Böhm [ctb]
Maintainer: Kurt Hornik <Kurt.Hornik@R-project.org>

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Package WeightSVM updated to version 1.7-9 with previous version 1.7-5 dated 2020-05-28

Title: Subject Weighted Support Vector Machines
Description: Functions for subject/instance weighted support vector machines (SVM). It uses a modified version of 'libsvm' and is compatible with package 'e1071'.
Author: Tianchen Xu [aut, cre] (<https://orcid.org/0000-0002-0102-7630>), Chih-Chung Chang [ctb, cph] (libsvm C++-code), Chih-Chen Lin [ctb, cph] (libsvm C++-code), Ming-Wei Chang [ctb, cph] (libsvm C++-code), Hsuan-Tien Lin [ctb, cph] (libsvm C++-code), Ming-Hen Tsai [ctb, cph] (libsvm C++-code), Chia-Hua Ho [ctb, cph] (libsvm C++-code), Hsiang-Fu Yu [ctb, cph] (libsvm C++-code), David Meyer [ctb], Evgenia Dimitriadou [ctb], Kurt Hornik [ctb], Andreas Weingessel [ctb], Friedrich Leisch [ctb]
Maintainer: Tianchen Xu <tx2155@columbia.edu>

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Package swdpwr updated to version 1.6 with previous version 1.5 dated 2021-05-16

Title: Power Calculation for Stepped Wedge Cluster Randomized Trials
Description: To meet the needs of statistical power calculation for stepped wedge cluster randomized trials, we developed this software. Different parameters can be specified by users for different scenarios, including: cross-sectional and cohort designs, binary and continuous outcomes, marginal (GEE) and conditional models (mixed effects model), three link functions (identity, log, logit links), with and without time effects under exchangeable, nested exchangeable and block exchangeable correlation structures. Unequal numbers of clusters per sequence are also allowed. The methods included in this package: Zhou et al. (2020) <doi:10.1093/biostatistics/kxy031>, Li et al. (2018) <doi:10.1111/biom.12918>. Supplementary documents can be found at: <https://ysph.yale.edu/cmips/research/software/swdpwr/>. The Shiny app for swdpwr can be accessed at: <https://jiachenchen322.shinyapps.io/swdpwr_shinyapp/>. The package also includes functions that perform calculations for the intra-cluster correlation coefficients based on the random effects variances as input variables for continuous and binary outcomes, respectively.
Author: Jiachen Chen [cre, aut], Xin Zhou [aut], Fan Li [aut] and Donna Spiegelman [aut].
Maintainer: Jiachen Chen <jiachen.chen322@gmail.com>

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Package piwikproR updated to version 0.3.1 with previous version 0.2.0 dated 2021-06-08

Title: Access 'Piwik Pro' Website Statistics
Description: Run Queries against the API of 'Piwik Pro' <https://developers.piwik.pro/en/latest/custom_reports/http_api/http_api.html>. The result is a tibble.
Author: Martin Stingl <martin.stingl@dfv.de>
Maintainer: Martin Stingl <martin.stingl@dfv.de>

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Package trustOptim updated to version 0.8.7.3 with previous version 0.8.7.2 dated 2021-09-26

Title: Trust Region Optimization for Nonlinear Functions with Sparse Hessians
Description: Trust region algorithm for nonlinear optimization. Efficient when the Hessian of the objective function is sparse (i.e., relatively few nonzero cross-partial derivatives). See Braun, M. (2014) <doi:10.18637/jss.v060.i04>.
Author: Michael Braun [aut, cre, cph] (<https://orcid.org/0000-0003-4774-2119>)
Maintainer: Michael Braun <braunm@smu.edu>

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New package stableGR with initial version 1.1
Package: stableGR
Title: A Stable Gelman-Rubin Diagnostic for Markov Chain Monte Carlo
Version: 1.1
Date: 2021-10-9
Maintainer: Christina Knudson <knud8583@stthomas.edu>
Description: Practitioners of Bayesian statistics often use Markov chain Monte Carlo (MCMC) samplers to sample from a posterior distribution. This package determines whether the MCMC sample is large enough to yield reliable estimates of the target distribution. In particular, this calculates a Gelman-Rubin convergence diagnostic using stable and consistent estimators of Monte Carlo variance. Additionally, this uses the connection between an MCMC sample's effective sample size and the Gelman-Rubin diagnostic to produce a threshold for terminating MCMC simulation. Finally, this informs the user whether enough samples have been collected and (if necessary) estimates the number of samples needed for a desired level of accuracy. The theory underlying these methods can be found in "Revisiting the Gelman-Rubin Diagnostic" by Vats and Knudson (2018) <arXiv:1812:09384>.
License: GPL-3
Depends: R (>= 3.5), mcmcse(>= 1.4-1)
Imports: mvtnorm
ByteCompile: TRUE
Repository: CRAN
NeedsCompilation: no
Packaged: 2021-10-10 00:22:29 UTC; admin
Author: Christina Knudson [aut, cre], Dootika Vats [aut]
Date/Publication: 2021-10-11 08:40:02 UTC

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Package segclust2d updated to version 0.3.0 with previous version 0.2.0 dated 2019-02-27

Title: Bivariate Segmentation/Clustering Methods and Tools
Description: Provides two methods for segmentation and joint segmentation/clustering of bivariate time-series. Originally intended for ecological segmentation (home-range and behavioural modes) but easily applied on other series, the package also provides tools for analysing outputs from R packages 'moveHMM' and 'marcher'. The segmentation method is a bivariate extension of Lavielle's method available in 'adehabitatLT' (Lavielle, 1999 <doi:10.1016/S0304-4149(99)00023-X> and 2005 <doi:10.1016/j.sigpro.2005.01.012>). This method rely on dynamic programming for efficient segmentation. The segmentation/clustering method alternates steps of dynamic programming with an Expectation-Maximization algorithm. This is an extension of Picard et al (2007) <doi:10.1111/j.1541-0420.2006.00729.x> method (formerly available in 'cghseg' package) to the bivariate case. The method is fully described in Patin et al (2018) <doi:10.1101/444794>.
Author: Remi Patin [aut, cre], Marie-Pierre Etienne [aut], Emilie Lebarbier [aut], Simon Benhamou [aut]
Maintainer: Remi Patin <remi.patin@normale.fr>

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Package rtmpt updated to version 0.2-2 with previous version 0.2-1 dated 2021-06-03

Title: Fitting RT-MPT Models
Description: Fit response-time extended multinomial processing tree (RT-MPT) models by Klauer and Kellen (2018) <doi:10.1016/j.jmp.2017.12.003>. The RT-MPT class not only incorporate frequencies like traditional multinomial processing tree (MPT) models, but also latencies. This enables it to estimate process completion times and encoding plus motor execution times next to the process probabilities of traditional MPTs. 'rtmpt' is a Bayesian framework and posterior samples are sampled using a Metropolis-Gibbs sampler like the one described in the Klauer and Kellen (2018), but with some modifications. Other than in the original C++ program we use the free and open source GNU Scientific Library (GSL). There is also the possibility to suppress single process completion times.
Author: Raphael Hartmann [aut, cre], Karl C. Klauer [cph, aut, ctb, ths], Henrik Singmann [ctb, aut], Jean Marie Linhart [ctb], Frederick Novomestky [ctb]
Maintainer: Raphael Hartmann <raphael.hartmann@protonmail.com>

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Package rbibutils updated to version 2.2.4 with previous version 2.2.3 dated 2021-08-09

Title: Read 'Bibtex' Files and Convert Between Bibliography Formats
Description: Read and write 'Bibtex' files. Convert between bibliography formats, including 'Bibtex', 'Biblatex', 'PubMed', 'Endnote', and 'Bibentry'. Includes a port of the 'bibutils' utilities by Chris Putnam <https://sourceforge.net/projects/bibutils/>. Supports all bibliography formats and character encodings implemented in 'bibutils'.
Author: Georgi N. Boshnakov [aut, cre] (R port, R code, new C code and modifications to bibutils' C code, conversion to Bibentry (R and C code)), Chris Putman [aut] (src/*, author of the bibutils libraries, https://sourceforge.net/projects/bibutils/), Richard Mathar [ctb] (src/addsout.c), Johannes Wilm [ctb] (src/biblatexin.c, src/bltypes.c)
Maintainer: Georgi N. Boshnakov <georgi.boshnakov@manchester.ac.uk>

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Package rasterVis updated to version 0.51.0 with previous version 0.50.3 dated 2021-07-22

Title: Visualization Methods for Raster Data
Description: Methods for enhanced visualization and interaction with raster data. It implements visualization methods for quantitative data and categorical data, both for univariate and multivariate rasters. It also provides methods to display spatiotemporal rasters, and vector fields. See the website for examples.
Author: Oscar Perpinan Lamigueiro [cre, aut] (<https://orcid.org/0000-0002-4134-7196>), Robert Hijmans [aut]
Maintainer: Oscar Perpinan Lamigueiro <oscar.perpinan@upm.es>

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Package FRK updated to version 2.0.1 with previous version 2.0.0 dated 2021-05-28

Title: Fixed Rank Kriging
Description: Fixed Rank Kriging is a tool for spatial/spatio-temporal modelling and prediction with large datasets. The approach models the field, and hence the covariance function, using a set of r basis functions, where r is typically much smaller than the number of data points (or polygons) m. This low-rank basis-function representation facilitates the modelling of 'big' spatial/spatio-temporal data. The method naturally allows for non-stationary, anisotropic covariance functions. Discretisation of the spatial domain into so-called basic areal units (BAUs) facilitates the use of observations with varying support (i.e., both point-referenced and areal supports, potentially simultaneously), and prediction over arbitrary user-specified regions. `FRK` also supports inference over various manifolds, including the 2D plane and 3D sphere, and it provides helper functions to model, fit, predict, and plot with relative ease. Version 2.0.0 and above of the package `FRK` also supports modelling of non-Gaussian data, by employing a spatial generalised linear mixed model (GLMM) framework to cater for Poisson, binomial, negative-binomial, gamma, and inverse-Gaussian distributions. Zammit-Mangion and Cressie <doi:10.18637/jss.v098.i04> describe `FRK` in a Gaussian setting, and detail its use of basis functions and BAUs.
Author: Andrew Zammit-Mangion [aut, cre], Matthew Sainsbury-Dale [aut]
Maintainer: Andrew Zammit-Mangion <andrewzm@gmail.com>

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New package fipio with initial version 1.0.0
Package: fipio
Title: Lightweight Federal Information Processing System (FIPS) Code Information Retrieval
Version: 1.0.0
Description: Provides a lightweight suite of functions for retrieving information about 5-digit or 2-digit US FIPS codes.
URL: https://fipio.justinsingh.me, https://github.com/program--/fipio
BugReports: https://github.com/program--/fipio/issues
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 2.10)
Suggests: testthat (>= 3.0.0), mockery (>= 0.4.2), sfheaders, covr
NeedsCompilation: no
Packaged: 2021-10-10 06:41:37 UTC; jsinghm
Author: Justin Singh-Mohudpur [aut, cre] (<https://orcid.org/0000-0002-5233-5799>)
Maintainer: Justin Singh-Mohudpur <justin@justinsingh.me>
Repository: CRAN
Date/Publication: 2021-10-11 08:40:05 UTC

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New package excessmort with initial version 0.6.1
Package: excessmort
Title: Excess Mortality
Version: 0.6.1
Depends: R (>= 3.5.0),
Imports: stats, datasets, dplyr, tidyr, rlang, lubridate, splines, ggplot2, scales
Suggests: tidycensus, knitr, rmarkdown
VignetteBuilder: knitr
Description: Implementation of method for estimating excess mortality and other health related outcomes from weekly or daily count data described in Acosta and Irizarry (2021) "A Flexible Statistical Framework for Estimating Excess Mortality".
License: Artistic-2.0
Encoding: UTF-8
LazyData: true
LazyDataCompression: xz
NeedsCompilation: no
Packaged: 2021-10-08 20:22:32 UTC; rafa
Author: Rafael A. Irizarry [aut, cre], Rolando Acosta [aut]
Maintainer: Rafael A. Irizarry <rafael_irizarry@dfci.harvard.edu>
Repository: CRAN
Date/Publication: 2021-10-11 08:10:12 UTC

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New package drpop with initial version 0.0.1
Package: drpop
Title: Efficient Doubly Robust Population Size Estimation
Version: 0.0.1
Description: Estimation of the total population size from capture-recapture data efficiently and with low bias implementing the methods from Das M, Kennedy EH, and Jewell NP (2021) <arXiv:2104.14091>. The estimator is doubly robust against errors in the estimation of the intermediate nuisance parameters. Users can choose from the flexible estimation models provided in the package, or use any other preferred model.
Depends: stats
Imports: gam, janitor, reshape2, stringr, tidyr, dplyr, SuperLearner, ggplot2, nnet, nnls, parallel, ranger
License: GPL-3
Encoding: UTF-8
Suggests: testthat (>= 2.0.0)
NeedsCompilation: no
Packaged: 2021-10-09 16:12:06 UTC; manja
Author: Manjari Das [aut, cre] (<https://orcid.org/0000-0002-6781-6368>), Edward H. Kennedy [aut] (<https://orcid.org/0000-0002-1510-8175>)
Maintainer: Manjari Das <manjari8d@gmail.com>
Repository: CRAN
Date/Publication: 2021-10-11 08:20:02 UTC

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New package apache.sedona with initial version 1.1.0
Package: apache.sedona
Title: R Interface for Apache Sedona
Version: 1.1.0
Maintainer: Apache Sedona <private@sedona.apache.org>
Description: R interface for 'Apache Sedona' based on 'sparklyr' (<https://sedona.apache.org>).
License: Apache License 2.0
Depends: R (>= 3.2)
Imports: rlang, sparklyr (>= 1.3), DBI (>= 0.6-1), dplyr (>= 0.7.2), dbplyr (>= 1.1.0)
Suggests: knitr, rmarkdown
Encoding: UTF-8
SystemRequirements: 'Apache Spark' 2.4.x or 3.x
NeedsCompilation: no
Packaged: 2021-10-09 01:54:24 UTC; jiayu
Author: Apache Sedona [aut, cre], Jia Yu [ctb, cph], Yitao Li [aut, cph] (<https://orcid.org/0000-0002-1261-905X>), The Apache Software Foundation [cph], RStudio [cph]
Repository: CRAN
Date/Publication: 2021-10-11 08:10:15 UTC

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Package Anthropometry updated to version 1.16 with previous version 1.15 dated 2021-04-19

Title: Statistical Methods for Anthropometric Data
Description: Statistical methodologies especially developed to analyze anthropometric data. These methods are aimed at providing effective solutions to some commons problems related to Ergonomics and Anthropometry. They are based on clustering, the statistical concept of data depth, statistical shape analysis and archetypal analysis. Please see Vinue (2017) <doi:10.18637/jss.v077.i06>.
Author: Guillermo Vinue, Irene Epifanio, Amelia Simo, M. Victoria Ibanez, Juan Domingo, Guillermo Ayala
Maintainer: Guillermo Vinue <Guillermo.Vinue@uv.es>

Diff between Anthropometry versions 1.15 dated 2021-04-19 and 1.16 dated 2021-10-11

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Package terra updated to version 1.4-11 with previous version 1.4-9 dated 2021-10-07

Title: Spatial Data Analysis
Description: Methods for spatial data analysis with raster and vector data. Raster methods allow for low-level data manipulation as well as high-level global, local, zonal, and focal computation. The predict and interpolate methods facilitate the use of regression type (interpolation, machine learning) models for spatial prediction, including with satellite remote sensing data. Processing of very large files is supported. See the manual and tutorials on <https://rspatial.org/terra/> to get started. 'terra' is very similar to the 'raster' package; but 'terra' can do more, is easier to use, and it is faster.
Author: Robert J. Hijmans [cre, aut] (<https://orcid.org/0000-0001-5872-2872>), Roger Bivand [ctb] (<https://orcid.org/0000-0003-2392-6140>), Karl Forner [ctb], Jeroen Ooms [ctb] (<https://orcid.org/0000-0002-4035-0289>), Edzer Pebesma [ctb] (<https://orcid.org/0000-0001-8049-7069>)
Maintainer: Robert J. Hijmans <r.hijmans@gmail.com>

Diff between terra versions 1.4-9 dated 2021-10-07 and 1.4-11 dated 2021-10-11

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Package sfcr updated to version 0.2.1 with previous version 0.2.0 dated 2021-10-05

Title: Simulate Stock-Flow Consistent Models
Description: Routines to write, simulate, and validate stock-flow consistent (SFC) models. The accounting structure of SFC models are described in Godley and Lavoie (2007, ISBN:978-1-137-08599-3). The algorithms implemented to solve the models (Gauss-Seidel and Broyden) are described in Kinsella and O'Shea (2010) <doi:10.2139/ssrn.1729205> and Peressini and Sullivan (1988, ISBN:0-387-96614-5).
Author: Joao Macalos [aut, cre] (<https://orcid.org/0000-0001-6050-6394>)
Maintainer: Joao Macalos <joaomacalos@gmail.com>

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Package semptools updated to version 0.2.9.3 with previous version 0.2.9.2 dated 2021-09-27

Title: Customizing Structural Equation Modelling Plots
Description: Most function focus on specific ways to customize a graph. They use a 'qgraph' output as the first argument, and return a modified 'qgraph' object. This allows the functions to be chained by a pipe operator.
Author: Shu Fai Cheung [aut, cre] (<https://orcid.org/0000-0002-9871-9448>), Mark Hok Chio Lai [aut] (<https://orcid.org/0000-0002-9196-7406>)
Maintainer: Shu Fai Cheung <shufai.cheung@gmail.com>

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Package pubh updated to version 1.2.5 with previous version 1.1.20 dated 2021-02-16

Title: A Toolbox for Public Health and Epidemiology
Description: A toolbox for making R functions and capabilities more accessible to students and professionals from Epidemiology and Public Health related disciplines. Includes a function to report coefficients and confidence intervals from models using robust standard errors (when available), functions that expand 'ggplot2' plots and functions relevant for introductory papers in Epidemiology or Public Health. Please note that use of the provided data sets is for educational purposes only.
Author: Josie Athens [aut, cre], Frank Harell [ctb], John Fox [ctb], R-Core [ctb]
Maintainer: Josie Athens <josie.athens@gmail.com>

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New package niaidMI with initial version 1.0.0
Package: niaidMI
Title: Markov Model Multiple Imputation for NIAID OS
Version: 1.0.0
Date: 2021-10-08
Description: The implementation of Markov Model Multiple Imputation with the application to COVID-19 scale, NIAID OS.
License: MIT + file LICENSE
Depends: R (>= 3.5.0)
Suggests: testthat
Imports: Rcpp (>= 1.0.3)
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2021-10-08 14:59:35 UTC; c300194
Author: Nathan Morris [aut, cre], Chaoran Hu [aut], Eli Lilly and Company [cph]
Maintainer: Nathan Morris <morris_nathan@lilly.com>
Repository: CRAN
Date/Publication: 2021-10-11 07:50:10 UTC

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Permanent link

Package meta updated to version 5.0-0 with previous version 4.19-2 dated 2021-09-30

Title: General Package for Meta-Analysis
Description: User-friendly general package providing standard methods for meta-analysis and supporting Schwarzer, Carpenter, and Rücker <DOI:10.1007/978-3-319-21416-0>, "Meta-Analysis with R" (2015): - fixed effect and random effects meta-analysis; - several plots (forest, funnel, Galbraith / radial, L'Abbe, Baujat, bubble); - statistical tests and trim-and-fill method to evaluate bias in meta-analysis; - import data from 'RevMan 5'; - prediction interval, Hartung-Knapp method for random effects model; - cumulative meta-analysis and leave-one-out meta-analysis; - meta-regression; - generalised linear mixed models; - produce forest plot summarising several (subgroup) meta-analyses.
Author: Guido Schwarzer [cre, aut] (<https://orcid.org/0000-0001-6214-9087>)
Maintainer: Guido Schwarzer <sc@imbi.uni-freiburg.de>

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Package MedianaDesigner updated to version 0.5 with previous version 0.4 dated 2021-10-05

Title: Efficient Simulation-Based Power and Sample Size Calculations for a Broad Class of Late-Stage Clinical Trials
Description: The following modules are included in the package: Adaptive designs with data-driven sample size or event count re-estimation, Adaptive designs with data-driven treatment selection, Adaptive designs with data-driven population selection, Optimal selection of a futility stopping rule, Event prediction in event-driven trials, Adaptive trials with response-adaptive randomization (experimental module), Traditional trials with multiple objectives (experimental module).
Author: Alex Dmitrienko [aut, cre]
Maintainer: Alex Dmitrienko <admitrienko@mediana.us>

Diff between MedianaDesigner versions 0.4 dated 2021-10-05 and 0.5 dated 2021-10-11

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Permanent link

Package madrat updated to version 2.3.2 with previous version 2.3.1 dated 2021-10-05

Title: May All Data be Reproducible and Transparent (MADRaT) *
Description: Provides a framework which should improve reproducibility and transparency in data processing. It provides functionality such as automatic meta data creation and management, rudimentary quality management, data caching, work-flow management and data aggregation. * The title is a wish not a promise. By no means we expect this package to deliver everything what is needed to achieve full reproducibility and transparency, but we believe that it supports efforts in this direction.
Author: Jan Philipp Dietrich [aut, cre], Lavinia Baumstark [aut], Stephen Wirth [aut], Anastasis Giannousakis [aut], Renato Rodrigues [aut], Benjamin Leon Bodirsky [aut], Ulrich Kreidenweis [aut], David Klein [aut], Pascal Führlich [aut]
Maintainer: Jan Philipp Dietrich <dietrich@pik-potsdam.de>

Diff between madrat versions 2.3.1 dated 2021-10-05 and 2.3.2 dated 2021-10-11

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Package gslnls updated to version 1.0.1 with previous version 1.0.0 dated 2021-10-07

Title: GSL Nonlinear Least-Squares Fitting
Description: An R interface to nonlinear least-squares optimization with the GNU Scientific Library (GSL), see M. Galassi et al. (2009, ISBN:0954612078). The available trust region methods include the Levenberg-Marquadt algorithm with and without geodesic acceleration, and several variants of Powell's dogleg algorithm. Bindings are provided to tune a number of parameters affecting the low-level aspects of the trust region algorithms. The interface mimics R's nls() function and returns model objects inheriting from the same class.
Author: Joris Chau [aut, cre]
Maintainer: Joris Chau <joris.chau@openanalytics.eu>

Diff between gslnls versions 1.0.0 dated 2021-10-07 and 1.0.1 dated 2021-10-11

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New package gapclosing with initial version 1.0.2
Package: gapclosing
Title: Estimate Gaps Under an Intervention
Version: 1.0.2
Description: Provides functions to estimate the disparities across categories (e.g. Black and white) that persists if a treatment variable (e.g. college) is equalized. Makes estimates by treatment modeling, outcome modeling, and doubly-robust augmented inverse probability weighting estimation, with standard errors calculated by a nonparametric bootstrap. Cross-fitting is supported. Survey weights are supported for point estimation but not for standard error estimation; those applying this package with complex survey samples should consult the data distributor to select an appropriate approach for standard error construction, which may involve calling the functions repeatedly for many sets of replicate weights provided by the data distributor. The methods in this package are described in Lundberg (2021) <doi:10.31235/osf.io/gx4y3>.
License: MIT + file LICENSE
URL: https://ilundberg.github.io/gapclosing/
BugReports: https://github.com/ilundberg/gapclosing/issues
Encoding: UTF-8
Imports: stats, mgcv, ranger, glmnet, magrittr, dplyr, forcats, ggplot2, tidyr, foreach, tidyselect, parallel, doParallel
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, spelling
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-09-30 01:53:22 UTC; ilundberg
Author: Ian Lundberg [aut, cre] (<https://orcid.org/0000-0002-1909-2270>)
Maintainer: Ian Lundberg <ianlundberg@ucla.edu>
Language: en-US
Repository: CRAN
Date/Publication: 2021-10-11 07:40:22 UTC

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New package factset.protobuf.stach.v2 with initial version 1.0.0
Package: factset.protobuf.stach.v2
Title: 'FactSet' 'STACH' Library
Version: 1.0.0
Author: analytics-reporting
Maintainer: Charlie Mathis<chmathis@factset.com>
Description: Generates 'RProtobuf' classes for 'FactSet' 'STACH' tabular format which represents complex multi-dimensional array of data. These classes help in the 'serialization' and 'deserialization' of 'STACH' formatted data. See 'GitHub' repository <https://github.com/factset/stachschema-sdks/tree/master/r/factset.protobuf.stach.v2> documentation for more information.
URL: https://github.com/factset/stachschema-sdks
BugReports: https://github.com/factset/stachschema-sdks/issues
License: Apache License 2.0
Encoding: UTF-8
Imports: R6
Depends: RProtoBuf
Suggests: testthat
NeedsCompilation: no
Packaged: 2021-10-08 09:55:03 UTC; vaddala
Repository: CRAN
Date/Publication: 2021-10-11 08:00:05 UTC

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Package exactRankTests updated to version 0.8-34 with previous version 0.8-32 dated 2021-04-16

Title: Exact Distributions for Rank and Permutation Tests
Description: Computes exact conditional p-values and quantiles using an implementation of the Shift-Algorithm by Streitberg & Roehmel.
Author: Torsten Hothorn [aut, cre], Kurt Hornik [aut]
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

Diff between exactRankTests versions 0.8-32 dated 2021-04-16 and 0.8-34 dated 2021-10-11

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Package epiR updated to version 2.0.38 with previous version 2.0.36 dated 2021-09-26

Title: Tools for the Analysis of Epidemiological Data
Description: Tools for the analysis of epidemiological and surveillance data. Contains functions for directly and indirectly adjusting measures of disease frequency, quantifying measures of association on the basis of single or multiple strata of count data presented in a contingency table, computation of confidence intervals around incidence risk and incidence rate estimates and sample size calculations for cross-sectional, case-control and cohort studies. Surveillance tools include functions to calculate an appropriate sample size for 1- and 2-stage representative freedom surveys, functions to estimate surveillance system sensitivity and functions to support scenario tree modelling analyses.
Author: Mark Stevenson <mark.stevenson1@unimelb.edu.au> and Evan Sergeant <evansergeant@gmail.com> with contributions from Telmo Nunes, Cord Heuer, Jonathon Marshall, Javier Sanchez, Ron Thornton, Jeno Reiczigel, Jim Robison-Cox, Paola Sebastiani, Peter Solymos, Kazuki Yoshida, Geoff Jones, Sarah Pirikahu, Simon Firestone, Ryan Kyle, Johann Popp, Mathew Jay, Charles Reynard, Allison Cheung, Nagendra Singanallur and Aniko Szabo.
Maintainer: Mark Stevenson <mark.stevenson1@unimelb.edu.au>

Diff between epiR versions 2.0.36 dated 2021-09-26 and 2.0.38 dated 2021-10-11

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New package csodata with initial version 1.2.1
Package: csodata
Title: Download Data from the CSO 'PxStat' API
Version: 1.2.1
Date: 2021-10-07
Maintainer: Conor Crowley <conor.crowley@cso.ie>
Description: Imports 'PxStat' data in JSON-stat format and (optionally) reshapes it into wide format. The Central Statistics Office (CSO) is the national statistical institute of Ireland and 'PxStat' is the CSOs online database of Official Statistics. This database contains current and historical data series compiled from CSO statistical releases and is accessed at <http://data.cso.ie>. The CSO 'PxStat' Application Programming Interface (API), which is accessed in this package, provides access to 'PxStat' data in JSON-stat format at <http://data.cso.ie>. This dissemination tool allows developers machine to machine access to CSO 'PxStat' data.
Imports: dplyr, httr, jsonlite, reshape2, rjstat, R.cache, sf, lubridate
License: GPL-3
Encoding: UTF-8
Suggests: knitr, rmarkdown, tmap, viridisLite
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-10-07 12:59:27 UTC; crowleyco
Author: Eoin Horgan [aut] (<https://orcid.org/0000-0002-3446-6154>), Conor Crowley [aut, cre], Vytas Vaiciulis [aut], Mervyn O'Luing [aut]
Repository: CRAN
Date/Publication: 2021-10-11 07:40:32 UTC

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Package ChemoSpec2D updated to version 0.5.0 with previous version 0.4.187 dated 2021-03-16

Title: Exploratory Chemometrics for 2D Spectroscopy
Description: A collection of functions for exploratory chemometrics of 2D spectroscopic data sets such as COSY (correlated spectroscopy) and HSQC (heteronuclear single quantum coherence) 2D NMR (nuclear magnetic resonance) spectra. 'ChemoSpec2D' deploys methods aimed primarily at classification of samples and the identification of spectral features which are important in distinguishing samples from each other. Each 2D spectrum (a matrix) is treated as the unit of observation, and thus the physical sample in the spectrometer corresponds to the sample from a statistical perspective. In addition to chemometric tools, a few tools are provided for plotting 2D spectra, but these are not intended to replace the functionality typically available on the spectrometer. 'ChemoSpec2D' takes many of its cues from 'ChemoSpec' and tries to create consistent graphical output and to be very user friendly.
Author: Bryan A. Hanson [aut, cre] (<https://orcid.org/0000-0003-3536-8246>)
Maintainer: Bryan A. Hanson <hanson@depauw.edu>

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New package cartogramR with initial version 1.0-3
Package: cartogramR
Version: 1.0-3
Date: 2021-10-01
Title: Continuous Cartogram
Description: Procedures for making continuous cartogram. Procedures available are: flow based cartogram (Gastner & Newman (2004) <doi:10.1073/pnas.0400280101>), fast flow based cartogram (Gastner, Seguy & More (2018) <doi:10.1073/pnas.1712674115>), rubber band based cartogram (Dougenik et al. (1985) <doi:10.1111/j.0033-0124.1985.00075.x>).
Depends: R (>= 3.5.0)
Imports: sf, data.table
Suggests: lwgeom
SystemRequirements: FFTW (>=3.3.1); possible package: fftw-devel (rpm), fftw-dev (deb) or fftw (brew).
License: MIT + file LICENSE
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2021-10-07 14:30:24 UTC; pac
Author: Pierre-Andre Cornillon [aut, cre], Florent Demoraes [aut], Flow-Based-Cartograms [cph] (Author of core C code for gsm and gn procedures)
Maintainer: Pierre-Andre Cornillon <pierre-andre.cornillon@univ-rennes2.fr>
Repository: CRAN
Date/Publication: 2021-10-11 07:40:35 UTC

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Package BTSPAS updated to version 2021.11.1 with previous version 2021.1.1 dated 2020-12-16

Title: Bayesian Time-Stratified Population Analysis
Description: Provides advanced Bayesian methods to estimate abundance and run-timing from temporally-stratified Petersen mark-recapture experiments. Methods include hierarchical modelling of the capture probabilities and spline smoothing of the daily run size. Theory described in Bonner and Schwarz (2011) <doi:10.1111/j.1541-0420.2011.01599.x>.
Author: Carl J Schwarz <cschwarz.stat.sfu.ca@gmail.com> and Simon J Bonner <sbonner6@uwo.ca>
Maintainer: Carl J Schwarz <cschwarz.stat.sfu.ca@gmail.com>

Diff between BTSPAS versions 2021.1.1 dated 2020-12-16 and 2021.11.1 dated 2021-10-11

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Package ATAforecasting updated to version 0.0.53 with previous version 0.0.52 dated 2021-03-08

Title: Automatic Time Series Analysis and Forecasting Using the Ata Method
Description: The Ata method (Yapar et al. (2019) <doi:10.15672/hujms.461032>), an alternative to exponential smoothing (described in Yapar (2016) <doi:10.15672/HJMS.201614320580>, Yapar et al. (2017) <doi:10.15672/HJMS.2017.493>), is a new univariate time series forecasting method which provides innovative solutions to issues faced during the initialization and optimization stages of existing forecasting methods. Forecasting performance of the Ata method is superior to existing methods both in terms of easy implementation and accurate forecasting. It can be applied to non-seasonal or seasonal time series which can be decomposed into four components (remainder, level, trend and seasonal). This methodology performed well on the M3 and M4-competition data. This package was written based on Ali Sabri Taylan’s PhD dissertation.
Author: Ali Sabri Taylan [aut, cre, cph] (<https://orcid.org/0000-0001-9514-934X>), Hanife Taylan Selamlar [aut, cph] (<https://orcid.org/0000-0002-4091-884X>), Guckan Yapar [aut, ths, cph] (<https://orcid.org/0000-0002-0971-6676>)
Maintainer: Ali Sabri Taylan <alisabritaylan@gmail.com>

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Package photobiologyInOut updated to version 0.4.23 with previous version 0.4.22-1 dated 2020-04-14

Title: Read Spectral and Logged Data from Foreign Files
Description: Functions for reading, and in some cases writing, foreign files containing spectral data from spectrometers and their associated software, output from daylight simulation models in common use, and some spectral data repositories. As well as functions for exchange of spectral data with other R packages. Part of the 'r4photobiology' suite, Aphalo P. J. (2015) <doi:10.19232/uv4pb.2015.1.14>.
Author: Pedro J. Aphalo [aut, cre] (<https://orcid.org/0000-0003-3385-972X>), Titta K. Kotilainen [ctb] (<https://orcid.org/0000-0002-2822-9734>), Glenn Davis [ctb]
Maintainer: Pedro J. Aphalo <pedro.aphalo@helsinki.fi>

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Package multivator updated to version 1.1-10 with previous version 1.1-9 dated 2017-05-28

Title: A Multivariate Emulator
Description: A multivariate generalization of the emulator package.
Author: Robin K. S. Hankin [aut, cre] (<https://orcid.org/0000-0001-5982-0415>)
Maintainer: Robin K. S. Hankin <hankin.robin@gmail.com>

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Package jsmodule updated to version 1.2.0 with previous version 1.1.9 dated 2021-09-23

Title: 'RStudio' Addins and 'Shiny' Modules for Medical Research
Description: 'RStudio' addins and 'Shiny' modules for descriptive statistics, regression and survival analysis.
Author: Jinseob Kim [aut, cre] (<https://orcid.org/0000-0002-9403-605X>), Zarathu [cph, fnd]
Maintainer: Jinseob Kim <jinseob2kim@gmail.com>

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Package jskm updated to version 0.4.3 with previous version 0.4.2 dated 2020-11-24

Title: Kaplan-Meier Plot with 'ggplot2'
Description: The function 'jskm()' creates publication quality Kaplan-Meier plot with at risk tables below. 'svyjskm()' provides plot for weighted Kaplan-Meier estimator.
Author: Jinseob Kim [aut, cre] (<https://orcid.org/0000-0002-9403-605X>), Zarathu [cph, fnd]
Maintainer: Jinseob Kim <jinseob2kim@gmail.com>

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Package grImport updated to version 0.9-4 with previous version 0.9-3 dated 2019-11-27

Title: Importing Vector Graphics
Description: Functions for converting, importing, and drawing PostScript pictures in R plots.
Author: Paul Murrell [aut, cre], Richard Walton [aut], Simon Potter [ctb]
Maintainer: Paul Murrell <p.murrell@auckland.ac.nz>

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Package binsreg updated to version 0.7 with previous version 0.6 dated 2021-08-07

Title: Binscatter Estimation and Inference
Description: Provides tools for statistical analysis using the binscatter methods developed by Cattaneo, Crump, Farrell and Feng (2021a) <arXiv:1902.09608> and Cattaneo, Crump, Farrell and Feng (2021b) <arXiv:1902.09615>. Binscatter provides a flexible way of describing the relationship between two variables based on partitioning/binning of the independent variable of interest. binsreg(), binsqreg() and binsglm() implement binscatter least squares regression, quantile regression and generalized linear regression respectively, with particular focus on constructing binned scatter plots. They also implement robust (pointwise and uniform) inference of regression functions and derivatives thereof. binstest() implements hypothesis testing procedures for parametric functional forms of and nonparametric shape restrictions on the regression function. binspwc() implements hypothesis testing procedures for pairwise group comparison of binscatter estimators. binsregselect() implements data-driven procedures for selecting the number of bins for binscatter estimation. All the commands allow for covariate adjustment, smoothness restrictions and clustering.
Author: Matias D. Cattaneo, Richard K. Crump, Max H. Farrell, Yingjie Feng
Maintainer: Yingjie Feng <fengyingjiepku@gmail.com>

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