Title: Array Operations for Arrays of Mismatching Sizes
Description: Support for implicit expansion of arrays in operations involving
arrays of mismatching sizes. This pattern is known as "broadcasting" in
'Python' and "implicit expansion" in 'Matlab' and is explained for example in
the article "Array programming with NumPy" by C. R. Harris et al. (2020)
<doi:10.1038/s41586-020-2649-2>.
Author: Manuel Hentschel [aut, cre]
Maintainer: Manuel Hentschel <Manuel.Hentschel@unige.ch>
Diff between implicitExpansion versions 0.0.1 dated 2022-09-13 and 0.1.0 dated 2022-10-02
DESCRIPTION | 6 - MD5 | 16 ++--- NAMESPACE | 9 ++ R/binaryOperators.R | 60 +++++++++++++++++++ R/implicitExpansion.R | 149 ++++++++++++++++++++++++++----------------------- man/BinaryOperators.Rd | 29 +++++++++ man/expandArray.Rd | 2 man/expandedDim.Rd | 4 - man/mmapply.Rd | 21 +++++- 9 files changed, 210 insertions(+), 86 deletions(-)
More information about implicitExpansion at CRAN
Permanent link
Title: Download Geographic Data
Description: Functions for downloading of geographic data for use in spatial analysis and mapping. The package facilitates access to climate, elevation, land use, soil, species occurrence, accessibility, administrative boundaries and other data.
Author: Robert J. Hijmans [cre, aut], Aniruddha Ghosh [ctb], Alex Mandel [ctb]
Maintainer: Robert J. Hijmans <r.hijmans@gmail.com>
Diff between geodata versions 0.4-9 dated 2022-08-07 and 0.4-11 dated 2022-10-02
DESCRIPTION | 8 ++++---- MD5 | 16 ++++++++-------- R/gadm.R | 9 ++++++--- R/zzz.R | 2 +- build/partial.rdb |binary man/soil_af.Rd | 2 +- man/soil_af_elements.Rd | 4 ++-- man/soil_grids.Rd | 2 +- man/soil_grids_vsi.Rd | 2 +- 9 files changed, 24 insertions(+), 21 deletions(-)
Title: Create Datasets with Identical Summary Statistics
Description: Anscombe's quartet are a set of four two-variable datasets that
have several common summary statistics but which have very different joint
distributions. This becomes apparent when the data are plotted, which
illustrates the importance of using graphical displays in Statistics. This
package enables the creation of datasets that have identical marginal sample
means and sample variances, sample correlation, least squares regression
coefficients and coefficient of determination. The user supplies an initial
dataset, which is shifted, scaled and rotated in order to achieve target
summary statistics. The general shape of the initial dataset is retained.
The target statistics can be supplied directly or calculated based on a
user-supplied dataset. The 'datasauRus' package
<https://cran.r-project.org/package=datasauRus> provides further examples
of datasets that have markedly different scatter plots but share many
sample summary statistics.
Author: Paul J. Northrop [aut, cre, cph]
Maintainer: Paul J. Northrop <p.northrop@ucl.ac.uk>
Diff between anscombiser versions 1.0.0 dated 2020-10-11 and 1.1.0 dated 2022-10-02
anscombiser-1.0.0/anscombiser/R/anscombiser.R |only anscombiser-1.0.0/anscombiser/man/anscombiser.Rd |only anscombiser-1.1.0/anscombiser/DESCRIPTION | 16 anscombiser-1.1.0/anscombiser/MD5 | 62 + anscombiser-1.1.0/anscombiser/NAMESPACE | 2 anscombiser-1.1.0/anscombiser/NEWS.md |only anscombiser-1.1.0/anscombiser/R/anscombise.R | 59 + anscombiser-1.1.0/anscombiser/R/anscombise_gif.R |only anscombiser-1.1.0/anscombiser/R/anscombiser-internal.R | 20 anscombiser-1.1.0/anscombiser/R/anscombiser-package.R |only anscombiser-1.1.0/anscombiser/R/datasets.R |only anscombiser-1.1.0/anscombiser/R/mimic.R | 31 anscombiser-1.1.0/anscombiser/R/mimic_gif.R |only anscombiser-1.1.0/anscombiser/README.md | 23 anscombiser-1.1.0/anscombiser/build/partial.rdb |only anscombiser-1.1.0/anscombiser/build/vignette.rds |binary anscombiser-1.1.0/anscombiser/data/anscombe1.rda |only anscombiser-1.1.0/anscombiser/data/anscombe2.rda |only anscombiser-1.1.0/anscombiser/data/anscombe3.rda |only anscombiser-1.1.0/anscombiser/data/anscombe4.rda |only anscombiser-1.1.0/anscombiser/data/input1.rda |only anscombiser-1.1.0/anscombiser/data/input2.rda |only anscombiser-1.1.0/anscombiser/data/input3.rda |only anscombiser-1.1.0/anscombiser/data/input4.rda |only anscombiser-1.1.0/anscombiser/data/input5.rda |only anscombiser-1.1.0/anscombiser/data/input6.rda |only anscombiser-1.1.0/anscombiser/data/input7.rda |only anscombiser-1.1.0/anscombiser/data/input8.rda |only anscombiser-1.1.0/anscombiser/inst/doc/intro-to-anscombiser.R | 4 anscombiser-1.1.0/anscombiser/inst/doc/intro-to-anscombiser.Rmd | 12 anscombiser-1.1.0/anscombiser/inst/doc/intro-to-anscombiser.html | 377 ++++++---- anscombiser-1.1.0/anscombiser/man/anscombe.Rd |only anscombiser-1.1.0/anscombiser/man/anscombise.Rd | 56 + anscombiser-1.1.0/anscombiser/man/anscombise_gif.Rd |only anscombiser-1.1.0/anscombiser/man/anscombiser-internal.Rd | 5 anscombiser-1.1.0/anscombiser/man/anscombiser-package.Rd |only anscombiser-1.1.0/anscombiser/man/figures/README-trump-1.png |binary anscombiser-1.1.0/anscombiser/man/input_datasets.Rd |only anscombiser-1.1.0/anscombiser/man/mimic.Rd | 32 anscombiser-1.1.0/anscombiser/man/mimic_gif.Rd |only anscombiser-1.1.0/anscombiser/man/trump.Rd | 5 anscombiser-1.1.0/anscombiser/tests/testthat/test-anscombise.R | 58 + anscombiser-1.1.0/anscombiser/tests/testthat/test-mimic.R | 67 + anscombiser-1.1.0/anscombiser/vignettes/intro-to-anscombiser.Rmd | 12 anscombiser-1.1.0/anscombiser/vignettes/taylor-and-francis-chicago-author-date.csl |only 45 files changed, 628 insertions(+), 213 deletions(-)
Title: Curve Registration for Exponential Family Functional Data
Description: A method for performing joint registration and functional principal
component analysis for curves (functional data) that are generated from exponential family distributions. This
mainly implements the algorithms described in 'Wrobel et al. (2019)' <doi:10.1111/biom.12963> and further adapts them to potentially
incomplete curves where (some) curves are not observed from the beginning and/or until the end of the common domain. Curve registration
can be used to better understand patterns in functional data by separating curves into phase and amplitude variability.
This software handles both binary and continuous functional data, and is
especially applicable in accelerometry and wearable technology.
Author: Julia Wrobel [aut, cre] ,
Alexander Bauer [aut],
Erin McDonnell [aut],
Fabian Scheipl [ctb],
Jeff Goldsmith [aut]
Maintainer: Julia Wrobel <julia.wrobel@cuanschutz.edu>
Diff between registr versions 1.0.0 dated 2020-03-16 and 2.1.0 dated 2022-10-02
registr-1.0.0/registr/R/nhanes-data.R |only registr-1.0.0/registr/R/piecewise_parametric_hinv.R |only registr-1.0.0/registr/man/h_inv_parametric.Rd |only registr-1.0.0/registr/man/piecewise_parametric_hinv.Rd |only registr-2.1.0/registr/DESCRIPTION | 36 registr-2.1.0/registr/MD5 | 113 - registr-2.1.0/registr/NAMESPACE | 29 registr-2.1.0/registr/NEWS.md | 37 registr-2.1.0/registr/R/bfpca.R | 413 +++- registr-2.1.0/registr/R/bs_deriv.R | 8 registr-2.1.0/registr/R/constrOptim_helpers.R |only registr-2.1.0/registr/R/constraints.R | 43 registr-2.1.0/registr/R/data.R |only registr-2.1.0/registr/R/data_clean.R | 15 registr-2.1.0/registr/R/fpca_gauss.R | 509 ++++- registr-2.1.0/registr/R/gfpca_covHall.R |only registr-2.1.0/registr/R/gfpca_helpers.R |only registr-2.1.0/registr/R/gfpca_twoStep.R |only registr-2.1.0/registr/R/loss_h.R | 159 + registr-2.1.0/registr/R/loss_h_gradient.R | 111 - registr-2.1.0/registr/R/plot.fpca.R |only registr-2.1.0/registr/R/register_fpca.R | 394 +++- registr-2.1.0/registr/R/registr-utils.R |only registr-2.1.0/registr/R/registr.R | 889 ++++++++-- registr-2.1.0/registr/R/simulate_functional_data.R | 2 registr-2.1.0/registr/R/simulate_unregistered_curves.R | 2 registr-2.1.0/registr/README.md | 109 - registr-2.1.0/registr/build/vignette.rds |binary registr-2.1.0/registr/data/growth_incomplete.rda |only registr-2.1.0/registr/inst/doc/incomplete_curves.R |only registr-2.1.0/registr/inst/doc/incomplete_curves.Rmd |only registr-2.1.0/registr/inst/doc/incomplete_curves.html |only registr-2.1.0/registr/inst/doc/registr.R | 290 ++- registr-2.1.0/registr/inst/doc/registr.Rmd | 505 ++++- registr-2.1.0/registr/inst/doc/registr.html | 777 +++++++- registr-2.1.0/registr/man/bfpca.Rd | 73 registr-2.1.0/registr/man/bfpca_argPreparation.Rd |only registr-2.1.0/registr/man/bfpca_optimization.Rd |only registr-2.1.0/registr/man/bs_deriv.Rd | 2 registr-2.1.0/registr/man/coarsen_index.Rd |only registr-2.1.0/registr/man/constraints.Rd | 11 registr-2.1.0/registr/man/cov_hall.Rd |only registr-2.1.0/registr/man/crossprods_irregular.Rd |only registr-2.1.0/registr/man/crossprods_regular.Rd |only registr-2.1.0/registr/man/data_clean.Rd | 4 registr-2.1.0/registr/man/deriv.inv.logit.Rd |only registr-2.1.0/registr/man/determine_npc.Rd |only registr-2.1.0/registr/man/ensure_proper_beta.Rd |only registr-2.1.0/registr/man/fpca_gauss.Rd | 67 registr-2.1.0/registr/man/fpca_gauss_argPreparation.Rd |only registr-2.1.0/registr/man/fpca_gauss_optimization.Rd |only registr-2.1.0/registr/man/gfpca_twoStep.Rd |only registr-2.1.0/registr/man/growth_incomplete.Rd |only registr-2.1.0/registr/man/initial_params.Rd |only registr-2.1.0/registr/man/loss_h.Rd | 52 registr-2.1.0/registr/man/loss_h_gradient.Rd | 46 registr-2.1.0/registr/man/nhanes.Rd | 8 registr-2.1.0/registr/man/piecewise_linear2_hinv.Rd |only registr-2.1.0/registr/man/plot.fpca.Rd |only registr-2.1.0/registr/man/register_fpca.Rd | 236 ++ registr-2.1.0/registr/man/registr.Rd | 173 + registr-2.1.0/registr/man/registr_oneCurve.Rd |only registr-2.1.0/registr/man/simulate_functional_data.Rd | 2 registr-2.1.0/registr/man/simulate_unregistered_curves.Rd | 2 registr-2.1.0/registr/src/Makevars | 4 registr-2.1.0/registr/src/RcppExports.cpp | 5 registr-2.1.0/registr/tests/testthat/test-bfpca.R | 124 + registr-2.1.0/registr/tests/testthat/test-constrOptim_helpers.R |only registr-2.1.0/registr/tests/testthat/test-fpca_gauss.R | 87 registr-2.1.0/registr/tests/testthat/test-gfpca_twoStep.R |only registr-2.1.0/registr/tests/testthat/test-plot_fpca.R |only registr-2.1.0/registr/tests/testthat/test-register_fpca.R | 251 ++ registr-2.1.0/registr/tests/testthat/test-registr.R | 165 + registr-2.1.0/registr/vignettes/incomplete_curves.Rmd |only registr-2.1.0/registr/vignettes/references.bib |only registr-2.1.0/registr/vignettes/registr.Rmd | 505 ++++- 76 files changed, 5015 insertions(+), 1243 deletions(-)
Title: Version-Control for CRAN, GitHub, and GitLab Packages
Description: Make R scripts reproducible, by ensuring that
every time a given script is run, the same version of the used packages are
loaded (instead of whichever version the user running the script happens to
have installed). This is achieved by using the command
groundhog.library() instead of the base command library(), and including a
date in the call. The date is used to call on the same version of the
package every time (the most recent version available at that date).
Load packages from CRAN, GitHub, or Gitlab.
Author: Uri Simonsohn [aut, cre] ,
Hugo Gruson [ctb, aut]
Maintainer: Uri Simonsohn <urisohn@gmail.com>
Diff between groundhog versions 2.0.1 dated 2022-08-06 and 2.1.0 dated 2022-10-02
DESCRIPTION | 6 +++--- MD5 | 10 +++++----- R/localize.R | 3 ++- inst/cran.times.rds |binary inst/cran.toc.rds |binary inst/missing.mran.dates.rds |binary 6 files changed, 10 insertions(+), 9 deletions(-)
Title: Covariate Assisted Spectral Clustering on Ratios of Eigenvectors
Description: Functions for the novel algorithm CASCORE, proposed to detect the latent community structure in graphs with node covariates. The models we can handle include covariate assisted degree corrected stochastic block model (CADCSBM). CASCORE allows for the disagreement between the community structure revealed in the adjacency information and the community structure revealed in the covariate information. More details are in the reference paper: Yaofang Hu and Wanjie Wang (2022) <arXiv:2208.00257>.
This package also includes other classical community detection algorithms that are compared to CASCORE in our paper, such as Spectral Clustering On Ratios-of Eigenvectors (SCORE), normalized PCA, ordinary PCA and covariate-assisted spectral clustering (CASC) and ADMM.
Author: Yaofang Hu [aut, cre],
Wanjie Wang [aut]
Maintainer: Yaofang Hu <yaofangh@smu.edu>
Diff between CASCORE versions 0.1.0 dated 2022-08-17 and 0.1.1 dated 2022-10-02
DESCRIPTION | 10 ++--- MD5 | 38 ++++++++++++++-------- NAMESPACE | 3 + R/ADMM.R |only R/Ac.R |only R/Acs.R |only R/CASC.R | 11 ++++-- R/CASCORE.R | 72 ++++++++++++++++-------------------------- R/Pinv.R |only R/SCORE.R | 8 ++-- R/cl2mat.R |only R/nPCA.R | 8 ++-- R/normalizeSym.R |only R/oPCA.R | 10 +++-- R/projAXb.R |only R/projSP.R |only R/rsc.R |only build |only man/ADMM.Rd |only man/CASC.Rd | 6 ++- man/CASCORE.Rd | 21 ++++++++---- man/SCORE.Rd | 7 +--- man/nPCA.Rd | 2 - man/oPCA.Rd | 4 +- tests/testthat/test-ADMM.R |only tests/testthat/test-CASCORE.R | 6 +-- 26 files changed, 111 insertions(+), 95 deletions(-)
Title: Posterior Predictive (PoP) Design for Phase I Clinical Trials
Description: The primary goal of phase I clinical trials is to find the maximum tolerated dose (MTD). To reach this objective, we introduce a new design for phase I clinical trials, the posterior predictive (PoP) design. The PoP design is an innovative model-assisted design that is as simply as the conventional algorithmic designs as its decision rules can be pre-tabulated prior to the onset of trial, but is of more flexibility of selecting diverse target toxicity rates and cohort sizes. The PoP design has desirable properties, such as coherence and consistency. Moreover, the PoP design provides better empirical performance than the BOIN and Keyboard design with respect to high average probabilities of choosing the MTD and slightly lower risk of treating patients at subtherapeutic or overly toxic doses.
Author: Chenqi Fu [aut],
Xinying Fang [aut, cre],
Shouhao Zhou [aut]
Maintainer: Xinying Fang <fxy950225@gmail.com>
Diff between PoPdesign versions 1.0.2 dated 2022-09-29 and 1.0.3 dated 2022-10-02
DESCRIPTION | 6 +++--- MD5 | 8 ++++---- inst/doc/vignette_for_PoP_design.Rmd | 8 +------- inst/doc/vignette_for_PoP_design.html | 24 ++++++++---------------- vignettes/vignette_for_PoP_design.Rmd | 8 +------- 5 files changed, 17 insertions(+), 37 deletions(-)
Title: Generalized Estimation Equation Solver
Description: Generalized Estimation Equation solver.
Author: Vincent J Carey [aut],
Thomas S Lumley [trl] ,
Cleve Moler [ctb] ,
Brian Ripley [trl, cre, ctb]
Maintainer: Brian Ripley <ripley@stats.ox.ac.uk>
Diff between gee versions 4.13-23 dated 2022-05-29 and 4.13-24 dated 2022-10-02
DESCRIPTION | 8 +-- MD5 | 6 +- src/ugee.c | 133 ++++++++++++++++++------------------------------------------ src/ugee.h | 64 +++++++++++++++------------- 4 files changed, 83 insertions(+), 128 deletions(-)
Title: Read, Plot and Analyse Output from the DEPONS Model
Description: Methods for analyzing population dynamics and movement tracks simulated using the DEPONS model <https://www.depons.eu>, and for manipulating input raster files and shipping routes.
Author: Jacob Nabe-Nielsen and Caitlin K. Frankish
Maintainer: Jacob Nabe-Nielsen <jnn@ecos.au.dk>
Diff between DEPONS2R versions 1.1.4 dated 2022-07-03 and 1.1.6 dated 2022-10-02
DEPONS2R-1.1.4/DEPONS2R/man/ais.to.DeponsShips.Rd |only DEPONS2R-1.1.6/DEPONS2R/DESCRIPTION | 6 DEPONS2R-1.1.6/DEPONS2R/MD5 | 21 DEPONS2R-1.1.6/DEPONS2R/NAMESPACE | 1 DEPONS2R-1.1.6/DEPONS2R/R/a-misc.R | 2 DEPONS2R-1.1.6/DEPONS2R/R/blockdyn-methods.R | 2 DEPONS2R-1.1.6/DEPONS2R/R/ships_methods.R | 472 ------------ DEPONS2R-1.1.6/DEPONS2R/build/partial.rdb |binary DEPONS2R-1.1.6/DEPONS2R/man/DeponsShips-class.Rd | 2 DEPONS2R-1.1.6/DEPONS2R/man/interpolate.ais.data.Rd | 2 DEPONS2R-1.1.6/DEPONS2R/man/read.DeponsShips.Rd | 3 DEPONS2R-1.1.6/DEPONS2R/tests/testthat/test_ships_methods.R | 36 12 files changed, 42 insertions(+), 505 deletions(-)
Title: NA Data Imputation Algorithms
Description: Creates a uniform interface for several advanced imputations missing data methods. Every available method can be used as a part of 'mlr3' pipelines which allows easy tuning and performance evaluation. Most of the used functions work separately on the training and test sets (imputation is trained on the training set and impute training data. After that imputation is again trained on the test set and impute test data).
Author: Jan Borowski, Piotr Fic
Maintainer: Jan Borowski <janborowka7@gmail.com>
Diff between NADIA versions 0.4.1 dated 2021-01-06 and 0.4.2 dated 2022-10-02
NADIA-0.4.1/NADIA/vignettes/Errors_Statistic_and_Handling_cache |only NADIA-0.4.2/NADIA/DESCRIPTION | 15 NADIA-0.4.2/NADIA/MD5 | 73 NADIA-0.4.2/NADIA/R/autotune_Amelia.R | 2 NADIA-0.4.2/NADIA/R/autotune_VIM_regrImp.R | 2 NADIA-0.4.2/NADIA/R/autotune_mice.R | 6 NADIA-0.4.2/NADIA/build/partial.rdb |binary NADIA-0.4.2/NADIA/build/vignette.rds |binary NADIA-0.4.2/NADIA/inst/doc/Errors_Statistic_and_Handling.Rmd | 2 NADIA-0.4.2/NADIA/inst/doc/Errors_Statistic_and_Handling.html | 327 ++- NADIA-0.4.2/NADIA/inst/doc/NADIA_examples_and_motivation.html | 836 +++++----- NADIA-0.4.2/NADIA/man/PipeOpAmelia.Rd | 31 NADIA-0.4.2/NADIA/man/PipeOpHist_B.Rd | 31 NADIA-0.4.2/NADIA/man/PipeOpMean_B.Rd | 31 NADIA-0.4.2/NADIA/man/PipeOpMedian_B.Rd | 31 NADIA-0.4.2/NADIA/man/PipeOpMice.Rd | 31 NADIA-0.4.2/NADIA/man/PipeOpMice_A.Rd | 31 NADIA-0.4.2/NADIA/man/PipeOpMode_B.Rd | 31 NADIA-0.4.2/NADIA/man/PipeOpOOR_B.Rd | 31 NADIA-0.4.2/NADIA/man/PipeOpSample_B.Rd | 31 NADIA-0.4.2/NADIA/man/PipeOpSimulateMissings.Rd | 31 NADIA-0.4.2/NADIA/man/PipeOpSoftImpute.Rd | 31 NADIA-0.4.2/NADIA/man/PipeOpVIM_HD.Rd | 31 NADIA-0.4.2/NADIA/man/PipeOpVIM_IRMI.Rd | 31 NADIA-0.4.2/NADIA/man/PipeOpVIM_kNN.Rd | 31 NADIA-0.4.2/NADIA/man/PipeOpVIM_regrImp.Rd | 31 NADIA-0.4.2/NADIA/man/PipeOpmissForest.Rd | 31 NADIA-0.4.2/NADIA/man/PipeOpmissMDA_MFA.Rd | 31 NADIA-0.4.2/NADIA/man/PipeOpmissMDA_MFA_A.Rd | 31 NADIA-0.4.2/NADIA/man/PipeOpmissMDA_PCA_MCA_FMAD.Rd | 31 NADIA-0.4.2/NADIA/man/PipeOpmissMDA_PCA_MCA_FMAD_A.Rd | 31 NADIA-0.4.2/NADIA/man/PipeOpmissRanger.Rd | 31 NADIA-0.4.2/NADIA/tests/testthat/test_A.R | 2 NADIA-0.4.2/NADIA/tests/testthat/test_autotune.R | 8 NADIA-0.4.2/NADIA/vignettes/Errors_Statistic_and_Handling.Rmd | 2 35 files changed, 1084 insertions(+), 842 deletions(-)
Title: Design Patterns in R
Description: Build robust and maintainable software with object-oriented
design patterns in R. Design patterns abstract and present in neat,
well-defined components and interfaces the experience of many software
designers and architects over many years of solving similar problems.
These are solutions that have withstood the test of time with respect
to re-usability, flexibility, and maintainability. 'R6P' provides
abstract base classes with examples for a few known design patterns.
The patterns were selected by their applicability to analytic projects
in R. Using these patterns in R projects have proven effective in
dealing with the complexity that data-driven applications possess.
Author: Harel Lustiger [aut, cre] ,
Tidylab [cph, fnd]
Maintainer: Harel Lustiger <tidylab@gmail.com>
Diff between R6P versions 0.2.2 dated 2021-08-03 and 0.3.0 dated 2022-10-02
DESCRIPTION | 50 +-- MD5 | 21 - R/base-NullObject.R | 9 R/base-Singleton.R | 6 R/base-ValueObject.R | 10 R/object_relational-Repository.R | 6 R/utils.R |only README.md | 53 +++ man/NullObject.Rd | 80 ++--- man/Repository.Rd | 82 ++---- man/Singleton.Rd | 40 -- man/ValueObject.Rd | 533 +++++++++++++++++++-------------------- 12 files changed, 452 insertions(+), 438 deletions(-)
Title: Machine Learning and Inference for Topological Data Analysis
Description: Topological data analysis is a powerful tool for finding non-linear global structure
in whole datasets. 'TDApplied' aims to bridge topological data analysis with data, statistical
and machine learning practitioners so that more analyses may benefit from the
power of topological data analysis. The main tool of topological data analysis is
persistent homology, which computes a shape descriptor of a dataset, called
a persistence diagram. There are three goals of this package: (1) convert persistence diagrams
computed using the two main R packages for topological data analysis into a data frame,
(2) implement fast versions of both distance and kernel calculations
for pairs of persistence diagrams, and (3) provide methods for machine learning
and inference for persistence diagrams which scale well.
Author: Shael Brown [aut, cre],
Dr. Reza Farivar [aut, fnd]
Maintainer: Shael Brown <shaelebrown@gmail.com>
Diff between TDApplied versions 0.1.2 dated 2022-09-26 and 0.1.3 dated 2022-10-02
DESCRIPTION | 6 - MD5 | 14 +-- NEWS.md | 5 + R/distance_calculations.R | 168 ++++++++++++++++++++++------------------- R/machine_learning.R | 29 ++----- build/partial.rdb |binary inst/doc/ML_and_Inference.html | 18 ++-- tests/testthat/test-MDS.R | 2 8 files changed, 130 insertions(+), 112 deletions(-)
Title: Semisupervised Document Scaling by Word-Embedding Models
Description: A word embeddings-based semisupervised model for document scaling Watanabe (2020) <doi:10.1080/19312458.2020.1832976>.
LSS allows users to analyze large and complex corpora on arbitrary dimensions with seed words exploiting efficiency of word embeddings (SVD, Glove).
It can generate word vectors on a users-provided corpus or incorporate a pre-trained word vectors.
Author: Kohei Watanabe [aut, cre, cph]
Maintainer: Kohei Watanabe <watanabe.kohei@gmail.com>
Diff between LSX versions 1.1.1 dated 2022-02-26 and 1.1.2 dated 2022-10-02
DESCRIPTION | 9 +++----- MD5 | 12 +++++----- NEWS.md | 8 +++++++ R/textmodel.R | 19 +++++++++-------- build/partial.rdb |binary man/textmodel_lss.Rd | 53 ------------------------------------------------ man/textstat_context.Rd | 4 +-- 7 files changed, 30 insertions(+), 75 deletions(-)
Title: A Simple and Robust JSON Parser and Generator for R
Description: A reasonably fast JSON parser and generator, optimized for statistical
data and the web. Offers simple, flexible tools for working with JSON in R, and
is particularly powerful for building pipelines and interacting with a web API.
The implementation is based on the mapping described in the vignette (Ooms, 2014).
In addition to converting JSON data from/to R objects, 'jsonlite' contains
functions to stream, validate, and prettify JSON data. The unit tests included
with the package verify that all edge cases are encoded and decoded consistently
for use with dynamic data in systems and applications.
Author: Jeroen Ooms [aut, cre] ,
Duncan Temple Lang [ctb],
Lloyd Hilaiel [cph]
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>
Diff between jsonlite versions 1.8.1 dated 2022-10-01 and 1.8.2 dated 2022-10-02
DESCRIPTION | 6 +++--- MD5 | 10 +++++----- NEWS | 3 +++ R/asJSON.Date.R | 2 +- inst/doc/json-aaquickstart.html | 2 +- inst/doc/json-mapping.pdf |binary 6 files changed, 13 insertions(+), 10 deletions(-)
Title: Machine Learning Model Evaluation for 'h2o' Package
Description: Several functions are provided that simplify using 'h2o'
package. Currently, a function for extracting the AutoML
model parameter is provided, alongside a function for computing
F-Measure statistics at any given threshold. For more information
about 'h2o' package see <https://h2o.ai/>.
Author: E. F. Haghish [aut, cre, cph]
Maintainer: E. F. Haghish <haghish@uio.no>
Diff between h2otools versions 0.0.1 dated 2022-09-07 and 0.1 dated 2022-10-02
DESCRIPTION | 6 +- MD5 | 19 +++++--- NAMESPACE | 20 +++++---- R/Fmeasure.R | 4 - R/automlModelParam.R | 4 - R/checkFrame.R |only R/performance.R | 54 ++++++++++++++++++++----- README.md | 19 +++++++- man/Fmeasure.Rd | 102 ++++++++++++++++++++++++------------------------ man/automlModelParam.Rd | 80 ++++++++++++++++++------------------- man/checkFrame.Rd |only man/performance.Rd |only 12 files changed, 179 insertions(+), 129 deletions(-)
Title: Fit, Simulate and Diagnose Exponential-Family Models for
Networks
Description: An integrated set of tools to analyze and simulate networks based on exponential-family random graph models (ERGMs). 'ergm' is a part of the Statnet suite of packages for network analysis. See Hunter, Handcock, Butts, Goodreau, and Morris (2008) <doi:10.18637/jss.v024.i03> and Krivitsky, Hunter, Morris, and Klumb (2021) <arXiv:2106.04997>.
Author: Mark S. Handcock [aut],
David R. Hunter [aut],
Carter T. Butts [aut],
Steven M. Goodreau [aut],
Pavel N. Krivitsky [aut, cre] ,
Martina Morris [aut],
Li Wang [ctb],
Kirk Li [ctb],
Skye Bender-deMoll [ctb],
Chad Klumb [ctb],
Michal Bojanowski [ctb] ,
[...truncated...]
Maintainer: Pavel N. Krivitsky <pavel@statnet.org>
Diff between ergm versions 4.2.2 dated 2022-06-01 and 4.2.3 dated 2022-10-02
BUGS | 12 + DESCRIPTION | 19 +- LICENSE | 1 MD5 | 204 +++++++++++++++--------------- NAMESPACE | 3 R/InitErgmConstraint.blockdiag.R | 10 - R/InitErgmConstraint.hints.R | 2 R/InitErgmTerm.R | 44 +++--- R/InitErgmTerm.operator.R | 1 R/anova.ergm.R | 13 - R/anova.ergmlist.R | 8 - R/check.ErgmTerm.R | 12 - R/control.logLik.ergm.R | 2 R/data.R | 8 - R/ergm-package.R | 7 - R/ergm-terms-index.R | 5 R/ergm.R | 3 R/ergm.getMCMCsample.R | 4 R/ergm.utility.R | 31 ++-- R/ergmMPLE.R | 2 R/ergm_model.R | 3 R/ergm_proposal.R | 2 R/ergm_state.R | 21 +-- R/is.inCH.R | 44 +++++- R/parallel.utils.R | 25 ++- R/rlebdm.R | 28 ++-- R/simulate.ergm.R | 7 + R/zzz.R | 5 build/ergm.pdf |binary build/vignette.rds |binary inst/CITATION | 4 inst/NEWS.Rd | 71 ++++++++++ inst/doc/Terms-API.html | 13 + inst/doc/ergm-term-crossRef.html | 77 ++++++----- inst/doc/ergm.Rmd | 2 inst/doc/ergm.pdf |binary inst/doc/nodal_attributes.html | 17 +- inst/include/ergm_MHstorage.h | 2 man/Sum-operator-ergmTerm.Rd | 1 man/altkstar-ergmTerm.Rd | 4 man/anova.ergm.Rd | 7 - man/asymmetric-ergmTerm.Rd | 4 man/b1star-ergmTerm.Rd | 2 man/b1starmix-ergmTerm.Rd | 12 - man/b2star-ergmTerm.Rd | 2 man/b2starmix-ergmTerm.Rd | 4 man/blockdiag-ergmConstraint.Rd | 6 man/control.ergm.Rd | 11 - man/control.ergm.bridge.Rd | 5 man/degreedist.Rd | 4 man/dyadcov-ergmTerm.Rd | 13 + man/edgecov-ergmTerm.Rd | 13 + man/ergm-deprecated.Rd | 16 +- man/ergm-errors.Rd | 4 man/ergm-package.Rd | 7 - man/ergm-parallel.Rd | 4 man/ergm.Rd | 12 - man/ergm.bridge.llr.Rd | 2 man/ergm.estfun.Rd | 10 - man/ergm.godfather.Rd | 2 man/ergm.mple.Rd | 2 man/ergmMPLE.Rd | 4 man/ergm_MCMC_sample.Rd | 2 man/ergm_SAN_slave.Rd | 2 man/ergm_model.Rd | 13 + man/ergm_proposal.Rd | 14 +- man/ergm_state.Rd | 30 ++-- man/ergm_state_cache.Rd | 12 - man/ergm_symmetrize.Rd | 6 man/ergmlhs.Rd | 10 - man/faux.mesa.high.Rd | 2 man/florentine.Rd | 6 man/gof.Rd | 15 +- man/is.inCH.Rd | 2 man/is.valued.Rd | 10 - man/kstar-ergmTerm.Rd | 2 man/logLik.ergm.Rd | 8 - man/logLikNull.Rd | 4 man/macros/uid-algo.Rd |only man/mcmc.diagnostics.Rd | 7 - man/network.list.Rd | 6 man/nodematch-ergmTerm.Rd | 6 man/nparam.Rd | 6 man/param_names.Rd | 4 man/rlebdm.Rd | 28 ++-- man/san.Rd | 8 - man/simulate.ergm.Rd | 12 + man/simulate.formula.Rd | 4 man/summary_formula.Rd | 14 +- man/to_ergm_Cdouble.Rd | 8 - man/update.network.Rd | 12 - src/MHproposal.c | 2 src/wtMHproposal.c | 2 tests/testthat/helper-edges-MLE.R |only tests/testthat/test-bridge-target.stats.R | 18 -- tests/testthat/test-c-ergm_model.R | 8 - tests/testthat/test-constrain-dind.R | 2 tests/testthat/test-drop.R | 1 tests/testthat/test-ergm.bridge.llr.R | 43 +----- tests/testthat/test-metrics.R | 25 --- tests/testthat/test-miss.CD.R | 43 +----- tests/testthat/test-miss.R | 44 +----- tests/testthat/test-parallel.R | 33 ---- vignettes/ergm.Rmd | 2 104 files changed, 695 insertions(+), 644 deletions(-)
Title: Alternating Manifold Proximal Gradient Method for Sparse PCA
Description: Alternating Manifold Proximal Gradient Method for Sparse PCA uses the Alternating Manifold Proximal
Gradient (AManPG) method to find sparse principal components from a data or covariance matrix. Provides
a novel algorithm for solving the sparse principal component analysis problem which provides
advantages over existing methods in terms of efficiency and convergence guarantees.
Chen, S., Ma, S., Xue, L., & Zou, H. (2020) <doi:10.1287/ijoo.2019.0032>.
Zou, H., Hastie, T., & Tibshirani, R. (2006) <doi:10.1198/106186006X113430>.
Zou, H., & Xue, L. (2018) <doi:10.1109/JPROC.2018.2846588>.
Author: Shixiang Chen [aut],
Justin Huang [aut],
Benjamin Jochem [aut],
Shiqian Ma [aut],
Haichuan Xu [aut],
Lingzhou Xue [aut],
Zhong Zheng [cre, aut],
Hui Zou [aut]
Maintainer: Zhong Zheng <zvz5337@psu.edu>
Diff between amanpg versions 0.3.3 dated 2021-10-05 and 0.3.4 dated 2022-10-02
DESCRIPTION | 18 +- MD5 | 8 - build/vignette.rds |binary inst/doc/An-Introduction-to-amanpg.R | 246 ++++++++++++++++----------------- inst/doc/An-Introduction-to-amanpg.pdf |binary 5 files changed, 138 insertions(+), 134 deletions(-)
Title: Multivariate Nonparametric Probability Density Estimator
Description: Farmer, J., D. Jacobs (2108) <DOI:10.1371/journal.pone.0196937>. A multivariate nonparametric density estimator based on the maximum-entropy method. Accurately predicts a probability density function (PDF) for random data using a novel iterative scoring function to determine the best fit without overfitting to the sample.
Author: Jenny Farmer <jfarmer@carolina.rr.com> and Donald Jacobs <djacobs1@uncc.ecu>
Maintainer: Jenny Farmer <jfarmer@carolina.rr.com>
Diff between PDFEstimator versions 4.1 dated 2022-08-11 and 4.3 dated 2022-10-02
DESCRIPTION | 10 +++---- MD5 | 12 ++++---- build/partial.rdb |binary src/ChebyShev.cpp | 67 +++++++++++++++--------------------------------- src/ChebyShev.h | 7 +---- src/InputData.cpp | 2 - src/InputParameters.cpp | 24 ++++++++--------- 7 files changed, 46 insertions(+), 76 deletions(-)
Title: 'Amazon Web Services' Application Integration Services
Description: Interface to 'Amazon Web Services' application integration
services, including 'Simple Queue Service' ('SQS') message queue,
'Simple Notification Service' ('SNS') publish/subscribe messaging, and
more <https://aws.amazon.com/>.
Author: David Kretch [aut],
Adam Banker [aut],
Dyfan Jones [cre],
Amazon.com, Inc. [cph]
Maintainer: Dyfan Jones <dyfan.r.jones@gmail.com>
Diff between paws.application.integration versions 0.1.12 dated 2021-08-23 and 0.1.13 dated 2022-10-02
DESCRIPTION | 28 MD5 | 156 R/eventbridge_interfaces.R | 932 +- R/eventbridge_operations.R | 5616 +++++++------- R/eventbridge_service.R | 272 R/mq_interfaces.R | 528 - R/mq_operations.R | 3066 ++++---- R/mq_service.R | 204 R/sfn_interfaces.R | 560 - R/sfn_operations.R | 3584 ++++----- R/sfn_service.R | 238 R/sns_interfaces.R | 760 +- R/sns_operations.R | 4614 ++++++------ R/sns_service.R | 258 R/sqs_interfaces.R | 452 - R/sqs_operations.R | 4764 ++++++------ R/sqs_service.R | 278 R/swf_interfaces.R | 824 +- R/swf_operations.R | 9426 ++++++++++++------------- R/swf_service.R | 256 man/eventbridge.Rd | 222 man/eventbridge_create_partner_event_source.Rd | 122 man/eventbridge_list_targets_by_rule.Rd | 248 man/eventbridge_put_events.Rd | 104 man/eventbridge_put_permission.Rd | 192 man/eventbridge_put_rule.Rd | 238 man/eventbridge_put_targets.Rd | 454 - man/eventbridge_test_event_pattern.Rd | 76 man/mq.Rd | 158 man/mq_create_broker.Rd | 314 man/mq_create_configuration.Rd | 124 man/mq_create_user.Rd | 92 man/mq_delete_user.Rd | 60 man/mq_describe_user.Rd | 90 man/mq_update_broker.Rd | 2 man/mq_update_user.Rd | 92 man/sfn.Rd | 188 man/sfn_create_activity.Rd | 156 man/sfn_send_task_failure.Rd | 74 man/sfn_send_task_heartbeat.Rd | 96 man/sfn_send_task_success.Rd | 72 man/sfn_start_execution.Rd | 148 man/sns.Rd | 206 man/sns_create_platform_application.Rd | 134 man/sns_opt_in_phone_number.Rd | 58 man/sns_set_platform_application_attributes.Rd | 128 man/sns_set_sms_attributes.Rd | 208 man/sns_set_subscription_attributes.Rd | 108 man/sns_subscribe.Rd | 230 man/sns_tag_resource.Rd | 96 man/sqs.Rd | 214 man/sqs_change_message_visibility.Rd | 188 man/sqs_change_message_visibility_batch.Rd | 140 man/sqs_delete_message_batch.Rd | 128 man/sqs_receive_message.Rd | 480 - man/sqs_send_message.Rd | 396 - man/sqs_send_message_batch.Rd | 230 man/swf.Rd | 208 man/swf_deprecate_activity_type.Rd | 126 man/swf_deprecate_workflow_type.Rd | 128 man/swf_describe_workflow_type.Rd | 170 man/swf_poll_for_activity_task.Rd | 178 man/swf_poll_for_decision_task.Rd | 1104 +- man/swf_record_activity_task_heartbeat.Rd | 174 man/swf_register_activity_type.Rd | 278 man/swf_register_workflow_type.Rd | 318 man/swf_respond_activity_task_canceled.Rd | 142 man/swf_respond_activity_task_completed.Rd | 146 man/swf_respond_activity_task_failed.Rd | 132 man/swf_respond_decision_task_completed.Rd | 316 man/swf_start_workflow_execution.Rd | 388 - man/swf_undeprecate_activity_type.Rd | 124 man/swf_undeprecate_workflow_type.Rd | 122 tests/testthat/test_eventbridge.R | 50 tests/testthat/test_mq.R | 66 tests/testthat/test_sfn.R | 18 tests/testthat/test_sns.R | 34 tests/testthat/test_sqs.R | 18 tests/testthat/test_swf.R | 6 79 files changed, 23662 insertions(+), 23666 deletions(-)
More information about paws.application.integration at CRAN
Permanent link
Title: Analysis of Multivariate Event Times
Description: Implementation of various statistical models for multivariate
event history data <doi:10.1007/s10985-013-9244-x>. Including multivariate
cumulative incidence models <doi:10.1002/sim.6016>, and bivariate random
effects probit models (Liability models) <doi:10.1016/j.csda.2015.01.014>.
Also contains two-stage binomial modelling that can do pairwise odds-ratio
dependence modelling based marginal logistic regression models. This is an
alternative to the alternating logistic regression approach (ALR).
Author: Klaus K. Holst [aut, cre],
Thomas Scheike [aut]
Maintainer: Klaus K. Holst <klaus@holst.it>
Diff between mets versions 1.3.0 dated 2022-09-05 and 1.3.1 dated 2022-10-02
mets-1.3.0/mets/data/datalist |only mets-1.3.0/mets/data/migr.txt |only mets-1.3.0/mets/data/multcif.txt |only mets-1.3.0/mets/data/np.txt |only mets-1.3.0/mets/data/twinbmi.txt |only mets-1.3.0/mets/data/twinstut.txt |only mets-1.3.1/mets/DESCRIPTION | 8 mets-1.3.1/mets/MD5 | 97 +- mets-1.3.1/mets/NEWS.md | 3 mets-1.3.1/mets/R/binomial.regression.R | 4 mets-1.3.1/mets/R/phreg.R | 33 mets-1.3.1/mets/R/restricted.mean.R | 31 mets-1.3.1/mets/data/migr.txt.xz |only mets-1.3.1/mets/data/multcif.txt.xz |only mets-1.3.1/mets/data/np.txt.xz |only mets-1.3.1/mets/data/twinbmi.txt.xz |only mets-1.3.1/mets/data/twinstut.txt.xz |only mets-1.3.1/mets/inst/doc/basic-dutils.html | 45 - mets-1.3.1/mets/inst/doc/binomial-family.html | 113 +- mets-1.3.1/mets/inst/doc/binomial-twin.R | 24 mets-1.3.1/mets/inst/doc/binomial-twin.Rmd | 24 mets-1.3.1/mets/inst/doc/binomial-twin.html | 107 +- mets-1.3.1/mets/inst/doc/binreg-ate.R | 3 mets-1.3.1/mets/inst/doc/binreg-ate.Rmd | 3 mets-1.3.1/mets/inst/doc/binreg-ate.html | 116 +-- mets-1.3.1/mets/inst/doc/binreg.html | 47 - mets-1.3.1/mets/inst/doc/cifreg.html | 52 - mets-1.3.1/mets/inst/doc/haplo-discrete-ttp.html | 50 - mets-1.3.1/mets/inst/doc/interval-discrete-survival.html | 52 - mets-1.3.1/mets/inst/doc/marginal-cox.R | 6 mets-1.3.1/mets/inst/doc/marginal-cox.Rmd | 10 mets-1.3.1/mets/inst/doc/marginal-cox.html | 92 +- mets-1.3.1/mets/inst/doc/mediation-survival.html | 384 +++++----- mets-1.3.1/mets/inst/doc/quantitative-twin.R | 11 mets-1.3.1/mets/inst/doc/quantitative-twin.Rmd | 37 mets-1.3.1/mets/inst/doc/quantitative-twin.html | 53 - mets-1.3.1/mets/inst/doc/recurrent-events.R | 6 mets-1.3.1/mets/inst/doc/recurrent-events.Rmd | 10 mets-1.3.1/mets/inst/doc/recurrent-events.html | 106 +- mets-1.3.1/mets/inst/doc/time-to-event-family-studies-arev.R | 6 mets-1.3.1/mets/inst/doc/time-to-event-family-studies-arev.Rmd | 10 mets-1.3.1/mets/inst/doc/time-to-event-family-studies-arev.html | 94 +- mets-1.3.1/mets/inst/doc/twostage-survival.R | 4 mets-1.3.1/mets/inst/doc/twostage-survival.Rmd | 4 mets-1.3.1/mets/inst/doc/twostage-survival.html | 66 - mets-1.3.1/mets/man/binregATE.Rd | 4 mets-1.3.1/mets/man/figures |only mets-1.3.1/mets/man/resmeanIPCW.Rd | 22 mets-1.3.1/mets/vignettes/binomial-twin.Rmd | 24 mets-1.3.1/mets/vignettes/binreg-ate.Rmd | 3 mets-1.3.1/mets/vignettes/marginal-cox.Rmd | 10 mets-1.3.1/mets/vignettes/quantitative-twin.Rmd | 37 mets-1.3.1/mets/vignettes/recurrent-events.Rmd | 10 mets-1.3.1/mets/vignettes/time-to-event-family-studies-arev.Rmd | 10 mets-1.3.1/mets/vignettes/twostage-survival.Rmd | 4 55 files changed, 983 insertions(+), 852 deletions(-)
Title: Fast and Flexible Implementations of Exploratory Factor Analysis
Tools
Description: Provides functions to perform exploratory factor analysis (EFA) procedures and compare their solutions. The goal is to provide state-of-the-art factor retention methods and a high degree of flexibility in the EFA procedures. This way, for example, implementations from R 'psych' and 'SPSS' can be compared. Moreover, functions for Schmid-Leiman transformation and the computation of omegas are provided. To speed up the analyses, some of the iterative procedures, like principal axis factoring (PAF), are implemented in C++.
Author: Markus Steiner [aut, cre],
Silvia Grieder [aut],
William Revelle [ctb],
Max Auerswald [ctb],
Morten Moshagen [ctb],
John Ruscio [ctb],
Brendan Roche [ctb],
Urbano Lorenzo-Seva [ctb],
David Navarro-Gonzalez [ctb]
Maintainer: Markus Steiner <markus.d.steiner@gmail.com>
Diff between EFAtools versions 0.4.2 dated 2022-09-27 and 0.4.3 dated 2022-10-02
DESCRIPTION | 6 - MD5 | 10 +- NEWS.md | 23 ++++-- R/helper.R | 12 ++- inst/doc/EFAtools.html | 137 ++++++++++++++++++------------------- inst/doc/Replicate_SPSS_psych.html | 127 +++++++++++++++++----------------- 6 files changed, 167 insertions(+), 148 deletions(-)
Title: Statistical Functions for the Design of Studies with Composite
Endpoints
Description: It has been designed to calculate the required sample size in randomized clinical trials with composite endpoints. This package also includes functions to calculate the probability of observing the composite endpoint and the expected effect on the composite endpoint, among others. The methods implemented can be found in Bofill & Gómez (2019) <doi:10.1002/sim.8092> and Gómez & Lagakos (2013) <doi:10.1002/sim.5547>.
Author: Marta Bofill Roig [aut, cre], Jordi Cortes Martinez [aut], Guadalupe Gomez Melis [ctb]
Maintainer: Marta Bofill Roig <marta.bofillroig@meduniwien.ac.at>
Diff between CompAREdesign versions 2.1 dated 2022-09-29 and 2.2 dated 2022-10-02
DESCRIPTION | 6 +++--- MD5 | 57 +++++++++++++++++++++++++++++++++++++++++++++++++++++++-- NAMESPACE | 35 +++++++++++++++++++++++++++++++++++ R |only man |only 5 files changed, 93 insertions(+), 5 deletions(-)
Title: Dimension Reduction Methods for Multivariate Time Series
Description: Estimates VAR and VARX models with Structured Penalties.
Author: Will Nicholson [cre, aut],
David Matteson [aut],
Jacob Bien [aut]
Maintainer: Will Nicholson <wbn8@cornell.edu>
Diff between BigVAR versions 1.1.0 dated 2022-03-22 and 1.1.1 dated 2022-10-02
DESCRIPTION | 17 - MD5 | 32 +- NEWS | 7 R/BigVARAlgorithms.R | 10 R/BigVARFitFun.R | 22 + R/BigVARObjectClass.R | 249 +++++++++++--------- R/BigVARSupportFunctions.R | 32 +- build/vignette.rds |binary inst/doc/BigVAR.Rmd | 6 inst/doc/BigVAR.html | 36 +- man/constructModel.Rd | 6 man/plot.BigVAR-methods.Rd | 2 src/DataCons.cpp | 18 - src/ExperimentalBigVARFunctionsX.cpp | 7 src/RcppExports.cpp | 5 vignettes/BigVAR.Rmd | 6 vignettes/additional_material/bigvar_references.bib | 15 - 17 files changed, 262 insertions(+), 208 deletions(-)
Title: Exploratory Analysis of Genetic and Genomic Data
Description: Toolset for the exploration of genetic and genomic
data. Adegenet provides formal (S4) classes for storing and handling
various genetic data, including genetic markers with varying ploidy
and hierarchical population structure ('genind' class), alleles counts
by populations ('genpop'), and genome-wide SNP data ('genlight'). It
also implements original multivariate methods (DAPC, sPCA), graphics,
statistical tests, simulation tools, distance and similarity measures,
and several spatial methods. A range of both empirical and simulated
datasets is also provided to illustrate various methods.
Author: Thibaut Jombart [aut] ,
Zhian N. Kamvar [aut, cre] ,
Caitlin Collins [ctb],
Roman Lustrik [ctb],
Marie-Pauline Beugin [ctb],
Brian J. Knaus [ctb],
Peter Solymos [ctb],
Vladimir Mikryukov [ctb],
Klaus Schliep [ctb],
Tiago Maie [ctb],
Libor Morkovsky [ [...truncated...]
Maintainer: Zhian N. Kamvar <zkamvar@gmail.com>
Diff between adegenet versions 2.1.7 dated 2022-06-06 and 2.1.8 dated 2022-10-02
adegenet-2.1.7/adegenet/tests/testthat/Rplots.pdf |only adegenet-2.1.8/adegenet/ChangeLog | 6 ++ adegenet-2.1.8/adegenet/DESCRIPTION | 8 +-- adegenet-2.1.8/adegenet/MD5 | 55 ++++++++++------------ adegenet-2.1.8/adegenet/R/hybridize.R | 2 adegenet-2.1.8/adegenet/build/partial.rdb |binary adegenet-2.1.8/adegenet/data/H3N2.rda |binary adegenet-2.1.8/adegenet/data/dapcIllus.rda |binary adegenet-2.1.8/adegenet/data/eHGDP.rda |binary adegenet-2.1.8/adegenet/data/hybridtoy.RData |binary adegenet-2.1.8/adegenet/data/microbov.rda |binary adegenet-2.1.8/adegenet/data/nancycats.rda |binary adegenet-2.1.8/adegenet/data/rupica.RData |binary adegenet-2.1.8/adegenet/data/sim2pop.rda |binary adegenet-2.1.8/adegenet/data/spcaIllus.rda |binary adegenet-2.1.8/adegenet/data/swallowtails.rda |binary adegenet-2.1.8/adegenet/man/HWE.Rd | 4 - adegenet-2.1.8/adegenet/man/accessors.Rd | 2 adegenet-2.1.8/adegenet/man/dist.genpop.Rd | 2 adegenet-2.1.8/adegenet/man/genind.Rd | 2 adegenet-2.1.8/adegenet/man/genpop.Rd | 2 adegenet-2.1.8/adegenet/man/hybridize.Rd | 2 adegenet-2.1.8/adegenet/man/selpopsize.Rd | 4 - adegenet-2.1.8/adegenet/man/seploc.Rd | 4 - adegenet-2.1.8/adegenet/man/spca.Rd | 8 +-- adegenet-2.1.8/adegenet/man/truenames.Rd | 8 +-- adegenet-2.1.8/adegenet/src/adesub.c | 22 ++++---- adegenet-2.1.8/adegenet/src/snpbin.c | 10 ---- adegenet-2.1.8/adegenet/src/snpbin.h | 1 29 files changed, 68 insertions(+), 74 deletions(-)
Title: Bayesian Model for CACE Analysis
Description: Performs CACE (Complier Average Causal Effect analysis) on either a single study or meta-analysis of datasets with binary outcomes, using either complete or incomplete noncompliance information. Our package implements the Bayesian methods proposed in Zhou et al. (2019) <doi:10.1111/biom.13028>, which introduces a Bayesian hierarchical model for estimating CACE in meta-analysis of clinical trials with noncompliance, and Zhou et al. (2021) <doi:10.1080/01621459.2021.1900859>, with an application example on Epidural Analgesia.
Author: Jinhui Yang [aut, cre] ,
Jincheng Zhou [aut] ,
James Hodges [ctb],
Haitao Chu [ctb]
Maintainer: Jinhui Yang <james.yangjinhui@gmail.com>
Diff between BayesCACE versions 1.2.1 dated 2022-06-13 and 1.2.3 dated 2022-10-02
DESCRIPTION | 8 ++++---- MD5 | 8 ++++---- R/plt.noncomp.R | 4 ++-- build/partial.rdb |binary build/vignette.rds |binary 5 files changed, 10 insertions(+), 10 deletions(-)
Title: Subset- And Name-Aware Array Utility Functions
Description: Stacking arrays according to dimension names, subset-aware
splitting and mapping of functions, intersecting along arbitrary
dimensions, converting to and from data.frames, and many other helper
functions.
Author: Michael Schubert <mschu.dev@gmail.com>
Maintainer: Michael Schubert <mschu.dev@gmail.com>
Diff between narray versions 0.5.0 dated 2022-08-10 and 0.5.1 dated 2022-10-02
DESCRIPTION | 6 +- MD5 | 11 ++- NEWS.md | 10 +++ R/stack_old.r |only inst/doc/narray.html | 132 +++++++++++++++++++++++--------------------- src/stack.cpp | 21 ++++--- tests/testthat/test-stack.r | 15 ++++- 7 files changed, 114 insertions(+), 81 deletions(-)
Title: Data and Statistical Analyses after Multiple Imputation
Description: Statistical Analyses and Pooling after Multiple Imputation. A large variety
of repeated statistical analysis can be performed and finally pooled. Statistical analysis
that are available are, among others, Levene's test, Odds and Risk Ratios, One sample
proportions, difference between proportions and linear and logistic regression models.
Functions can also be used in combination with the Pipe operator.
More and more statistical analyses and pooling functions will be added over time.
Heymans (2007) <doi:10.1186/1471-2288-7-33>.
Eekhout (2017) <doi:10.1186/s12874-017-0404-7>.
Wiel (2009) <doi:10.1093/biostatistics/kxp011>.
Marshall (2009) <doi:10.1186/1471-2288-9-57>.
Sidi (2021) <doi:10.1080/00031305.2021.1898468>.
Lott (2018) <doi:10.1080/00031305.2018.1473796>.
Grund (2021) <doi:10.31234/osf.io/d459g>.
Author: Martijn Heymans [cre, aut] ,
Jaap Brand [ctb]
Maintainer: Martijn Heymans <mw.heymans@amsterdamumc.nl>
Diff between miceafter versions 0.1.0 dated 2021-12-16 and 0.5.0 dated 2022-10-02
DESCRIPTION | 8 MD5 | 60 +++-- NAMESPACE | 9 NEWS.md | 2 R/bf_test.R | 14 - R/cindex.R | 2 R/cor2fz.R |only R/cor_est.R |only R/df2milist.R | 2 R/fz2cor.R |only R/glm_mi.R | 2 R/invlogit_ci.R | 2 R/pool_cindex.R | 8 R/pool_cor.R |only R/pool_glm.R | 2 R/pool_propdiff_ac.R | 24 +- R/pool_scalar_RR.R | 72 ++++-- R/pool_t_test.R |only R/propdiff_ac.R | 33 ++ R/t_test.R |only R/with.milist.R | 2 README.md | 3 build/vignette.rds |binary inst/doc/levene_test.html | 254 +++++++++++++++++++++- inst/doc/pooling_cindex.html | 258 +++++++++++++++++++++-- inst/doc/regression_modelling.html | 409 ++++++++++++++++++++++++++++--------- man/bf_test.Rd | 12 - man/cor2fz.Rd |only man/cor_est.Rd |only man/fz2cor.Rd |only man/pool_cindex.Rd | 6 man/pool_cor.Rd |only man/pool_propdiff_ac.Rd | 15 + man/pool_scalar_RR.Rd | 11 man/pool_t_test.Rd |only man/propdiff_ac.Rd | 17 + man/t_test.Rd |only 37 files changed, 1022 insertions(+), 205 deletions(-)
Title: Paws Low-Level Amazon Web Services API
Description: Functions for making low-level API requests to Amazon Web Services
<https://aws.amazon.com>. The functions handle building, signing, and
sending requests, and receiving responses. They are designed to help build
higher-level interfaces to individual services, such as Simple Storage
Service (S3).
Author: David Kretch [aut],
Adam Banker [aut],
Dyfan Jones [cre],
Amazon.com, Inc. [cph]
Maintainer: Dyfan Jones <dyfan.r.jones@gmail.com>
Diff between paws.common versions 0.5.0 dated 2022-09-02 and 0.5.1 dated 2022-10-02
DESCRIPTION | 6 +++--- MD5 | 10 +++++----- NEWS.md | 4 ++++ R/util.R | 13 ++++++++++++- R/xmlutil.R | 7 +++++-- tests/testthat/test_xmlutil.R | 26 ++++++++++++++++++++++++++ 6 files changed, 55 insertions(+), 11 deletions(-)
Title: 'Rcpp' Integration for the 'Armadillo' Templated Linear Algebra
Library
Description: 'Armadillo' is a templated C++ linear algebra library (by Conrad
Sanderson) that aims towards a good balance between speed and ease of
use. Integer, floating point and complex numbers are supported, as
well as a subset of trigonometric and statistics functions. Various
matrix decompositions are provided through optional integration with
LAPACK and ATLAS libraries. The 'RcppArmadillo' package includes the
header files from the templated 'Armadillo' library. Thus users do
not need to install 'Armadillo' itself in order to use
'RcppArmadillo'. From release 7.800.0 on, 'Armadillo' is licensed
under Apache License 2; previous releases were under licensed as MPL
2.0 from version 3.800.0 onwards and LGPL-3 prior to that;
'RcppArmadillo' (the 'Rcpp' bindings/bridge to Armadillo) is licensed
under the GNU GPL version 2 or later, as is the rest of 'Rcpp'.
Author: Dirk Eddelbuettel, Romain Francois, Doug Bates, Binxiang Ni, and Conrad Sanderson
Maintainer: Dirk Eddelbuettel <edd@debian.org>
Diff between RcppArmadillo versions 0.11.2.4.0 dated 2022-09-10 and 0.11.4.0.1 dated 2022-10-02
ChangeLog | 25 + DESCRIPTION | 8 MD5 | 81 ++-- README.md | 8 configure | 18 - configure.ac | 2 inst/NEWS.Rd | 13 inst/doc/RcppArmadillo-intro.pdf |binary inst/doc/RcppArmadillo-sparseMatrix.pdf |binary inst/include/armadillo | 3 inst/include/armadillo_bits/Col_bones.hpp | 4 inst/include/armadillo_bits/Col_meat.hpp | 98 ++--- inst/include/armadillo_bits/Cube_bones.hpp | 10 inst/include/armadillo_bits/Cube_meat.hpp | 278 ++++++++-------- inst/include/armadillo_bits/MapMat_meat.hpp | 2 inst/include/armadillo_bits/Mat_bones.hpp | 7 inst/include/armadillo_bits/Mat_meat.hpp | 172 +++++---- inst/include/armadillo_bits/Row_bones.hpp | 4 inst/include/armadillo_bits/Row_meat.hpp | 98 ++--- inst/include/armadillo_bits/arma_version.hpp | 6 inst/include/armadillo_bits/auxlib_meat.hpp | 66 +-- inst/include/armadillo_bits/compiler_setup.hpp | 8 inst/include/armadillo_bits/debug.hpp | 20 + inst/include/armadillo_bits/field_meat.hpp | 2 inst/include/armadillo_bits/fn_chol.hpp | 2 inst/include/armadillo_bits/fn_find.hpp | 81 ++++ inst/include/armadillo_bits/fn_powext.hpp |only inst/include/armadillo_bits/glue_powext_bones.hpp |only inst/include/armadillo_bits/glue_powext_meat.hpp |only inst/include/armadillo_bits/op_chol_meat.hpp | 2 inst/include/armadillo_bits/op_expmat_meat.hpp | 2 inst/include/armadillo_bits/op_find_bones.hpp | 11 inst/include/armadillo_bits/op_find_meat.hpp | 46 ++ inst/include/armadillo_bits/op_inv_gen_meat.hpp | 4 inst/include/armadillo_bits/op_inv_spd_meat.hpp | 4 inst/include/armadillo_bits/op_sum_meat.hpp | 123 +++++-- inst/include/armadillo_bits/sp_auxlib_meat.hpp | 30 - inst/include/armadillo_bits/subview_cube_each_bones.hpp | 10 inst/include/armadillo_bits/subview_cube_each_meat.hpp | 18 - inst/include/armadillo_bits/subview_each_bones.hpp | 10 inst/include/armadillo_bits/subview_each_meat.hpp | 12 man/RcppArmadillo-package.Rd | 4 man/fastLm.Rd | 12 43 files changed, 804 insertions(+), 500 deletions(-)
Title: Bayesian Hierarchical Multi-Subject Multiscale Analysis of
Functional MRI (fMRI) Data
Description: Package BHMSMAfMRI performs Bayesian hierarchical multi-subject multiscale analysis of fMRI data as described in Sanyal & Ferreira (2012) <DOI:10.1016/j.neuroimage.2012.08.041>, or other multiscale data, using wavelet based prior that borrows strength across subjects and provides posterior smoothed images of the effect sizes and samples from the posterior distribution.
Author: Nilotpal Sanyal [aut, cre] ,
Marco A.R. Ferreira [aut]
Maintainer: Nilotpal Sanyal <nilotpal.sanyal@gmail.com>
Diff between BHMSMAfMRI versions 2.0 dated 2022-09-08 and 2.1 dated 2022-10-02
DESCRIPTION | 19 +++++++++---------- MD5 | 30 +++++++++++++++++++++--------- NEWS | 12 ++++++++++++ NEWS.md |only R/BHMSMA.R | 4 ++-- R/welcome_msg.R |only README.md |only inst/doc/BHMSMAfMRIvignette.R | 12 ++++++------ inst/doc/BHMSMAfMRIvignette.Rmd | 12 ++++++------ inst/doc/BHMSMAfMRIvignette.pdf |binary man/BHMSMAfMRI-package.Rd | 4 ++-- man/figures |only vignettes/BHMSMAfMRIvignette.Rmd | 12 ++++++------ vignettes/BOLDMATH2.TEX |only vignettes/GLMCoef.pdf |only vignettes/PostDiscovery.pdf |only vignettes/PostGLMCoef.pdf |only vignettes/PostGroupCoef.pdf |only vignettes/TrueCoef.pdf |only vignettes/jasa.bst |only vignettes/mybib.bib | 11 +---------- 21 files changed, 65 insertions(+), 51 deletions(-)