Title: Automate Package and Project Setup
Description: Automate package and project setup tasks that are
otherwise performed manually. This includes setting up unit testing,
test coverage, continuous integration, Git, 'GitHub', licenses,
'Rcpp', 'RStudio' projects, and more.
Author: Hadley Wickham [aut] (<https://orcid.org/0000-0003-4757-117X>),
Jennifer Bryan [aut, cre] (<https://orcid.org/0000-0002-6983-2759>),
Malcolm Barrett [aut] (<https://orcid.org/0000-0003-0299-5825>),
RStudio [cph, fnd]
Maintainer: Jennifer Bryan <jenny@rstudio.com>
Diff between usethis versions 2.1.3 dated 2021-10-27 and 2.1.5 dated 2021-12-09
DESCRIPTION | 14 ++++--- MD5 | 61 +++++++++++++++++----------------- NAMESPACE | 1 NEWS.md | 13 ++++++- R/code-of-conduct.R | 1 R/course.R | 14 +++---- R/create.R | 4 +- R/data-table.R | 2 - R/edit.R | 14 +++++++ R/git-default-branch.R | 10 +++-- R/github-actions.R | 1 R/github.R | 4 +- R/github_token.R | 2 - R/logo.R | 4 +- R/package.R | 2 - R/pkgdown.R | 32 +++++++++-------- R/roxygen.R | 2 - R/tidyverse.R | 1 R/utils-git.R | 4 +- R/utils-github.R | 38 +++++++++++---------- README.md | 18 +++++----- inst/WORDLIST | 1 man/create_from_github.Rd | 4 +- man/edit.Rd | 5 ++ man/github-token.Rd | 2 - man/use_course_details.Rd | 8 ++-- man/use_github.Rd | 4 +- man/zip-utils.Rd | 4 +- tests/testthat/_snaps/utils-github.md |only tests/testthat/test-course.R | 16 ++++---- tests/testthat/test-pkgdown.R | 10 ++++- tests/testthat/test-utils-github.R | 1 32 files changed, 174 insertions(+), 123 deletions(-)
Title: Scelestial: Steiner Tree Based Single-Cell Lineage Tree
Inference
Description: Scelestial infers a lineage tree from single-cell DNA mutation matrix.
It generates a tree with approximately maximum parsimony through
a Steiner tree approximation algorithm.
Author: Mohammad Hadi Foroughmand Araabi [aut, cre],
Sama Goliaei [aut, ctb],
Alice McHardy [ctb]
Maintainer: Mohammad Hadi Foroughmand Araabi <foroughmand@gmail.com>
Diff between RScelestial versions 1.0.2 dated 2021-11-05 and 1.0.3 dated 2021-12-09
DESCRIPTION | 12 - MD5 | 20 - NEWS.md | 5 R/scelestial.R | 6 build/vignette.rds |binary inst/doc/RScelestial-vignette.R | 32 +++ inst/doc/RScelestial-vignette.Rmd | 44 ++++ inst/doc/RScelestial-vignette.html | 328 ++++++++++++++++--------------- man/as.ten.state.matrix.from.node.seq.Rd | 2 src/RcppExports.cpp | 5 vignettes/RScelestial-vignette.Rmd | 44 ++++ 11 files changed, 328 insertions(+), 170 deletions(-)
Title: Miscellaneous Functions for Panel Data, Quantiles, and Printing
Results
Description: These are miscellaneous functions for working with panel data, quantiles, and printing results. For panel data, the package includes functions for making a panel data balanced (that is, dropping missing individuals that have missing observations in any time period), converting id numbers to row numbers, and to treat repeated cross sections as panel data under the assumption of rank invariance. For quantiles, there are functions to make distribution functions from a set of data points (this is particularly useful when a distribution function is created in several steps), to combine distribution functions based on some external weights, and to invert distribution functions. Finally, there are several other miscellaneous functions for obtaining weighted means, weighted distribution functions, and weighted quantiles; to generate summary statistics and their differences for two groups; and to add or drop covariates from formulas.
Author: Brantly Callaway [aut, cre]
Maintainer: Brantly Callaway <brantly.callaway@uga.edu>
Diff between BMisc versions 1.4.2 dated 2020-12-18 and 1.4.3 dated 2021-12-09
DESCRIPTION | 17 ++++++------ MD5 | 24 +++++++++++------ NAMESPACE | 5 +++ NEWS.md | 10 +++++++ R/BMisc.R | 60 +++++++++++++++++++++++++++++++++++--------- R/RcppExports.R |only R/imports.R | 2 + README.md | 32 +++++++++++++++-------- man/TorF.Rd |only man/combineDfs.Rd | 4 ++ man/multiplier_bootstrap.Rd |only man/panel2cs2.Rd | 9 ++++-- man/source_all.Rd |only src |only tests |only 15 files changed, 121 insertions(+), 42 deletions(-)
Title: Simulate Joint Distribution
Description: Simulate multivariate correlated data given nonparametric marginals and their joint structure characterized by a Pearson or Spearman correlation matrix. The simulator engages the problem from a purely computational perspective. It assumes no statistical models such as copulas or parametric distributions, and can approximate the target correlations regardless of theoretical feasibility. The algorithm integrates and advances the Iman-Conover (1982) approach <doi:10.1080/03610918208812265> and the Ruscio-Kaczetow iteration (2008) <doi:10.1080/00273170802285693>. Package functions are carefully implemented in C++ for squeezing computing speed, suitable for large input in a manycore environment. Precision of the approximation and computing speed both substantially outperform various CRAN packages to date. Benchmarks are detailed in function examples. A simple heuristic algorithm is additionally designed to optimize the joint distribution in the post-simulation stage. The heuristic demonstrated good potential of achieving the same level of precision of approximation without the enhanced Iman-Conover-Ruscio-Kaczetow. The package contains a copy of Permuted Congruential Generator from <https://www.pcg-random.org>.
Author: Charlie Wusuo Liu
Maintainer: Charlie Wusuo Liu <liuwusuo@gmail.com>
Diff between SimJoint versions 0.3.7 dated 2020-04-14 and 0.3.9 dated 2021-12-09
DESCRIPTION | 9 ++++----- MD5 | 20 ++++++++++---------- build/vignette.rds |binary inst/NEWS.Rd | 6 ++++++ inst/doc/SimulatedJointDistribution.pdf |binary inst/doc/SimulatedJointDistribution.pdf.asis | 2 +- man/SJpearson.Rd | 2 +- man/SJpearsonPMF.Rd | 2 +- src/RcppExports.cpp | 5 +++++ src/pcg/pcg_random.hpp | 5 ++++- vignettes/SimulatedJointDistribution.pdf.asis | 2 +- 11 files changed, 33 insertions(+), 20 deletions(-)
Title: Combining Tree-Boosting with Gaussian Process and Mixed Effects
Models
Description: An R package that allows for combining tree-boosting with Gaussian process and mixed effects models. It also allows for independently doing tree-boosting as well as inference and prediction for Gaussian process and mixed effects models. See <https://github.com/fabsig/GPBoost> for more information on the software and Sigrist (2020) <arXiv:2004.02653> and Sigrist (2021) <arXiv:2105.08966> for more information on the methodology.
Author: Fabio Sigrist [aut, cre],
Benoit Jacob [cph],
Gael Guennebaud [cph],
Nicolas Carre [cph],
Pierre Zoppitelli [cph],
Gauthier Brun [cph],
Jean Ceccato [cph],
Jitse Niesen [cph],
Other authors of Eigen for the included version of Eigen [ctb, cph],
Timothy A. Davis [cph],
Guolin Ke [ctb],
Damien Soukhavong [ctb],
James Lamb [ctb],
Other authors of LightGBM for the included version of LightGBM [ctb],
Microsoft Corporation [cph],
Dropbox, Inc. [cph],
Jay Loden [cph],
Dave Daeschler [cph],
Giampaolo Rodola [cph],
Alberto Ferreira [ctb],
Daniel Lemire [ctb],
Victor Zverovich [cph],
IBM Corporation [ctb],
Keith O'Hara [cph],
Stephen L. Moshier [cph]
Maintainer: Fabio Sigrist <fabiosigrist@gmail.com>
Diff between gpboost versions 0.6.7 dated 2021-08-17 and 0.7.0 dated 2021-12-09
DESCRIPTION | 8 MD5 | 40 - R/GPModel.R | 36 - R/gpb.cv.R | 10 README.md | 19 configure.ac | 2 demo/generalized_linear_Gaussian_process_mixed_effects_models.R | 2 demo/parameter_tuning.R | 76 +- man/GPModel_shared_params.Rd | 28 man/fit.GPModel.Rd | 28 man/fit.Rd | 28 man/fitGPModel.Rd | 28 src/include/GPBoost/likelihoods.h | 34 - src/include/GPBoost/re_model.h | 46 - src/include/GPBoost/re_model_template.h | 310 +++++----- src/include/LightGBM/c_api.h | 52 - tests/testthat/test_GPBoost_algorithm.R | 25 tests/testthat/test_GPBoost_algorithm_non_Gaussian_data.R | 31 - tests/testthat/test_GPModel_gaussian_process.R | 15 tests/testthat/test_GPModel_grouped_random_effects.R | 150 ++-- tests/testthat/test_GPModel_non_Gaussian_data.R | 71 +- 21 files changed, 558 insertions(+), 481 deletions(-)
Title: Epimed Solutions Collection for Data Editing, Analysis, and
Benchmark of Health Units
Description: Collection of functions related to benchmark with prediction models
for data analysis and editing of clinical and epidemiological data.
Author: Lunna Borges [aut, cre]
Maintainer: Lunna Borges <lunna.borges@epimedsolutions.com>
Diff between ems versions 1.3.10 dated 2021-03-10 and 1.3.11 dated 2021-12-09
DESCRIPTION | 8 +- MD5 | 34 ++++----- NEWS | 8 ++ R/SRU.R | 4 - R/calcurve.R | 4 - R/icu.R | 2 R/tableStack.R | 4 - man/SMR.Rd | 72 +++++++++++++------- man/SRU.Rd | 53 +++++++++++--- man/breastCancer.Rd | 4 - man/calcurve.Rd | 40 ++++++++--- man/dataquality.Rd | 77 +++++++++++++++------ man/funnel.Rd | 179 +++++++++++++++++++++++++++++++++++++++----------- man/icu.Rd | 6 + man/miscellaneous.Rd | 34 +++++++-- man/mortality_rate.Rd | 12 ++- man/reclass.Rd | 46 ++++++++---- man/tableStack.Rd | 42 ++++++++--- 18 files changed, 454 insertions(+), 175 deletions(-)
Title: QTL Analysis in Autopolyploid Bi-Parental F1 Populations
Description: Quantitative trait loci (QTL) analysis and exploration of meiotic patterns in
autopolyploid bi-parental F1 populations.
For all ploidy levels, identity-by-descent (IBD) probabilities can be estimated.
Significance thresholds, exploring QTL allele effects and visualising results are provided.
For more background and to reference the package see <doi:10.1093/bioinformatics/btab574>.
Author: Peter Bourke [aut, cre],
Christine Hackett [ctb],
Chris Maliepaard [ctb],
Geert van Geest [ctb],
Roeland Voorrips [ctb],
Johan Willemsen [ctb]
Maintainer: Peter Bourke <pbourkey@gmail.com>
Diff between polyqtlR versions 0.0.6 dated 2021-06-23 and 0.0.7 dated 2021-12-09
polyqtlR-0.0.6/polyqtlR/man/NettletonDoerge.Rd |only polyqtlR-0.0.6/polyqtlR/man/Nstates.fun.Rd |only polyqtlR-0.0.6/polyqtlR/man/TM.biv.2.Rd |only polyqtlR-0.0.6/polyqtlR/man/TM.biv.4.Rd |only polyqtlR-0.0.6/polyqtlR/man/TM.biv.6.Rd |only polyqtlR-0.0.6/polyqtlR/man/TM.hex.Rd |only polyqtlR-0.0.6/polyqtlR/man/TM.quad.Rd |only polyqtlR-0.0.6/polyqtlR/man/TMfun.2x_B.Rd |only polyqtlR-0.0.6/polyqtlR/man/TMfun.3x_BB.Rd |only polyqtlR-0.0.6/polyqtlR/man/TMfun.3x_QB.Rd |only polyqtlR-0.0.6/polyqtlR/man/TMfun.4x_BB.Rd |only polyqtlR-0.0.6/polyqtlR/man/TMfun.4x_BQ.Rd |only polyqtlR-0.0.6/polyqtlR/man/TMfun.4x_QB.Rd |only polyqtlR-0.0.6/polyqtlR/man/TMfun.4x_QQ.Rd |only polyqtlR-0.0.6/polyqtlR/man/TMfun.6x_BB.Rd |only polyqtlR-0.0.6/polyqtlR/man/TMfun.6x_BH.Rd |only polyqtlR-0.0.6/polyqtlR/man/TMfun.6x_HB.Rd |only polyqtlR-0.0.6/polyqtlR/man/TMfun.6x_HH.Rd |only polyqtlR-0.0.6/polyqtlR/man/bivTM.Rd |only polyqtlR-0.0.6/polyqtlR/man/colour.bar.Rd |only polyqtlR-0.0.6/polyqtlR/man/fast_IBD.Rd |only polyqtlR-0.0.6/polyqtlR/man/fast_permute.Rd |only polyqtlR-0.0.6/polyqtlR/man/findQTLpeaks.Rd |only polyqtlR-0.0.6/polyqtlR/man/hexTM.Rd |only polyqtlR-0.0.6/polyqtlR/man/hmm_IBD.Rd |only polyqtlR-0.0.6/polyqtlR/man/list.depth.Rd |only polyqtlR-0.0.6/polyqtlR/man/mapseq.Rd |only polyqtlR-0.0.6/polyqtlR/man/probgeno_df_to_array.Rd |only polyqtlR-0.0.6/polyqtlR/man/quadTM.Rd |only polyqtlR-0.0.6/polyqtlR/man/state_fun.Rd |only polyqtlR-0.0.6/polyqtlR/man/test_IBD_list.Rd |only polyqtlR-0.0.6/polyqtlR/man/test_dosage_matrix.Rd |only polyqtlR-0.0.6/polyqtlR/man/test_probgeno_df.Rd |only polyqtlR-0.0.6/polyqtlR/man/weighted.var.Rd |only polyqtlR-0.0.6/polyqtlR/man/write.logheader.Rd |only polyqtlR-0.0.7/polyqtlR/DESCRIPTION | 12 polyqtlR-0.0.7/polyqtlR/MD5 | 68 +--- polyqtlR-0.0.7/polyqtlR/NAMESPACE | 2 polyqtlR-0.0.7/polyqtlR/R/accessory_functions.R | 41 ++ polyqtlR-0.0.7/polyqtlR/R/polyqtlR_functions.R | 231 +++++++++++++--- polyqtlR-0.0.7/polyqtlR/inst/doc/polyqtlR_vignette.R | 113 +++++-- polyqtlR-0.0.7/polyqtlR/inst/doc/polyqtlR_vignette.html | 149 +++++----- polyqtlR-0.0.7/polyqtlR/inst/doc/polyqtlR_vignette.rmd | 107 +++++-- polyqtlR-0.0.7/polyqtlR/man/impute_dosages.Rd | 6 polyqtlR-0.0.7/polyqtlR/man/maxL_IBD.Rd |only polyqtlR-0.0.7/polyqtlR/man/meiosis_report.Rd | 11 polyqtlR-0.0.7/polyqtlR/man/plotLinearQTL.Rd | 4 polyqtlR-0.0.7/polyqtlR/man/plotLinearQTL_list.Rd | 3 polyqtlR-0.0.7/polyqtlR/man/spline_IBD.Rd | 5 polyqtlR-0.0.7/polyqtlR/src/RcppExports.cpp | 5 polyqtlR-0.0.7/polyqtlR/vignettes/bibliography.bib | 18 + polyqtlR-0.0.7/polyqtlR/vignettes/error_dosages.RDS |only polyqtlR-0.0.7/polyqtlR/vignettes/new_dosages.RDS |only polyqtlR-0.0.7/polyqtlR/vignettes/polyqtlR_vignette.rmd | 107 +++++-- 54 files changed, 594 insertions(+), 288 deletions(-)
Title: Joint Feature Screening via Sparse MLE
Description: Feature screening is a powerful tool in processing ultrahigh dimensional data. It attempts to screen out most irrelevant features in preparation for a more elaborate analysis. Xu and Chen (2014)<doi:10.1080/01621459.2013.879531> proposed an effective screening method SMLE, which naturally incorporates the joint effects among features in the screening process. This package provides an efficient implementation of SMLE-screening for high-dimensional linear, logistic, and Poisson models. The package also provides a function for conducting accurate post-screening feature selection based on an iterative hard-thresholding procedure and a user-specified selection criterion.
Author: Qianxiang Zang [aut, cre],
Chen Xu [aut],
Kelly Burkett [aut],
Maintainer: Qianxiang Zang <qzang023@uottawa.ca>
Diff between SMLE versions 2.0-1 dated 2021-10-01 and 2.0-2 dated 2021-12-09
SMLE-2.0-1/SMLE/R/ctg_fit.R |only SMLE-2.0-2/SMLE/DESCRIPTION | 6 SMLE-2.0-2/SMLE/MD5 | 55 +-- SMLE-2.0-2/SMLE/R/Gen_Data.R | 74 ++-- SMLE-2.0-2/SMLE/R/SMLE.R | 583 +++++++++++++++++++++++++++------- SMLE-2.0-2/SMLE/R/coef.R | 111 +++++- SMLE-2.0-2/SMLE/R/ebicc.r | 42 ++ SMLE-2.0-2/SMLE/R/logLik.R | 103 ++---- SMLE-2.0-2/SMLE/R/plot.selection.R | 19 - SMLE-2.0-2/SMLE/R/plot.smle.R | 51 +- SMLE-2.0-2/SMLE/R/predict.R | 206 ++++-------- SMLE-2.0-2/SMLE/R/print.R | 53 ++- SMLE-2.0-2/SMLE/R/smle_select.R | 109 +++--- SMLE-2.0-2/SMLE/R/summary.R | 24 - SMLE-2.0-2/SMLE/R/synSNP.R | 2 SMLE-2.0-2/SMLE/R/ult.R | 3 SMLE-2.0-2/SMLE/R/vote.R | 6 SMLE-2.0-2/SMLE/data/synSNP.rda |binary SMLE-2.0-2/SMLE/man/Gen_Data.Rd | 237 ++++++------- SMLE-2.0-2/SMLE/man/SMLE-package.Rd | 4 SMLE-2.0-2/SMLE/man/SMLE.Rd | 104 +++--- SMLE-2.0-2/SMLE/man/coef.Rd | 12 SMLE-2.0-2/SMLE/man/logLik.Rd | 4 SMLE-2.0-2/SMLE/man/plot.selection.Rd | 56 +-- SMLE-2.0-2/SMLE/man/plot.smle.Rd | 80 ++-- SMLE-2.0-2/SMLE/man/predict.Rd | 94 ++--- SMLE-2.0-2/SMLE/man/smle_select.Rd | 45 +- SMLE-2.0-2/SMLE/man/synSNP.Rd | 2 SMLE-2.0-2/SMLE/man/vote_update.Rd | 77 ++-- 29 files changed, 1299 insertions(+), 863 deletions(-)
Title: Calculates Demographic Indicators
Description: Calculates key indicators such as fertility rates (Total Fertility Rate (TFR), General Fertility Rate (GFR),
and Age Specific Fertility Rate (ASFR)) using Demographic and Health Survey (DHS) women/individual data,
childhood mortality probabilities and rates such as Neonatal Mortality Rate (NNMR), Post-neonatal Mortality Rate (PNNMR),
Infant Mortality Rate (IMR), Child Mortality Rate (CMR), and Under-five Mortality Rate (U5MR), and adult mortality indicators
such as the Age Specific Mortality Rate (ASMR), Age Adjusted Mortality Rate (AAMR), Age Specific Maternal Mortality Rate (ASMMR),
Age Adjusted Maternal Mortality Rate (AAMMR), Age Specific Pregnancy Related Mortality Rate (ASPRMR),
Age Adjusted Pregnancy Related Mortality Rate (AAPRMR), Maternal Mortality Ratio (MMR) and Pregnancy Related Mortality Ratio (PRMR).
In addition to the indicators, the 'DHS.rates' package estimates sampling errors indicators such as Standard Error (SE),
Design Effect (DEFT), Relative Standard Error (RSE) and Confidence Interval (CI).
The package is developed according to the DHS methodology of calculating the fertility indicators and
the childhood mortality rates outlined in the
"Guide to DHS Statistics" (Croft, Trevor N., Aileen M. J. Marshall, Courtney K. Allen, et al. 2018, <https://dhsprogram.com/Data/Guide-to-DHS-Statistics/index.cfm>)
and the DHS methodology of estimating the sampling errors indicators outlined in
the "DHS Sampling and Household Listing Manual" (ICF International 2012, <https://dhsprogram.com/pubs/pdf/DHSM4/DHS6_Sampling_Manual_Sept2012_DHSM4.pdf>).
Author: Mahmoud Elkasabi
Maintainer: Mahmoud Elkasabi <mahmoud.elkasabi@icf.com>
Diff between DHS.rates versions 0.9.0 dated 2021-06-18 and 0.9.1 dated 2021-12-09
DESCRIPTION | 8 - MD5 | 20 +-- R/AAMMR.R | 13 +- R/AAMR.R | 11 +- R/AAPRMR.R | 15 +- R/ASMMR.R | 11 +- R/ASMR.R | 12 +- R/ASPRMR.R | 11 +- R/MMR.R | 10 - R/PRMR.R | 10 - inst/doc/DHS.rates.html | 255 +++++------------------------------------------- 11 files changed, 102 insertions(+), 274 deletions(-)
Title: Visualise and Explore the Deep Dependencies of R Packages
Description: Provides tools for exploration of R package dependencies.
The main deepdep() function allows to acquire deep dependencies of any package and plot them in an elegant way.
It also adds some popularity measures for the packages e.g. in the form of download count through the 'cranlogs' package.
Uses the CRAN metadata database <http://crandb.r-pkg.org> and Bioconductor metadata <http://bioconductor.org>.
Other data acquire functions are: get_dependencies(), get_downloads() and get_description().
The deepdep_shiny() function runs shiny application that helps to produce a nice 'deepdep' plot.
Author: Dominik Rafacz [aut, cre] (<https://orcid.org/0000-0003-0925-1909>),
Hubert Baniecki [aut],
Szymon Maksymiuk [aut],
Laura Bakala [aut],
Dirk Eddelbuettel [ctb]
Maintainer: Dominik Rafacz <dominikrafacz@gmail.com>
Diff between deepdep versions 0.2.5.4 dated 2021-11-16 and 0.3.0 dated 2021-12-09
DESCRIPTION | 12 MD5 | 49 NEWS.md | 4 R/get_dependencies.R | 33 R/plot_deepdep.R | 26 inst/WORDLIST | 30 inst/doc/deepdep-comparison.Rmd | 2 inst/doc/deepdep-comparison.html | 4 inst/doc/deepdep-package.Rmd | 36 inst/doc/deepdep-package.html | 48 man/get_dependencies.Rd | 9 man/plot_deepdep.Rd | 7 tests/fixtures/deepdep-1.yml | 2286 ++++++++++++++-------------- tests/fixtures/deepdep-2.yml | 6 tests/fixtures/plot-1.yml | 178 +- tests/fixtures/plot-2.yml | 6 tests/testthat/test-deepdep.R | 8 tests/testthat/test-match_dependency_type.R |only vignettes/deepdep-comparison.Rmd | 2 vignettes/deepdep-package.Rmd | 36 vignettes/plot_dependencies1-1.png |binary vignettes/plot_dependencies1-2.png |binary vignettes/plot_dependencies2-1.png |binary vignettes/plot_dependencies3-1.png |binary vignettes/plot_dependencies4-1.png |binary vignettes/plot_dependencies5-1.png |binary 26 files changed, 1443 insertions(+), 1339 deletions(-)
Title: Power in a Group Sequential Design
Description: Tools for the evaluation of interim analysis plans for sequentially
monitored trials on a survival endpoint; tools to construct efficacy and
futility boundaries, for deriving power of a sequential design at a specified
alternative, template for evaluating the performance of candidate plans at a
set of time varying alternatives. See Izmirlian, G. (2014) <doi:10.4310/SII.2014.v7.n1.a4>.
Author: Grant Izmirlian <izmirlig@mail.nih.gov>
Maintainer: Grant Izmirlian <izmirlig@mail.nih.gov>
Diff between PwrGSD versions 2.3.3 dated 2021-01-27 and 2.3.5 dated 2021-12-09
DESCRIPTION | 6 ++-- MD5 | 12 ++++---- R/PwrGSD.R | 57 ++++++++++++++++++++++++++++++--------- build/vignette.rds |binary inst/doc/GrpSeqBnds-vignette.pdf |binary inst/doc/PwrGSD-vignette.pdf |binary inst/doc/cpd-PwrGSD-vignette.pdf |binary 7 files changed, 54 insertions(+), 21 deletions(-)
Title: Find Tools Needed to Build R Packages
Description: Provides functions used to build R packages. Locates compilers
needed to build R packages on various platforms and ensures the PATH is
configured appropriately so R can use them.
Author: Hadley Wickham [aut],
Jim Hester [aut],
Gábor Csárdi [aut, cre],
RStudio [cph]
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>
Diff between pkgbuild versions 1.2.1 dated 2021-11-30 and 1.3.0 dated 2021-12-09
DESCRIPTION | 8 +++---- MD5 | 18 ++++++++--------- NEWS.md | 14 +++++++++++-- R/build.R | 20 +++++++++++++++---- R/callback.R | 7 ++++++ R/compiler-flags.R | 54 ++++++++++++++++++++++++++++++---------------------- R/rcmd.R | 21 +++++++++++++++----- R/rtools-metadata.R | 7 +++++- R/rtools.R | 46 +++++++++++++++++++++++++++++++++++--------- man/build.Rd | 9 ++++++-- 10 files changed, 146 insertions(+), 58 deletions(-)
Title: Sequential Monte Carlo Methods for 'nimble'
Description: Includes five particle filtering algorithms for use with state space
models in the 'nimble' system: 'Auxiliary', 'Bootstrap', 'Ensemble Kalman filter',
'Iterated Filtering 2', and 'Liu-West', as described in Michaud et al. (2021),
<doi:10.18637/jss.v100.i03>. A full User Manual is available at
<https://r-nimble.org>.
Author: Nick Michaud [aut],
Perry de Valpine [aut],
Christopher Paciorek [aut, cre],
Daniel Turek [aut],
Benjamin R. Goldstein [ctb] (packaging contributions),
Dao Nguyen [ctb] (contributions to the IF2 code),
The Regents of the University of California [cph]
Maintainer: Christopher Paciorek <paciorek@stat.berkeley.edu>
Diff between nimbleSMC versions 0.10.0 dated 2020-11-09 and 0.10.1 dated 2021-12-09
DESCRIPTION | 17 +- LICENSE | 2 MD5 | 40 +++--- NAMESPACE | 1 R/AuxiliaryFilter.R | 33 +++-- R/BootstrapFilter.R | 27 ++-- R/IF2Filter.R | 34 +++-- R/LiuWestFilter.R | 153 ++++++++++++-------------- R/utils.R | 1 inst/CITATION | 39 ++++-- inst/COPYRIGHTS | 2 inst/NEWS | 16 ++ inst/test-utils/filteringTestLog_Correct.Rout | 9 - man/buildAuxiliaryFilter.Rd | 19 +-- man/buildBootstrapFilter.Rd | 18 +-- man/buildEnsembleKF.Rd | 18 +-- man/buildIteratedFilter2.Rd | 35 +++-- man/buildLiuWestFilter.Rd | 17 +- man/samplers.Rd | 8 - tests/testthat/filteringTestLog.Rout | 9 - tests/testthat/test-filtering.R | 36 +++--- 21 files changed, 285 insertions(+), 249 deletions(-)
Title: 'ATAforecasting' Modelling Interface for 'fable' Framework
Description: Allows ATA (Automatic Time series analysis using the Ata method) models from the 'ATAforecasting' package to be used in a tidy workflow with the modeling interface of
'fabletools'. This extends 'ATAforecasting' to provide enhanced model specification and management, performance evaluation methods, and
model combination tools. 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).
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>
Diff between fable.ata versions 0.0.2 dated 2021-11-17 and 0.0.3 dated 2021-12-09
DESCRIPTION | 13 +++++++------ MD5 | 8 ++++---- NAMESPACE | 2 ++ R/fable.ata-package.R | 3 ++- R/fable_ata.R | 23 +++++++++++++++-------- 5 files changed, 30 insertions(+), 19 deletions(-)
Title: Analysis of Coarsely Observed Data
Description: Functions to analyze coarse data.
Specifically, it contains functions to (1) fit parametric accelerated
failure time models to interval-censored survival time data, and (2)
estimate the case-fatality ratio in scenarios with under-reporting.
This package's development was motivated by applications to infectious
disease: in particular, problems with estimating the incubation period and
the case fatality ratio of a given disease. Sample data files are included
in the package. See Reich et al. (2009) <doi:10.1002/sim.3659>,
Reich et al. (2012) <doi:10.1111/j.1541-0420.2011.01709.x>, and
Lessler et al. (2009) <doi:10.1016/S1473-3099(09)70069-6>.
Author: Nicholas G. Reich [aut, cre],
Justin Lessler [aut],
Andrew Azman [aut],
Zhian N. Kamvar [ctb]
Maintainer: Nicholas G. Reich <nick@umass.edu>
Diff between coarseDataTools versions 0.6-5 dated 2019-12-06 and 0.6-6 dated 2021-12-09
coarseDataTools-0.6-5/coarseDataTools/inst/doc/CFR_vignette.Rnw |only coarseDataTools-0.6-5/coarseDataTools/inst/doc/CFR_vignette.pdf |only coarseDataTools-0.6-5/coarseDataTools/man/plot-methods.Rd |only coarseDataTools-0.6-5/coarseDataTools/vignettes/CFR_vignette.Rnw |only coarseDataTools-0.6-6/coarseDataTools/ChangeLog | 4 coarseDataTools-0.6-6/coarseDataTools/DESCRIPTION | 20 ++- coarseDataTools-0.6-6/coarseDataTools/MD5 | 49 ++++---- coarseDataTools-0.6-6/coarseDataTools/NAMESPACE | 2 coarseDataTools-0.6-6/coarseDataTools/R/S4stuff.R | 56 ---------- coarseDataTools-0.6-6/coarseDataTools/R/coarseDataTools-package.R | 3 coarseDataTools-0.6-6/coarseDataTools/R/dic.fit.R | 2 coarseDataTools-0.6-6/coarseDataTools/README.md | 1 coarseDataTools-0.6-6/coarseDataTools/build/vignette.rds |binary coarseDataTools-0.6-6/coarseDataTools/inst/CITATION | 2 coarseDataTools-0.6-6/coarseDataTools/inst/doc/CFR_vignette.R | 39 +----- coarseDataTools-0.6-6/coarseDataTools/inst/doc/CFR_vignette.Rmd |only coarseDataTools-0.6-6/coarseDataTools/inst/doc/CFR_vignette.html |only coarseDataTools-0.6-6/coarseDataTools/man/dic.fit.Rd | 17 ++- coarseDataTools-0.6-6/coarseDataTools/man/dic.fit.mcmc.Rd | 16 ++ coarseDataTools-0.6-6/coarseDataTools/man/exp.win.lengths.Rd | 6 - coarseDataTools-0.6-6/coarseDataTools/man/fluA.inc.per.Rd | 6 - coarseDataTools-0.6-6/coarseDataTools/man/logLik-methods.Rd | 1 coarseDataTools-0.6-6/coarseDataTools/man/mcmc.erlang.Rd | 12 +- coarseDataTools-0.6-6/coarseDataTools/man/nycH1N1.Rd | 6 - coarseDataTools-0.6-6/coarseDataTools/man/precision.simulation.Rd | 26 +++- coarseDataTools-0.6-6/coarseDataTools/man/simulated.outbreak.deaths.Rd | 6 - coarseDataTools-0.6-6/coarseDataTools/vignettes/CFR_vignette.Rmd |only coarseDataTools-0.6-6/coarseDataTools/vignettes/CFR_vignette_cache |only 28 files changed, 125 insertions(+), 149 deletions(-)
More information about coarseDataTools at CRAN
Permanent link
Title: LncRNA Identification and Analysis Using Heterologous Features
Description: Long non-coding RNAs identification and analysis. Default models are trained with human, mouse and wheat datasets by employing SVM. Features are based on intrinsic composition of sequence, EIIP value (electron-ion interaction pseudopotential), and secondary structure. This package can also extract other classic features and build new classifiers. Reference: Han SY., Liang YC., Li Y., et al. (2018) <doi:10.1093/bib/bby065>.
Author: Siyu HAN [aut, cre],
Ying LI [aut],
Yanchun LIANG [aut]
Maintainer: Siyu HAN <hansy15@mails.jlu.edu.cn>
Diff between LncFinder versions 1.1.4 dated 2020-07-01 and 1.1.5 dated 2021-12-09
DESCRIPTION | 10 +++++----- MD5 | 14 +++++++------- NEWS.md | 14 ++++++++++---- R/LncFinder.R | 31 +++++++++++++++++++++---------- README.md | 2 +- inst/CITATION | 2 +- man/build_model.Rd | 5 ++++- man/svm_tune.Rd | 8 ++++++-- 8 files changed, 55 insertions(+), 31 deletions(-)
Title: Extract Text from Rich Text Format (RTF) Documents
Description: Wraps the 'unrtf' utility to extract text from RTF files. Supports
document conversion to HTML, LaTeX or plain text. Output in HTML is recommended
because 'unrtf' has limited support for converting between character encodings.
Author: Jeroen Ooms [aut, cre],
Free Software Foundation, Inc [cph]
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>
Diff between unrtf versions 1.4 dated 2020-01-13 and 1.4.1 dated 2021-12-09
DESCRIPTION | 12 ++++++------ MD5 | 6 +++--- NEWS | 3 +++ src/Makevars | 7 +++++-- 4 files changed, 17 insertions(+), 11 deletions(-)
Title: Supplementary Item Response Theory Models
Description: Supplementary functions for item response models aiming
to complement existing R packages. The functionality includes among others
multidimensional compensatory and noncompensatory IRT models
(Reckase, 2009, <doi:10.1007/978-0-387-89976-3>),
MCMC for hierarchical IRT models and testlet models
(Fox, 2010, <doi:10.1007/978-1-4419-0742-4>),
NOHARM (McDonald, 1982, <doi:10.1177/014662168200600402>),
Rasch copula model (Braeken, 2011, <doi:10.1007/s11336-010-9190-4>;
Schroeders, Robitzsch & Schipolowski, 2014, <doi:10.1111/jedm.12054>),
faceted and hierarchical rater models (DeCarlo, Kim & Johnson, 2011,
<doi:10.1111/j.1745-3984.2011.00143.x>),
ordinal IRT model (ISOP; Scheiblechner, 1995, <doi:10.1007/BF02301417>),
DETECT statistic (Stout, Habing, Douglas & Kim, 1996,
<doi:10.1177/014662169602000403>), local structural equation modeling
(LSEM; Hildebrandt, Luedtke, Robitzsch, Sommer & Wilhelm, 2016,
<doi:10.1080/00273171.2016.1142856>).
Author: Alexander Robitzsch [aut,cre] (<https://orcid.org/0000-0002-8226-3132>)
Maintainer: Alexander Robitzsch <robitzsch@ipn.uni-kiel.de>
Diff between sirt versions 3.10-118 dated 2021-09-23 and 3.11-21 dated 2021-12-09
DESCRIPTION | 10 +-- MD5 | 68 ++++++++++++------------- R/RcppExports.R | 2 R/equating.rasch.R | 4 - R/linking.haberman.R | 8 +- R/linking_haberman_als.R | 14 ++--- R/linking_haberman_als_vcov.R | 29 ++++++---- R/linking_haberman_vcov_transformation.R | 10 ++- R/lsem.estimate.R | 21 ++++--- R/lsem_bootstrap_draw_bootstrap_sample.R | 4 - R/lsem_fitsem.R | 9 ++- R/lsem_fitsem_compute_sufficient_statistics.R | 12 ++-- R/lsem_fitsem_joint_estimation.R | 4 - R/lsem_fitsem_raw_data_define_pseudo_weights.R | 2 R/lsem_fitsem_raw_data_lavaan.R | 4 - R/lsem_residualize.R | 4 - R/lsem_weighted_cov.R | 45 ++++++++++++++-- R/lsem_weighted_mean.R | 26 ++++++++- R/summary.lsem.R | 8 +- R/xxirt.R | 4 - build/partial.rdb |binary data/data.lsem02.rda |only data/data.lsem03.rda |only data/datalist | 2 inst/NEWS | 16 +++++ man/brm.sim.Rd | 5 + man/btm.Rd | 4 - man/data.lsem.Rd | 54 ++++++++++++++++++- man/data.si.Rd | 12 ++-- man/invariance.alignment.Rd | 12 ++-- man/linking.haberman.Rd | 8 +- man/linking.haebara.Rd | 8 +- man/lsem.estimate.Rd | 13 ++-- man/rasch.mml.Rd | 4 - man/tetrachoric2.Rd | 4 - src/RcppExports.cpp | 2 36 files changed, 291 insertions(+), 141 deletions(-)
Title: Geographically Weighted Partial Correlation Mapper
Description: An interactive mapping tool for geographically weighted correlation and partial correlation. Geographically weighted partial correlation coefficients are calculated following (Percival and Tsutsumida, 2017)<doi:10.1553/giscience2017_01_s36> and are described in greater detail in (Tsutsumida et al., 2019)<doi:10.5194/ica-abs-1-372-2019> and (Percival et al., 2021)<arXiv:2101.03491>.
Author: Joseph Emile Honour Percival [aut, cre]
(<https://orcid.org/0000-0001-5941-4601>),
Narumasa Tsutsumida [aut] (<https://orcid.org/0000-0002-6333-0301>)
Maintainer: Joseph Emile Honour Percival <ipercival@gmail.com>
Diff between gwpcormapper versions 0.1.2 dated 2021-04-06 and 0.1.3 dated 2021-12-09
DESCRIPTION | 6 +++--- MD5 | 10 +++++----- NEWS.md | 5 +++++ R/app_server.R | 2 ++ src/RcppExports.cpp | 5 +++++ tests/test_algorithm.R | 5 +++-- 6 files changed, 23 insertions(+), 10 deletions(-)
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 1.16 dated 2021-10-11 and 1.17 dated 2021-12-09
DESCRIPTION | 8 ++++---- MD5 | 14 +++++++------- NEWS | 4 ++++ R/CCbiclustAnthropo.R | 2 +- R/array3Dlandm.R | 2 +- build/partial.rdb |binary inst/doc/Anthropometry.pdf |binary man/Anthropometry-package.Rd | 4 ++-- 8 files changed, 19 insertions(+), 15 deletions(-)
Title: Continuous Time Meta-Analysis ('CoTiMA')
Description: The 'CoTiMA' package performs meta-analyses of correlation matrices of repeatedly measured variables taken from
studies that used different time intervals. Different time intervals between measurement occasions impose problems for
meta-analyses because the effects (e.g. cross-lagged effects) cannot be simply aggregated, for example, by means of common
fixed or random effects analysis. However, continuous time math, which is applied in 'CoTiMA', can be used to extrapolate or
intrapolate the results from all studies to any desired time lag. By this, effects obtained in studies that used different
time intervals can be meta-analyzed. 'CoTiMA' fits models to empirical data using the structural equation model (SEM) package
'ctsem', the effects specified in a SEM are related to parameters that are not directly included in the model (i.e.,
continuous time parameters; together, they represent the continuous time structural equation model, CTSEM). Statistical
model comparisons and significance tests are then performed on the continuous time parameter estimates. 'CoTiMA' also allows
analysis of publication bias (Egger's test, PET-PEESE estimates, zcurve analysis etc.) and analysis of statistical power
(post hoc power, required sample sizes). See Dormann, C., Guthier, C., & Cortina, J. M. (2019) <doi:10.1177/1094428119847277>.
and Guthier, C., Dormann, C., & Voelkle, M. C. (2020) <doi:10.1037/bul0000304>.
Author: Christian Dormann [aut, cph],
Markus Homberg [aut, com, cre],
Christina Guthier [ctb],
Manuel Voelkle [ctb]
Maintainer: Markus Homberg <cotima@uni-mainz.de>
Diff between CoTiMA versions 0.4.4 dated 2021-10-12 and 0.5.2 dated 2021-12-09
CoTiMA-0.4.4/CoTiMA/data/optimFit313.rda |only CoTiMA-0.4.4/CoTiMA/data/pubResults_6.rda |only CoTiMA-0.4.4/CoTiMA/man/optimFit313.Rd |only CoTiMA-0.4.4/CoTiMA/man/pubResults_6.Rd |only CoTiMA-0.5.2/CoTiMA/DESCRIPTION | 10 CoTiMA-0.5.2/CoTiMA/MD5 | 158 +++--- CoTiMA-0.5.2/CoTiMA/NAMESPACE | 1 CoTiMA-0.5.2/CoTiMA/R/ctmaAllInvFit.R | 2 CoTiMA-0.5.2/CoTiMA/R/ctmaEqual.R | 3 CoTiMA-0.5.2/CoTiMA/R/ctmaFit.R | 100 +++- CoTiMA-0.5.2/CoTiMA/R/ctmaInit.R | 172 ++++--- CoTiMA-0.5.2/CoTiMA/R/ctmaLabels.R | 10 CoTiMA-0.5.2/CoTiMA/R/ctmaOptimizeInit.R | 5 CoTiMA-0.5.2/CoTiMA/R/ctmaPlot.R | 62 ++ CoTiMA-0.5.2/CoTiMA/R/ctmaPower.R | 4 CoTiMA-0.5.2/CoTiMA/R/ctmaPrep.R | 13 CoTiMA-0.5.2/CoTiMA/R/ctmaSV.R | 331 +++++++------- CoTiMA-0.5.2/CoTiMA/R/data.R | 136 +++++ CoTiMA-0.5.2/CoTiMA/build/vignette.rds |binary CoTiMA-0.5.2/CoTiMA/data/A128.rda |binary CoTiMA-0.5.2/CoTiMA/data/A313.rda |binary CoTiMA-0.5.2/CoTiMA/data/CoTiMABiG_D_BO.rda |binary CoTiMA-0.5.2/CoTiMA/data/CoTiMAFullFit_3.rda |binary CoTiMA-0.5.2/CoTiMA/data/CoTiMAFullFit_6.rda |binary CoTiMA-0.5.2/CoTiMA/data/CoTiMAFullFit_6_new.rda |only CoTiMA-0.5.2/CoTiMA/data/CoTiMAFullInv23Fit_6.rda |binary CoTiMA-0.5.2/CoTiMA/data/CoTiMAFullInvEq23Fit_6.rda |binary CoTiMA-0.5.2/CoTiMA/data/CoTiMAInitFit_3.rda |binary CoTiMA-0.5.2/CoTiMA/data/CoTiMAInitFit_6.rda |binary CoTiMA-0.5.2/CoTiMA/data/CoTiMAInitFit_6_NUTS.rda |binary CoTiMA-0.5.2/CoTiMA/data/CoTiMAInitFit_6_new.rda |only CoTiMA-0.5.2/CoTiMA/data/CoTiMAInitFit_D_BO.rda |binary CoTiMA-0.5.2/CoTiMA/data/CoTiMAMod1onFullFit_6.rda |binary CoTiMA-0.5.2/CoTiMA/data/CoTiMAMod1onFullFit_6_cats12.rda |only CoTiMA-0.5.2/CoTiMA/data/CoTiMAMod2on23Fit_6.rda |binary CoTiMA-0.5.2/CoTiMA/data/CoTiMAPart134Inv3Fit_6.rda |binary CoTiMA-0.5.2/CoTiMA/data/CoTiMAPower_D_BO.rda |binary CoTiMA-0.5.2/CoTiMA/data/CoTiMAoptimFit313.rda |only CoTiMA-0.5.2/CoTiMA/data/CoTiMAstudyList_3.rda |binary CoTiMA-0.5.2/CoTiMA/data/CoTiMAstudyList_6.rda |binary CoTiMA-0.5.2/CoTiMA/data/CoTiMAstudyList_6_new.rda |only CoTiMA-0.5.2/CoTiMA/data/ageM201.rda |only CoTiMA-0.5.2/CoTiMA/data/ageSD201.rda |only CoTiMA-0.5.2/CoTiMA/data/burnout201.rda |only CoTiMA-0.5.2/CoTiMA/data/country201.rda |only CoTiMA-0.5.2/CoTiMA/data/delta_t201.rda |only CoTiMA-0.5.2/CoTiMA/data/demands201.rda |only CoTiMA-0.5.2/CoTiMA/data/empcov128.rda |binary CoTiMA-0.5.2/CoTiMA/data/empcov201.rda |only CoTiMA-0.5.2/CoTiMA/data/empcov32.rda |binary CoTiMA-0.5.2/CoTiMA/data/malePercent201.rda |only CoTiMA-0.5.2/CoTiMA/data/moderator201.rda |only CoTiMA-0.5.2/CoTiMA/data/occupation201.rda |only CoTiMA-0.5.2/CoTiMA/data/pubList_8.rda |binary CoTiMA-0.5.2/CoTiMA/data/rawdata128.txt |binary CoTiMA-0.5.2/CoTiMA/data/results128.rda |binary CoTiMA-0.5.2/CoTiMA/data/sampleSize201.rda |only CoTiMA-0.5.2/CoTiMA/data/source201.rda |only CoTiMA-0.5.2/CoTiMA/inst/doc/CoTiMA_User_Guide.pdf |binary CoTiMA-0.5.2/CoTiMA/man/CoTiMABiG_D_BO.Rd | 2 CoTiMA-0.5.2/CoTiMA/man/CoTiMAFullFit_3.Rd | 2 CoTiMA-0.5.2/CoTiMA/man/CoTiMAFullFit_6.Rd | 2 CoTiMA-0.5.2/CoTiMA/man/CoTiMAFullFit_6_new.Rd |only CoTiMA-0.5.2/CoTiMA/man/CoTiMAFullInv23Fit_6.Rd | 2 CoTiMA-0.5.2/CoTiMA/man/CoTiMAFullInvEq23Fit_6.Rd | 2 CoTiMA-0.5.2/CoTiMA/man/CoTiMAInitFit_3.Rd | 2 CoTiMA-0.5.2/CoTiMA/man/CoTiMAInitFit_6.Rd | 2 CoTiMA-0.5.2/CoTiMA/man/CoTiMAInitFit_6_NUTS.Rd | 2 CoTiMA-0.5.2/CoTiMA/man/CoTiMAInitFit_6_new.Rd |only CoTiMA-0.5.2/CoTiMA/man/CoTiMAInitFit_D_BO.Rd | 2 CoTiMA-0.5.2/CoTiMA/man/CoTiMAMod1onFullFit_6.Rd | 2 CoTiMA-0.5.2/CoTiMA/man/CoTiMAMod1onFullFit_6_cats12.Rd |only CoTiMA-0.5.2/CoTiMA/man/CoTiMAMod2on23Fit_6.Rd | 2 CoTiMA-0.5.2/CoTiMA/man/CoTiMAPart134Inv3Fit_6.Rd | 2 CoTiMA-0.5.2/CoTiMA/man/CoTiMAPower_D_BO.Rd | 2 CoTiMA-0.5.2/CoTiMA/man/CoTiMAoptimFit313.Rd |only CoTiMA-0.5.2/CoTiMA/man/CoTiMAstudyList_3.Rd | 10 CoTiMA-0.5.2/CoTiMA/man/CoTiMAstudyList_6_new.Rd |only CoTiMA-0.5.2/CoTiMA/man/ageM201.Rd |only CoTiMA-0.5.2/CoTiMA/man/ageSD201.Rd |only CoTiMA-0.5.2/CoTiMA/man/burnout201.Rd |only CoTiMA-0.5.2/CoTiMA/man/country201.Rd |only CoTiMA-0.5.2/CoTiMA/man/ctmaAllInvFit.Rd | 2 CoTiMA-0.5.2/CoTiMA/man/ctmaFit.Rd | 9 CoTiMA-0.5.2/CoTiMA/man/ctmaGetPub.Rd | 2 CoTiMA-0.5.2/CoTiMA/man/ctmaInit.Rd | 2 CoTiMA-0.5.2/CoTiMA/man/ctmaOptimizeInit.Rd | 4 CoTiMA-0.5.2/CoTiMA/man/ctmaPower.Rd | 4 CoTiMA-0.5.2/CoTiMA/man/ctmaPrep.Rd | 7 CoTiMA-0.5.2/CoTiMA/man/delta_t201.Rd |only CoTiMA-0.5.2/CoTiMA/man/demands201.Rd |only CoTiMA-0.5.2/CoTiMA/man/empcov201.Rd |only CoTiMA-0.5.2/CoTiMA/man/empcov32.Rd | 2 CoTiMA-0.5.2/CoTiMA/man/malePercent201.Rd |only CoTiMA-0.5.2/CoTiMA/man/moderator201.Rd |only CoTiMA-0.5.2/CoTiMA/man/occupation201.Rd |only CoTiMA-0.5.2/CoTiMA/man/pubList_8.Rd | 2 CoTiMA-0.5.2/CoTiMA/man/sampleSize201.Rd |only CoTiMA-0.5.2/CoTiMA/man/source201.Rd |only 99 files changed, 693 insertions(+), 384 deletions(-)
Title: Computation of Variance-Based Sensitivity Indices
Description: It allows to rapidly compute, bootstrap and plot up to fourth-order Sobol'-based sensitivity indices using several state-of-the-art first and total-order estimators. Sobol' indices can be computed either for models that yield a scalar as a model output or for systems of differential equations. The package also provides a suit of benchmark tests functions and several options to obtain publication-ready figures of the model output uncertainty and sensitivity-related analysis. An overview of Sobol'-based sensitivity indices can be found in Saltelli et al. (2008, ISBN:9780470059975) and in Puy, Lo Piano, Saltelli, and Levin (2021) <arXiv:2101.10103>.
Author: Arnald Puy [aut, cre] (<https://orcid.org/0000-0001-9469-2156>),
Bertrand Ioos [ctb] (Author of included 'sensitivity' fragments),
Gilles Pujol [ctb] (Author of included 'sensitivity' fragments),
RStudio [cph] (Copyright holder of included 'sensitivity' fragments)
Maintainer: Arnald Puy <arnald.puy@pm.me>
Diff between sensobol versions 1.0.3 dated 2021-07-24 and 1.1.0 dated 2021-12-09
DESCRIPTION | 14 +-- MD5 | 22 ++--- NEWS.md | 3 R/plot_sobol.R | 8 + R/sobol_indices.R | 140 ++++++++++++++++++++++++-------- R/sobol_matrices.R | 27 ++++-- README.md | 2 build/partial.rdb |binary inst/REFERENCES.bib | 68 --------------- inst/doc/sensobol.pdf |binary src/RcppExports.cpp | 5 + vignettes/REFERENCES.bib | 205 +++++++++++++++++------------------------------ 12 files changed, 237 insertions(+), 257 deletions(-)
Title: Forest Analysis with Airborne Laser Scanning (LiDAR) Data
Description: Provides functions for forest analysis using airborne laser scanning (LiDAR remote sensing) data: tree detection (method 1 in Eysn et al. (2015) <doi:10.3390/f6051721>) and segmentation; forest parameters estimation and mapping with the area-based approach. It includes complementary steps for forest mapping: co-registration of field plots with LiDAR data (Monnet and Mermin (2014) <doi:10.3390/f5092307>); extraction of both physical (gaps, edges, trees) and statistical features from LiDAR data useful for e.g. habitat suitability modeling (Glad et al. (2020) <doi:10.1002/rse2.117>); model calibration with ground reference, and maps export.
Author: Jean-Matthieu Monnet [aut, cre]
(<https://orcid.org/0000-0002-9948-9891>),
Pascal Obstétar [ctb] (<https://orcid.org/0000-0002-2811-7548>)
Maintainer: Jean-Matthieu Monnet <jean-matthieu.monnet@inrae.fr>
Diff between lidaRtRee versions 3.1.0 dated 2021-07-30 and 3.1.2 dated 2021-12-09
lidaRtRee-3.1.0/lidaRtRee/R/las_chablais3-data.R |only lidaRtRee-3.1.0/lidaRtRee/data/las_chablais3.rda |only lidaRtRee-3.1.2/lidaRtRee/DESCRIPTION | 19 ++--- lidaRtRee-3.1.2/lidaRtRee/MD5 | 34 ++++----- lidaRtRee-3.1.2/lidaRtRee/R/aba.R | 2 lidaRtRee-3.1.2/lidaRtRee/R/common.R | 26 ++++--- lidaRtRee-3.1.2/lidaRtRee/R/extdata.R |only lidaRtRee-3.1.2/lidaRtRee/R/metrics.R | 56 ++++++++-------- lidaRtRee-3.1.2/lidaRtRee/R/raster_metrics.R | 12 +++ lidaRtRee-3.1.2/lidaRtRee/build/partial.rdb |binary lidaRtRee-3.1.2/lidaRtRee/inst |only lidaRtRee-3.1.2/lidaRtRee/man/aba_metrics.Rd | 20 ++--- lidaRtRee-3.1.2/lidaRtRee/man/clouds_metrics.Rd | 6 + lidaRtRee-3.1.2/lidaRtRee/man/clouds_tree_metrics.Rd | 21 ++---- lidaRtRee-3.1.2/lidaRtRee/man/las_chablais3.Rd | 14 +--- lidaRtRee-3.1.2/lidaRtRee/man/points2DSM.Rd | 6 + lidaRtRee-3.1.2/lidaRtRee/man/points2DTM.Rd | 6 + lidaRtRee-3.1.2/lidaRtRee/man/terrain_points_metrics.Rd | 5 + lidaRtRee-3.1.2/lidaRtRee/tests/testthat/test_common.R | 10 ++ lidaRtRee-3.1.2/lidaRtRee/tests/testthat/test_metrics.R | 28 +++++--- 20 files changed, 154 insertions(+), 111 deletions(-)
Title: An Interface for Image Recognition
Description: Provides an interface for image recognition using the 'Google Vision API' <https://cloud.google.com/vision/> . Converts API data for features such as object detection and optical character recognition to data frames. The package also includes functions for analyzing image annotations.
Author: Carsten Schwemmer [aut, cre] (<https://orcid.org/0000-0001-9084-946X>)
Maintainer: Carsten Schwemmer <c.schwem2er@gmail.com>
Diff between imgrec versions 0.1.2 dated 2021-03-29 and 0.1.3 dated 2021-12-09
DESCRIPTION | 12 - MD5 | 22 +- NEWS.md | 5 R/parse_annotations.R | 5 R/zzz.R | 7 README.md | 28 +-- build/vignette.rds |binary inst/doc/intro.Rmd | 322 ++++++++++++++++++++-------------------- inst/doc/intro.html | 303 ++++++------------------------------- inst/doc/label_tweets.html | 277 +++++----------------------------- vignettes/file3e803f643761.html |only vignettes/file3e805d387f.html |only vignettes/intro.Rmd | 322 ++++++++++++++++++++-------------------- 13 files changed, 466 insertions(+), 837 deletions(-)
Title: Raster-Based Spatial Stratification Algorithms
Description: Algorithms for the spatial stratification of landscapes, sampling and modeling of
spatially-varying phenomena. These algorithms offer a simple framework for the stratification
of geographic space based on raster layers representing landscape factors and/or factor scales.
The stratification process follows a hierarchical approach, which is based on first level units
(i.e., classification units) and second-level units (i.e., stratification units). Nonparametric
techniques allow to measure the correspondence between the geographic space and the landscape
configuration represented by the units. These correspondence metrics are useful to define
sampling schemes and to model the spatial variability of environmental phenomena. The
theoretical background of the algorithms and code examples are presented in Fuentes, Dorantes,
and Tipton (2021). <doi:10.31223/X50S57>.
Author: Bryan A. Fuentes [aut, cre] (<https://orcid.org/0000-0003-3506-7101>),
Minerva J. Dorantes [aut] (<https://orcid.org/0000-0002-2877-832X>),
John R. Tipton [aut] (<https://orcid.org/0000-0002-6135-8141>),
Robert J. Hijmans [ctb] (<https://orcid.org/0000-0001-5872-2872>)
Maintainer: Bryan A. Fuentes <bryandrep@gmail.com>
Diff between rassta versions 1.0.1 dated 2021-10-14 and 1.0.2 dated 2021-12-09
rassta-1.0.1/rassta/R/somgap.r |only rassta-1.0.1/rassta/R/sompam.r |only rassta-1.0.1/rassta/inst/tinytest/test_sompam.R |only rassta-1.0.1/rassta/man/figures/rassta_cheatsheet.png |only rassta-1.0.1/rassta/man/somgap.Rd |only rassta-1.0.1/rassta/man/sompam.Rd |only rassta-1.0.2/rassta/DESCRIPTION | 48 +++++----- rassta-1.0.2/rassta/MD5 | 83 +++++++++++------- rassta-1.0.2/rassta/NAMESPACE | 4 rassta-1.0.2/rassta/NEWS.md | 5 + rassta-1.0.2/rassta/R/dummies.r | 11 +- rassta-1.0.2/rassta/R/engine.r | 49 +++++----- rassta-1.0.2/rassta/R/figure.r | 33 +++---- rassta-1.0.2/rassta/R/locations.r | 30 +++--- rassta-1.0.2/rassta/R/predict_functions.r | 24 ++--- rassta-1.0.2/rassta/R/select_functions.r | 18 ++- rassta-1.0.2/rassta/R/signature.r | 10 +- rassta-1.0.2/rassta/R/similarity.r | 19 ++-- rassta-1.0.2/rassta/R/som_gap.r |only rassta-1.0.2/rassta/R/som_pam.r |only rassta-1.0.2/rassta/R/strata.r | 14 +-- rassta-1.0.2/rassta/README.md | 23 +++- rassta-1.0.2/rassta/build/partial.rdb |binary rassta-1.0.2/rassta/build/vignette.rds |only rassta-1.0.2/rassta/inst/CITATION |only rassta-1.0.2/rassta/inst/doc |only rassta-1.0.2/rassta/inst/tinytest/test_som_pam.R |only rassta-1.0.2/rassta/man/dummies.Rd | 11 +- rassta-1.0.2/rassta/man/engine.Rd | 49 +++++----- rassta-1.0.2/rassta/man/figure.Rd | 11 +- rassta-1.0.2/rassta/man/locations.Rd | 30 +++--- rassta-1.0.2/rassta/man/predict_functions.Rd | 24 ++--- rassta-1.0.2/rassta/man/select_functions.Rd | 18 ++- rassta-1.0.2/rassta/man/signature.Rd | 10 +- rassta-1.0.2/rassta/man/similarity.Rd | 19 ++-- rassta-1.0.2/rassta/man/som_gap.Rd |only rassta-1.0.2/rassta/man/som_pam.Rd |only rassta-1.0.2/rassta/man/strata.Rd | 18 +-- rassta-1.0.2/rassta/vignettes |only 39 files changed, 307 insertions(+), 254 deletions(-)
Title: Visualizing and Analyzing Animal Track Data
Description: Contains functions to access movement data stored in 'movebank.org'
as well as tools to visualize and statistically analyze animal movement data,
among others functions to calculate dynamic Brownian Bridge Movement Models.
Move helps addressing movement ecology questions.
Author: Bart Kranstauber [aut, cre],
Marco Smolla [aut],
Anne K Scharf [aut]
Maintainer: Bart Kranstauber <b.kranstauber@uva.nl>
Diff between move versions 4.0.6 dated 2020-11-26 and 4.1.6 dated 2021-12-09
ChangeLog | 31 + DESCRIPTION | 10 MD5 | 68 +- NAMESPACE | 1 R/WebImport.R | 104 +++- R/brownianbridgedyn.R | 5 R/brownianmotionvariancedyn.R | 1 R/namesIndiv.R | 5 R/nindiv.R | 2 R/nlocs.R | 2 R/print.R | 2 R/timelag.R | 2 build/vignette.rds |binary inst/doc/browseMovebank.R | 28 - inst/doc/browseMovebank.Rmd | 30 - inst/doc/browseMovebank.html | 53 +- inst/doc/move.R | 126 ++--- inst/doc/move.Rmd | 130 ++--- inst/doc/move.html | 841 +++++++++++++++---------------------- man/emd.Rd | 2 man/getMovebank.Rd | 44 - man/getMovebankAnimals.Rd | 2 man/getMovebankData.Rd | 11 man/getMovebankID.Rd | 4 man/getMovebankLocationData.Rd | 4 man/getMovebankNonLocationData.Rd | 4 man/getMovebankSensorAttributes.Rd | 4 man/getMovebankSensors.Rd | 2 man/getMovebankStudy.Rd | 2 man/move.Rd | 2 man/movebankLogin.Rd | 2 tests/testthat/test.print.R | 6 tests/testthat/test.web.R | 30 - vignettes/browseMovebank.Rmd | 30 - vignettes/move.Rmd | 130 ++--- 35 files changed, 829 insertions(+), 891 deletions(-)
Title: Leadership-Inference Framework for Multivariate Time Series
Description: A leadership-inference framework for multivariate time series. The framework for multiple-faction-leadership inference from coordinated activities or 'mFLICA' uses a notion of a leader as an individual who initiates collective patterns that everyone in a group follows. Given a set of time series of individual activities, our goal is to identify periods of coordinated activity, find factions of coordination if more than one exist, as well as identify leaders of each faction. For each time step, the framework infers following relations between individual time series, then identifying a leader of each faction whom many individuals follow but it follows no one. A faction is defined as a group of individuals that everyone follows the same leader. 'mFLICA' reports following relations, leaders of factions, and members of each faction for each time step. Please see Chainarong Amornbunchornvej and Tanya Berger-Wolf (2018) <doi:10.1137/1.9781611975321.62> for methodology and Chainarong Amornbunchornvej (2021) <doi:10.1016/j.softx.2021.100781> for software when referring to this package in publications.
Author: Chainarong Amornbunchornvej [aut, cre]
(<https://orcid.org/0000-0003-3131-0370>)
Maintainer: Chainarong Amornbunchornvej <grandca@gmail.com>
Diff between mFLICA versions 0.1.3 dated 2021-09-17 and 0.1.4 dated 2021-12-09
mFLICA-0.1.3/mFLICA/inst/doc/mFLICA-SoftwareArticle.ltx |only mFLICA-0.1.3/mFLICA/inst/doc/mFLICA-SoftwareArticle.pdf |only mFLICA-0.1.3/mFLICA/vignettes/ChaiRef.bib |only mFLICA-0.1.3/mFLICA/vignettes/FIG |only mFLICA-0.1.3/mFLICA/vignettes/mFLICA-SoftwareArticle.ltx |only mFLICA-0.1.4/mFLICA/DESCRIPTION | 6 ++--- mFLICA-0.1.4/mFLICA/MD5 | 18 ++------------- mFLICA-0.1.4/mFLICA/NEWS.md | 2 + mFLICA-0.1.4/mFLICA/build/vignette.rds |binary 9 files changed, 8 insertions(+), 18 deletions(-)
Title: Exact Tests and Confidence Intervals for 2x2 Tables
Description: Calculates conditional exact tests (Fisher's exact test, Blaker's exact test, or exact McNemar's test) and unconditional exact tests (including score-based tests on differences in proportions, ratios of proportions, and odds ratios, and Boshcloo's test) with appropriate matching confidence intervals, and provides power and sample size calculations. Gives melded confidence intervals for the binomial case (Fay, et al, 2015, <DOI:10.1111/biom.12231>). Gives boundary-optimized rejection region test (Gabriel, et al, 2018, <DOI:10.1002/sim.7579>), an unconditional exact test for the situation where the controls are all expected to fail. Gives confidence intervals compatible with exact McNemar's or sign tests (Fay and Lumbard, 2021, <DOI:10.1002/sim.8829>). For review of these kinds of exact tests see Fay and Hunsberger (2021, <DOI:10.1214/21-SS131>).
Author: Michael P. Fay [aut, cre],
Sally A. Hunsberger [ctb],
Martha Nason [ctb],
Erin Gabriel [ctb],
Keith Lumbard [ctb]
Maintainer: Michael P. Fay <mfay@niaid.nih.gov>
Diff between exact2x2 versions 1.6.5 dated 2020-08-03 and 1.6.6 dated 2021-12-09
ChangeLog | 4 ++++ DESCRIPTION | 10 +++++----- MD5 | 26 +++++++++++++------------- R/power2x2.R | 20 ++++++++++++++------ build/vignette.rds |binary inst/CITATION | 9 ++++++--- inst/doc/exact2x2.pdf |binary inst/doc/exact2x2Validation.pdf |binary inst/doc/exactMcNemar.pdf |binary inst/doc/midpAdjustment.pdf |binary inst/doc/unconditionalExact2x2Tests.pdf |binary man/exact2x2-package.Rd | 11 ++++++----- man/mcnemarExactDP.Rd | 4 ++-- man/uncondExact2x2.Rd | 4 ++++ 14 files changed, 54 insertions(+), 34 deletions(-)
Title: Non-Ordered Vectors
Description: Functionality for manipulating values of associative
maps. Ordinary R vectors are unsuitable for working with values of
associative maps because elements of an R vector may be accessed by
reference to their location in the vector, but associative maps are
stored in arbitrary order. However, when associating keys with
values one needs both parts to be in 1-1 correspondence, so one
cannot dispense with the order entirely. The 'disordR' package
includes a single S4 class, disord. This class allows one to
perform only those operations appropriate for manipulating values of
associative maps and prevents any other operation (such as accessing
an element at a particular location). A useful heuristic is that
one is only allowed to access or modify a disord object using a
python list comprehension. The idea is to prevent ill-defined
operations on values (or keys) of associative maps, whose order is
undefined or at best implementation-specific, while allowing and
facilitating sensible operations. The package is needed for
development versions of 'mvp', 'hyper2', 'spray', 'clifford', and
'freealg'.
Author: Robin K. S. Hankin [aut, cre] (<https://orcid.org/0000-0001-5982-0415>)
Maintainer: Robin K. S. Hankin <hankin.robin@gmail.com>
Diff between disordR versions 0.0-8 dated 2021-10-16 and 0.0-9 dated 2021-12-09
DESCRIPTION | 6 +++--- MD5 | 14 ++++++++------ NAMESPACE | 2 ++ NEWS.md |only R/disordR.R | 23 +++++++++++++++++++++++ build/vignette.rds |binary inst/doc/disordR.html | 40 ++++++++++++++++++++-------------------- man/summary.Rd |only tests/testthat/test_aaa.R | 10 ++++++++++ 9 files changed, 66 insertions(+), 29 deletions(-)
Title: Temporal Sensory Data Analysis
Description: Analysis and visualization of data from temporal sensory methods, including for temporal check-all-that-apply (TCATA) and temporal dominance of sensations (TDS).
Author: J.C. Castura [aut, cre, ctb] (<https://orcid.org/0000-0002-1640-833X>)
Maintainer: J.C. Castura <jcastura@compusense.com>
Diff between tempR versions 0.9.9.18 dated 2021-10-10 and 0.9.9.19 dated 2021-12-09
DESCRIPTION | 12 +-- MD5 | 17 ++-- NAMESPACE | 1 R/tcata.R | 180 ++++++++++++++++++++++++++++++++++++------------- R/tds.R | 4 - build/partial.rdb |binary man/citation.counts.Rd |only man/get.decluttered.Rd | 28 +++---- man/tcata.diff.plot.Rd | 2 man/tcata.line.plot.Rd | 54 ++++++-------- 10 files changed, 192 insertions(+), 106 deletions(-)
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2014-04-30 1.1-23
2013-10-10 1.0-7
2012-07-25 1.0-3
2012-07-20 1.0-2
2012-04-01 1.0-0
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2021-01-27 1.1.0
2020-01-10 1.0.0
2018-11-01 0.1.3
2018-05-23 0.1.2
2018-05-10 0.1.1
2018-04-24 0.1.0
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2020-07-31 1.0.5
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2021-10-05 1.8.6
2021-03-18 1.8.5
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2015-01-13 0.2
2014-10-10 0.1