Title: Bayesian Variable Selection and Model Averaging using Bayesian
Adaptive Sampling
Description: Package for Bayesian Variable Selection and Model Averaging
in linear models and generalized linear models using stochastic or
deterministic sampling without replacement from posterior
distributions. Prior distributions on coefficients are
from Zellner's g-prior or mixtures of g-priors
corresponding to the Zellner-Siow Cauchy Priors or the
mixture of g-priors from Liang et al (2008)
<DOI:10.1198/016214507000001337>
for linear models or mixtures of g-priors from Li and Clyde
(2019) <DOI:10.1080/01621459.2018.1469992> in generalized linear models.
Other model selection criteria include AIC, BIC and Empirical Bayes
estimates of g. Sampling probabilities may be updated based on the sampled
models using sampling w/out replacement or an efficient MCMC algorithm which
samples models using a tree structure of the model space
as an efficient hash table. See Clyde, Ghosh and Littman (2010)
<DOI:10.1198/jcgs.2010.09049> for details on the sampling algorithms.
Uniform priors over all models or beta-binomial prior distributions on
model size are allowed, and for large p truncated priors on the model
space may be used to enforce sampling models that are full rank.
The user may force variables to always be included in addition to imposing
constraints that higher order interactions are included only if their
parents are included in the model.
This material is based upon work supported by the National Science
Foundation under Division of Mathematical Sciences grant 1106891.
Any opinions, findings, and
conclusions or recommendations expressed in this material are those of
the author(s) and do not necessarily reflect the views of the
National Science Foundation.
Author: Merlise Clyde [aut, cre, cph] (ORCID=0000-0002-3595-1872),
Michael Littman [ctb],
Quanli Wang [ctb],
Joyee Ghosh [ctb],
Yingbo Li [ctb],
Don van de Bergh [ctb]
Maintainer: Merlise Clyde <clyde@duke.edu>
Diff between BAS versions 1.5.5 dated 2020-01-24 and 1.6.0 dated 2021-11-12
DESCRIPTION | 12 MD5 | 66 +-- NEWS.md | 13 R/BAS-package.R | 10 R/EB_global.R | 2 R/bas_glm.R | 6 R/bas_lm.R | 10 R/coefficients.R | 2 R/data.R | 2 R/hypergeometric2F1.R | 2 R/predict.R | 2 R/update.R | 2 README.md |only build/partial.rdb |only build/vignette.rds |binary inst/doc/BAS-vignette.html | 745 ++++++++++++++------------------------ man/BAS.Rd | 10 man/EB.global.Rd | 2 man/Hald.Rd | 6 man/bas.glm.Rd | 6 man/bas.lm.Rd | 10 man/bodyfat.Rd | 6 man/climate.Rd | 8 man/coef.Rd | 2 man/figures/unnamed-chunk-3-1.png |binary man/fitted.Rd | 2 man/hypergeometric2F1.Rd | 2 man/protein.Rd | 6 man/update.Rd | 2 src/Makevars.win | 1 src/bas.h | 11 src/bayesglm.c | 5 src/bayesreg.c | 22 - src/family.c | 6 src/glm_fit.c | 5 35 files changed, 428 insertions(+), 558 deletions(-)
Title: Semi-Automatic Grading of R and Rmd Scripts
Description: A customisable set of tools for assessing and grading
R or R-markdown scripts from students. It allows for checking correctness
of code output, runtime statistics and static code analysis. The latter
feature is made possible by representing R expressions using a tree
structure.
Author: Vik Gopal [aut, cre],
Samuel Seah [aut],
Viknesh Jeya Kumar [aut],
Gabriel Ang [aut],
Ruofan Liu [ctb],
National University of Singapore [cph]
Maintainer: Vik Gopal <vik.gopal@nus.edu.sg>
Diff between autoharp versions 0.0.8 dated 2021-05-29 and 0.0.10 dated 2021-11-12
DESCRIPTION | 7 ++++--- MD5 | 14 +++++++------- NEWS | 14 ++++++++++++++ R/forestharp.R | 12 ++++++++++-- R/log_summary.R | 7 ++++++- R/render_one.R | 8 ++++---- R/run_tuner.R | 5 ++--- R/utils.R | 22 +++++++++++++++------- 8 files changed, 62 insertions(+), 27 deletions(-)
Title: Conditional Random Fields for Labelling Sequential Data in
Natural Language Processing
Description: Wraps the 'CRFsuite' library <https://github.com/chokkan/crfsuite> allowing users
to fit a Conditional Random Field model and to apply it on existing data.
The focus of the implementation is in the area of Natural Language Processing where this R package allows you to easily build and apply models
for named entity recognition, text chunking, part of speech tagging, intent recognition or classification of any category you have in mind. Next to training, a small web application
is included in the package to allow you to easily construct training data.
Author: Jan Wijffels [aut, cre, cph] (R wrapper),
BNOSAC [cph] (R wrapper),
Naoaki Okazaki [aut, ctb, cph] (CRFsuite library (BSD licensed),
libLBFGS library (MIT licensed), Constant Quark Database software
(BSD licensed)),
Bob Jenkins [aut, ctb] (File src/cqdb/src/lookup3.c (Public Domain)),
Jorge Nocedal [aut, ctb, cph] (libLBFGS library (MIT licensed)),
Jesse Long [aut, ctb, cph] (RumAVL library (MIT licensed))
Maintainer: Jan Wijffels <jwijffels@bnosac.be>
Diff between crfsuite versions 0.3.4 dated 2020-10-10 and 0.4 dated 2021-11-12
DESCRIPTION | 6 LICENSE | 6 LICENSE.note | 290 ++--- MD5 | 83 - NAMESPACE | 68 - NEWS.md | 88 - R/RcppExports.R | 58 - R/coef.R |only R/data.R | 400 +++--- R/evaluation.R | 246 ++-- R/feature_engineering.R | 318 ++--- R/modelling.R | 932 ++++++++-------- R/pkg.R | 18 R/training_data.R | 436 +++---- R/utils.R | 64 - README.md | 140 +- build/vignette.rds |binary inst/CITATION | 30 inst/app/annotation.Rmd | 758 ++++++------- inst/crftuning/crftuning.R | 130 +- inst/doc/crfsuite-nlp.R | 217 +-- inst/doc/crfsuite-nlp.Rmd | 551 ++++----- inst/doc/crfsuite-nlp.html | 2419 ++++++++++++++++++++++++++++++++---------- man/airbnb.Rd | 52 man/airbnb_chunks.Rd | 58 - man/as.crf.Rd | 46 man/crf.Rd | 280 ++-- man/crf_caretmethod.Rd | 74 - man/crf_cbind_attributes.Rd | 138 +- man/crf_evaluation.Rd | 164 +- man/crf_options.Rd | 98 - man/merge.chunkrange.Rd | 134 +- man/ner_download_modeldata.Rd | 92 - man/predict.crf.Rd | 151 +- man/txt_feature.Rd | 82 - man/txt_sprintf.Rd | 66 - src/RcppExports.cpp | 35 src/crf/src/crf1d.h | 1 src/crf/src/crf1d_model.c | 105 + src/crf/src/crf1d_tag.c | 7 src/include/crfsuite.h | 10 src/rcpp_crfsuite.cpp | 32 vignettes/crfsuite-nlp.Rmd | 551 ++++----- 43 files changed, 5504 insertions(+), 3930 deletions(-)
Title: Access and Analyze eBird Status and Trends Data
Description: Tools to download, map, plot and analyze eBird Status and
Trends data (<https://ebird.org/science/status-and-trends>). eBird
(<https://ebird.org/home>) is a global database of bird observations
collected by citizen scientists. eBird Status and Trends uses these
data to model continental bird abundances, range boundaries, habitat
associations, and trends.
Author: Matthew Strimas-Mackey [aut, cre]
(<https://orcid.org/0000-0001-8929-7776>),
Shawn Ligocki [aut],
Tom Auer [aut] (<https://orcid.org/0000-0001-8619-7147>),
Daniel Fink [aut] (<https://orcid.org/0000-0002-8368-1248>),
Cornell Lab of Ornithology [cph]
Maintainer: Matthew Strimas-Mackey <mes335@cornell.edu>
Diff between ebirdst versions 0.3.2 dated 2021-09-15 and 0.3.3 dated 2021-11-12
DESCRIPTION | 8 +-- MD5 | 19 +++---- NEWS.md | 4 + R/ebirdst-loading.R | 83 ++++++++++++++++++++++++--------- R/ebirdst-plotting.R | 8 --- inst/doc/ebirdst-advanced-mapping.html | 4 - inst/doc/ebirdst-intro-mapping.html | 4 - inst/doc/ebirdst-non-raster.html | 4 - inst/doc/ebirdst.html | 4 - inst/extdata |only tests/testthat/test_pipd.R | 8 --- 11 files changed, 89 insertions(+), 57 deletions(-)
Title: Trajectories and Phylogenies Simulator
Description: Generates stochastic time series and genealogies associated with a population dynamics model. Times series are simulated using the Gillespie exact and approximate algorithms and a new algorithm we introduce that uses both approaches to optimize the time execution of the simulations. Genealogies are simulated from a trajectory using a backwards-in-time based approach. Methods are described in Danesh G et al (2020) <doi:10.1101/2020.11.09.373795>.
Author: Gonche Danesh [aut, cre, cph],
Emma Saulnier [aut, cph],
Olivier Gascuel [aut, cph],
Marc Choisy [aut, cph, ths],
Samuel Alizon [aut, cph, ths]
Maintainer: Gonche Danesh <gonche.danesh@gmail.com>
Diff between TiPS versions 1.0 dated 2021-09-13 and 1.1.0 dated 2021-11-12
TiPS-1.0/TiPS/vignettes/TiPS_cache |only TiPS-1.0/TiPS/vignettes/TiPS_files |only TiPS-1.1.0/TiPS/DESCRIPTION | 12 +- TiPS-1.1.0/TiPS/MD5 | 159 +---------------------------- TiPS-1.1.0/TiPS/R/generator.R | 175 ++++++++++++++++----------------- TiPS-1.1.0/TiPS/inst/CITATION |only TiPS-1.1.0/TiPS/inst/doc/TiPS.R | 10 + TiPS-1.1.0/TiPS/inst/doc/TiPS.Rmd | 37 ++++-- TiPS-1.1.0/TiPS/inst/doc/TiPS.html | 103 +++++++++++-------- TiPS-1.1.0/TiPS/man/build_simulator.Rd | 13 +- TiPS-1.1.0/TiPS/src/Reaction.cpp | 15 +- TiPS-1.1.0/TiPS/vignettes/TiPS.Rmd | 37 ++++-- 12 files changed, 242 insertions(+), 319 deletions(-)
Title: Sum of Single Effects Linear Regression
Description: Implements methods for variable selection in linear
regression based on the "Sum of Single Effects" (SuSiE) model, as
described in Wang et al (2020) <DOI:10.1101/501114> and Zou et al
(2021) <DOI:10.1101/2021.11.03.467167>. These methods provide
simple summaries, called "Credible Sets", for accurately
quantifying uncertainty in which variables should be selected.
The methods are motivated by genetic fine-mapping applications,
and are particularly well-suited to settings where variables are
highly correlated and detectable effects are sparse. The fitting
algorithm, a Bayesian analogue of stepwise selection methods
called "Iterative Bayesian Stepwise Selection" (IBSS), is simple
and fast, allowing the SuSiE model be fit to large data sets
(thousands of samples and hundreds of thousands of variables).
Author: Gao Wang [aut],
Yuxin Zou [aut],
Kaiqian Zhang [aut],
Peter Carbonetto [aut, cre],
Matthew Stephens [aut]
Maintainer: Peter Carbonetto <peter.carbonetto@gmail.com>
Diff between susieR versions 0.11.84 dated 2021-11-10 and 0.11.92 dated 2021-11-12
DESCRIPTION | 13 ++++---- MD5 | 29 ++++++++++--------- R/susie_utils.R | 40 ++++++++++++++++----------- build/partial.rdb |binary inst/doc/finemapping.html | 6 ++-- inst/doc/finemapping_summary_statistics.html | 6 ++-- inst/doc/l0_initialization.html | 4 +- inst/doc/mwe.html | 6 ++-- inst/doc/sparse_susie_eval.html | 4 +- inst/doc/susie_refine.html | 6 ++-- inst/doc/susierss_diagnostic.html | 6 ++-- inst/doc/trend_filtering.html | 4 +- inst/doc/trendfiltering_derivations.pdf |binary man/susieR-package.Rd | 5 ++- man/susie_get_methods.Rd | 7 ++++ tests/testthat/test_susie_get_cs.R |only 16 files changed, 77 insertions(+), 59 deletions(-)
Title: Bayes Estimation of Latent Class Mixed Multinomial Probit Models
Description: Fitting latent class mixed multinomial probit (LCMMNP) models to simulated
or empirical choice data via Bayesian estimation. The number of latent
classes can be updated within the algorithm on a weight-based strategy.
For a reference on the method see Oelschlaeger and Bauer (2021)
<https://trid.trb.org/view/1759753>.
Author: Lennart Oelschläger [aut, cre],
Dietmar Bauer [aut],
Sebastian Büscher [ctb],
Manuel Batram [ctb]
Maintainer: Lennart Oelschläger <lennart.oelschlaeger@uni-bielefeld.de>
Diff between RprobitB versions 0.1.1 dated 2021-05-25 and 1.0.0 dated 2021-11-12
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Title: Pacote Para Analise Multivariada
Description: Package with multivariate analysis methodologies for experiment evaluation.
The package estimates dissimilarity measures, builds dendrograms, obtains MANOVA,
principal components, canonical variables, etc. (Pacote com metodologias de analise
multivariada para avaliação de experimentos. O pacote estima medidas de dissimilaridade,
construi de dendogramas, obtem a MANOVA, componentes principais, variáveis canônicas, etc.)
Author: Alcinei Mistico Azevedo [aut, cre]
(<https://orcid.org/0000-0001-5196-0851>)
Maintainer: Alcinei Mistico Azevedo <alcineimistico@hotmail.com>
Diff between MultivariateAnalysis versions 0.4.3 dated 2021-09-27 and 0.4.4 dated 2021-11-12
DESCRIPTION | 6 MD5 | 107 +++++---- NAMESPACE | 5 NEWS.md | 8 R/ApplyDissimilaridade.R | 3 R/ComponentesPrincipais.Misto.R | 237 +++++++++++----------- R/Dendograma.R | 144 ------------- R/Dendrograma.R |only R/HeatPlot.R | 28 +- R/MANOVA.R | 2 R/MatrixPlot.R |only R/Normatiza.R | 4 R/PairComp.R |only R/Tocher.R | 1 R/zzz.R | 50 ++++ inst/doc/Exemplo_dados_DBC_Misto.R | 8 inst/doc/Exemplo_dados_DBC_Misto.Rmd | 12 - inst/doc/Exemplo_dados_DBC_Misto.html | 26 +- inst/doc/Exemplo_dados_Qualitativos_FMI.R | 6 inst/doc/Exemplo_dados_Qualitativos_FMI.Rmd | 8 inst/doc/Exemplo_dados_Qualitativos_FMI.html | 10 inst/doc/Exemplo_dados_binarios.R | 2 inst/doc/Exemplo_dados_binarios.Rmd | 4 inst/doc/Exemplo_dados_binarios.html | 14 - inst/doc/Exemplo_dados_misto.R | 8 inst/doc/Exemplo_dados_misto.Rmd | 12 - inst/doc/Exemplo_dados_misto.html | 33 +-- inst/doc/Exemplo_dados_multicategoricos.R | 2 inst/doc/Exemplo_dados_multicategoricos.Rmd | 4 inst/doc/Exemplo_dados_multicategoricos.html | 10 inst/doc/Exemplo_dados_quantitativos_DBC.R | 6 inst/doc/Exemplo_dados_quantitativos_DBC.Rmd | 8 inst/doc/Exemplo_dados_quantitativos_DBC.html | 16 - inst/doc/Exemplo_dados_quantitativos_DIC.R | 6 inst/doc/Exemplo_dados_quantitativos_DIC.Rmd | 8 inst/doc/Exemplo_dados_quantitativos_DIC.html | 18 - inst/doc/Exemplo_dados_quantitativos_FAT_DBC.R | 4 inst/doc/Exemplo_dados_quantitativos_FAT_DBC.Rmd | 6 inst/doc/Exemplo_dados_quantitativos_FAT_DBC.html | 14 - inst/doc/Exemplo_dados_quantitativos_Med.R | 6 inst/doc/Exemplo_dados_quantitativos_Med.Rmd | 8 inst/doc/Exemplo_dados_quantitativos_Med.html | 14 - man/ApplyDissimilaridade.Rd | 2 man/Dendograma.Rd | 72 ------ man/Dendrograma.Rd |only man/HeatPlot.Rd | 16 - man/Normatiza.Rd | 4 man/PairComp.Rd |only vignettes/Exemplo_dados_DBC_Misto.Rmd | 12 - vignettes/Exemplo_dados_Qualitativos_FMI.Rmd | 8 vignettes/Exemplo_dados_binarios.Rmd | 4 vignettes/Exemplo_dados_misto.Rmd | 12 - vignettes/Exemplo_dados_multicategoricos.Rmd | 4 vignettes/Exemplo_dados_quantitativos_DBC.Rmd | 8 vignettes/Exemplo_dados_quantitativos_DIC.Rmd | 8 vignettes/Exemplo_dados_quantitativos_FAT_DBC.Rmd | 6 vignettes/Exemplo_dados_quantitativos_Med.Rmd | 8 57 files changed, 460 insertions(+), 572 deletions(-)
More information about MultivariateAnalysis at CRAN
Permanent link
Title: High Dimensional Geometry, Set Operations, Projection, and
Inference Using Kernel Density Estimation, Support Vector
Machines, and Convex Hulls
Description: Estimates the shape and volume of high-dimensional datasets and performs set operations: intersection / overlap, union, unique components, inclusion test, and hole detection. Uses stochastic geometry approach to high-dimensional kernel density estimation, support vector machine delineation, and convex hull generation. Applications include modeling trait and niche hypervolumes and species distribution modeling.
Author: Benjamin Blonder, with contributions from Cecina Babich Morrow, David J. Harris, Stuart Brown, Gregoire Butruille, Alex Laini, and Dan Chen
Maintainer: Benjamin Blonder <benjamin.blonder@berkeley.edu>
Diff between hypervolume versions 2.0.12 dated 2019-12-06 and 3.0.0 dated 2021-11-12
DESCRIPTION | 26 MD5 | 110 ++-- NAMESPACE | 231 ++++---- R/bootstrap.R |only R/bootstrap_seq.R |only R/copy_param_hypervolume.R |only R/estimate_bandwidth.R | 51 + R/get_centroid_weighted.R |only R/globals.R |only R/hypervolume_box.R | 6 R/hypervolume_estimate_probability.R | 119 ++-- R/hypervolume_funnel.R |only R/hypervolume_gaussian.R | 17 R/hypervolume_n_occupancy.R |only R/hypervolume_n_occupancy_permute.R |only R/hypervolume_n_occupancy_test.R |only R/hypervolume_overlap_confidence.R |only R/hypervolume_overlap_test.R |only R/hypervolume_permute.R |only R/hypervolume_plot.R | 872 +++++++++++++++++--------------- R/hypervolume_resample.R |only R/hypervolume_save_animated_gif.R | 2 R/hypervolume_set_n_intersection.R |only R/hypervolume_thin.R | 4 R/k_split.R |only R/sampling_bias_bootstrap.R |only R/to_hv_list.R |only R/weight_data.R | 4 build/partial.rdb |binary build/vignette.rds |only inst |only man/copy_param_hypervolume.Rd |only man/estimate_bandwidth.Rd | 30 - man/expectation_ball.Rd | 7 man/expectation_box.Rd | 7 man/expectation_convex.Rd | 7 man/get_centroid.Rd | 7 man/get_centroid_weighted.Rd |only man/hypervolume.Rd | 8 man/hypervolume_box.Rd | 7 man/hypervolume_distance.Rd | 12 man/hypervolume_estimate_probability.Rd | 34 - man/hypervolume_funnel.Rd |only man/hypervolume_gaussian.Rd | 13 man/hypervolume_general_model.Rd | 12 man/hypervolume_join.Rd | 15 man/hypervolume_n_occupancy.Rd |only man/hypervolume_n_occupancy_permute.Rd |only man/hypervolume_n_occupancy_test.Rd |only man/hypervolume_overlap_confidence.Rd |only man/hypervolume_overlap_statistics.Rd | 13 man/hypervolume_overlap_test.Rd |only man/hypervolume_permute.Rd |only man/hypervolume_project.Rd | 7 man/hypervolume_prune.Rd | 22 man/hypervolume_resample.Rd |only man/hypervolume_save_animated_gif.Rd | 21 man/hypervolume_segment.Rd | 18 man/hypervolume_set.Rd | 34 - man/hypervolume_set_n_intersection.Rd |only man/hypervolume_svm.Rd | 8 man/hypervolume_thin.Rd | 12 man/hypervolume_threshold.Rd | 12 man/hypervolume_variable_importance.Rd | 11 man/padded_range.Rd | 13 man/plot.Hypervolume.Rd | 24 man/to_hv_list.Rd |only man/weight_data.Rd | 18 src/KDTree.h | 18 src/RcppExports.cpp | 5 vignettes |only 71 files changed, 1101 insertions(+), 736 deletions(-)
Title: Wrapper Functions for 'ODAM' (Open Data for Access and Mining)
Web Services
Description: 'ODAM' (Open Data for Access and Mining) is a framework that implements a simple way to make research data broadly accessible and fully available for reuse, including by a script language such as R. The main purpose is to make a data set accessible online with a minimal effort from the data provider, and to allow any scientists or bioinformaticians to be able to explore the data set and then extract a subpart or the totality of the data according to their needs. The Rodam package has only one class, 'odamws', that provides methods to allow you to retrieve online data using 'ODAM' Web Services. This obviously requires that data are implemented according the 'ODAM' approach , namely that the data subsets were deposited in the suitable data repository in the form of TSV files associated with their metadata also described in TSV files. See <https://inrae.github.io/ODAM/>.
Author: Daniel Jacob [cre, aut] (<https://orcid.org/0000-0002-6687-7169>)
Maintainer: Daniel Jacob <daniel.jacob@inrae.fr>
Diff between Rodam versions 0.1.10 dated 2021-10-26 and 0.1.12 dated 2021-11-12
DESCRIPTION | 8 ++--- MD5 | 8 ++--- R/odamws.R | 75 +++++++++++++++++++++++++--------------------------- inst/doc/Rodam.html | 6 ++-- man/odamws.Rd | 8 ++--- 5 files changed, 52 insertions(+), 53 deletions(-)
Title: Spatial Seemingly Unrelated Regression Models
Description: A collection of functions to test and estimate Seemingly
Unrelated Regression (usually called SUR) models, with spatial structure, by maximum
likelihood and three-stage least squares. The package estimates the
most common spatial specifications, that is, SUR with Spatial Lag of
X regressors (called SUR-SLX), SUR with Spatial Lag Model (called SUR-SLM),
SUR with Spatial Error Model (called SUR-SEM), SUR with Spatial Durbin Model (called SUR-SDM),
SUR with Spatial Durbin Error Model (called SUR-SDEM),
SUR with Spatial Autoregressive terms and Spatial Autoregressive
Disturbances (called SUR-SARAR), SUR-SARAR with Spatial Lag of X
regressors (called SUR-GNM) and SUR with Spatially Independent Model (called SUR-SIM).
The methodology of these models can be found in next references
Mur, J., Lopez, F., and Herrera, M. (2010) <doi:10.1080/17421772.2010.516443>
Lopez, F.A., Mur, J., and Angulo, A. (2014) <doi:10.1007/s00168-014-0624-2>.
Author: Ana Angulo [aut],
Fernando A Lopez [aut],
Roman Minguez [aut, cre],
Jesus Mur [aut]
Maintainer: Roman Minguez <roman.minguez@uclm.es>
Diff between spsur versions 1.0.1.9 dated 2021-06-25 and 1.0.2.0 dated 2021-11-12
DESCRIPTION | 24 ++++++++++++------------ MD5 | 14 +++++++------- NAMESPACE | 2 +- R/cov_spsur_f.R | 8 ++++---- R/spSUR-package.R | 4 ++-- build/vignette.rds |binary inst/doc/Vignette_User_Guide.html | 4 ++-- inst/doc/spsur-vs-spatialreg.html | 2 +- 8 files changed, 29 insertions(+), 29 deletions(-)
Title: Infrastructure for Computing with Basis Functions
Description: Some very simple infrastructure for basis functions.
Author: Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>)
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>
Diff between basefun versions 1.1-0 dated 2021-03-09 and 1.1-1 dated 2021-11-12
DESCRIPTION | 9 +++++---- MD5 | 8 ++++---- R/Bernstein.R | 13 ++++++++++--- inst/NEWS.Rd | 11 ++++++++++- man/Bernstein_basis.Rd | 36 ++++++++++++++++++++++++++++++++---- 5 files changed, 61 insertions(+), 16 deletions(-)
Title: Meta-Analysis of Generalized Additive Models
Description: Meta-analysis of generalized additive
models and generalized additive mixed models. A typical use case is
when data cannot be shared across locations, and an overall meta-analytic
fit is sought. 'metagam' provides functionality for removing individual
participant data from models computed using the 'mgcv' and 'gamm4' packages such
that the model objects can be shared without exposing individual data.
Furthermore, methods for meta-analysing these fits are provided. The implemented
methods are described in Sorensen et al. (2020), <doi:10.1016/j.neuroimage.2020.117416>,
extending previous works by Schwartz and Zanobetti (2000)
and Crippa et al. (2018) <doi:10.6000/1929-6029.2018.07.02.1>.
Author: Oystein Sorensen [aut, cre] (<https://orcid.org/0000-0003-0724-3542>),
Andreas M. Brandmaier [aut] (<https://orcid.org/0000-0001-8765-6982>),
Athanasia Mo Mowinckel [aut] (<https://orcid.org/0000-0002-5756-0223>)
Maintainer: Oystein Sorensen <oystein.sorensen@psykologi.uio.no>
Diff between metagam versions 0.2.0 dated 2020-11-12 and 0.3.0 dated 2021-11-12
DESCRIPTION | 17 - MD5 | 76 +++--- NAMESPACE | 1 R/metagam.R | 186 ++++++++------- R/metagam_package.R | 11 R/misc.R |only R/plot_dominance.R | 8 R/plot_heterogeneity.R | 18 - R/plot_metagam.R | 4 R/print_metagam.R | 18 - R/strip_rawdata.R | 15 - R/summary_metagam.R | 29 -- README.md | 54 +--- build/vignette.rds |binary inst/REFERENCES.bib | 27 ++ inst/doc/dominance.R | 6 inst/doc/dominance.Rmd | 6 inst/doc/dominance.html | 294 ++---------------------- inst/doc/heterogeneity.R | 5 inst/doc/heterogeneity.Rmd | 7 inst/doc/heterogeneity.html | 342 +++++----------------------- inst/doc/introduction.Rmd | 2 inst/doc/introduction.html | 424 ++++++++--------------------------- inst/doc/multivariate.R | 3 inst/doc/multivariate.Rmd | 5 inst/doc/multivariate.html | 434 ++++++++---------------------------- inst/doc/pvals.R |only inst/doc/pvals.Rmd |only inst/doc/pvals.html |only inst/examples/metagam_examples.R | 11 man/getmasd.Rd |only man/metagam.Rd | 19 - man/plot.metagam.Rd | 11 man/strip_rawdata.Rd | 11 man/summary.metagam.Rd | 3 tests/testdata |only tests/testthat/test-strip_rawdata.R | 12 vignettes/dominance.Rmd | 6 vignettes/figures |only vignettes/heterogeneity.Rmd | 7 vignettes/introduction.Rmd | 2 vignettes/multivariate.Rmd | 5 vignettes/pvals.Rmd |only 43 files changed, 564 insertions(+), 1515 deletions(-)
Title: A Flexible Class for Messy Dates
Description: Contains a set of tools for constructing and coercing
into and from the messydt class.
This date class implements ISO 8601-2:2019(E) and
allows regular dates to be annotated
to express unspecified date components,
approximate or uncertain date components,
date ranges, and sets of dates.
This is useful for describing and analysing temporal information,
whether historical or recent, where date precision may vary.
Author: James Hollway [cre, aut, ctb] (IHEID,
<https://orcid.org/0000-0002-8361-9647>),
Henrique Sposito [ctb] (IHEID, <https://orcid.org/0000-0003-3420-6085>),
Jael Tan [ctb] (IHEID, <https://orcid.org/0000-0002-6234-9764>)
Maintainer: James Hollway <james.hollway@graduateinstitute.ch>
Diff between messydates versions 0.1.1 dated 2021-07-19 and 0.2.0 dated 2021-11-12
DESCRIPTION | 23 +++-- MD5 | 64 ++++++++----- NAMESPACE | 9 + NEWS.md | 36 +++++++ R/annotate.R |only R/battles.R |only R/class.R | 9 + R/coerce_from_messydate.R | 3 R/coerce_to_messydate.R | 84 +++++++++++------- R/contract.R | 61 ++++++------- R/expand.R | 161 +++++++++++++++++++++++++---------- R/extract.R | 37 +++----- R/logical.R | 6 - R/messydate_make.R | 8 + R/resequence.R |only R/resolve.R | 17 +++ README.md | 36 +++++-- data |only man/annotate.Rd |only man/as_messydate.Rd | 1 man/battles.Rd |only man/contract.Rd | 7 - man/expand.Rd | 25 +++-- man/extract.Rd | 10 +- man/figures/cheatsheet.pdf |only man/figures/cheatsheet.png |only man/interleave.Rd |only man/logical.Rd | 6 - man/make_messydate.Rd | 2 man/resequence.Rd |only man/resolve.Rd | 4 tests/testthat/test-annotate.R |only tests/testthat/test-coerce-from.R | 2 tests/testthat/test-contract.R | 14 ++- tests/testthat/test-expand.R | 14 ++- tests/testthat/test-extract.R | 9 + tests/testthat/test-messydate-make.R | 4 tests/testthat/test-resolve.R | 16 +-- tests/testthat/test_resequence.R |only 39 files changed, 448 insertions(+), 220 deletions(-)
Title: Methods for Analysing 'EQ-5D' Data and Calculating 'EQ-5D' Index
Scores
Description: EQ-5D is a popular health related quality of life instrument used
in the clinical and economic evaluation of health care. Developed by the
EuroQol group <https://euroqol.org/>, the instrument consists of two
components: health state description and evaluation. For the description
component a subject self-rates their health in terms of five dimensions;
mobility, self-care, usual activities, pain/discomfort, and
anxiety/depression using either a three-level (EQ-5D-3L,
<https://euroqol.org/eq-5d-instruments/eq-5d-3l-about/>) or a five-level
(EQ-5D-5L, <https://euroqol.org/eq-5d-instruments/eq-5d-5l-about/>)
scale. Frequently the scores on these five dimensions are converted to a
single utility index using country specific value sets, which can be used
in the clinical and economic evaluation of health care as well as in
population health surveys. The eq5d package provides methods to calculate
index scores from a subject's dimension scores. 29 TTO and 11 VAS EQ-5D-3L
value sets including those for countries in Szende et al (2007)
<doi:10.1007/1-4020-5511-0> and Szende et al (2014)
<doi:10.1007/978-94-007-7596-1>, 29 EQ-5D-5L EQ-VT value sets from the
EuroQol website, the EQ-5D-5L crosswalk value sets developed by
van Hout et al. (2012) <doi:10.1016/j.jval.2012.02.008>, the
crosswalk value set for Russia and reverse crosswalk value sets. Two
EQ-5D-Y value sets are also included. Methods are also included for the
analysis of EQ-5D profiles along with a shiny web tool to enable the
calculation, visualisation and automated statistical analysis of EQ-5D
data via a web browser using EQ-5D dimension scores stored in CSV or
Excel files.
Author: Fraser Morton [aut, cre],
Jagtar Singh Nijjar [aut]
Maintainer: Fraser Morton <fraser.morton@glasgow.ac.uk>
Diff between eq5d versions 0.10.0 dated 2021-07-27 and 0.10.1 dated 2021-11-12
DESCRIPTION | 10 ++-- MD5 | 41 ++++++++--------- NEWS.md | 8 +++ R/data.R | 2 R/eq5d.R | 78 ++++++++++++++++----------------- R/eq5d5l.R | 22 ++++----- R/eq5dcw.R | 22 ++++----- R/eq5drcw.R | 22 ++++----- R/eq5dy.R | 26 +++++------ R/sysdata.rda |only README.md | 30 ++++++------ data/vt.RData |binary inst/doc/eq5d.html | 101 ++++++++++--------------------------------- man/VT.Rd | 4 + man/eq5d-package.Rd | 26 ----------- man/eq5d.Rd | 22 ++++----- man/eq5d5l.Rd | 2 man/eq5dcw.Rd | 2 man/eq5drcw.Rd | 2 man/eq5dy.Rd | 2 man/valuesets.Rd | 2 tests/testthat/test-eq5d5l.R | 6 ++ 22 files changed, 186 insertions(+), 244 deletions(-)
Title: Loading Data from 'ActiveCampaign API v3'
Description: Interface for loading data from 'ActiveCampaign API v3'
<https://developers.activecampaign.com/reference>. Provide functions
for getting data by deals, contacts, accounts, campaigns and messages.
Author: Alexey Seleznev [aut, cre] (<https://orcid.org/0000-0003-0410-7385>),
Netpeak [cph]
Maintainer: Alexey Seleznev <selesnow@gmail.com>
Diff between ractivecampaign versions 0.1.1 dated 2021-09-30 and 0.2.0 dated 2021-11-12
DESCRIPTION | 8 ++-- MD5 | 53 +++++++++++++++----------- NAMESPACE | 5 ++ NEWS.md | 10 +++++ R/ac_auth.R | 12 +++--- R/ac_get_accounts.R | 19 ++++++--- R/ac_get_campaigns.R | 15 +++++-- R/ac_get_campaigns_aggregate_revenues.R | 33 ++++++++++------ R/ac_get_campaigns_messages.R | 14 +++++-- R/ac_get_contact_tags.R |only R/ac_get_contacts.R | 60 +++++++++++++++--------------- R/ac_get_custom_account_fields.R | 16 ++++++-- R/ac_get_custom_account_fields_values.R | 18 ++++++--- R/ac_get_custom_contact_fields.R | 2 - R/ac_get_custom_contact_fields_values.R | 21 +++++++--- R/ac_get_custom_deal_fields.R | 15 +++++-- R/ac_get_custom_deal_fields_values.R | 2 - R/ac_get_deal_activities.R |only R/ac_get_deal_piplines.R | 23 ++++++++--- R/ac_get_deal_stages.R | 22 +++++++---- R/ac_get_deals.R | 63 ++++++++++++++++++-------------- R/ac_get_messages.R | 15 +++++-- R/ac_get_tags.R |only R/ac_get_users.R |only R/zzz.R | 16 ++++++++ README.md | 27 +++++++++++++ man/ac_auth.Rd | 4 +- man/ac_get_contact_tags.Rd |only man/ac_get_deal_activities.Rd |only man/ac_get_tags.Rd |only man/ac_get_users.Rd |only man/figures/demo_plot_1.png |only 32 files changed, 318 insertions(+), 155 deletions(-)
More information about ractivecampaign at CRAN
Permanent link
Title: Fast Kalman Filtering Through Sequential Processing
Description: Fast and flexible Kalman filtering implementation utilizing sequential processing, designed for efficient parameter estimation through maximum likelihood estimation. Sequential processing is a univariate treatment of a multivariate series of observations and can benefit from computational efficiency over traditional Kalman filtering when independence is assumed in the variance of the disturbances of the measurement equation. Sequential processing is described in the textbook of Durbin and Koopman (2001, ISBN:978-0-19-964117-8). 'FKF.SP' was built upon the existing 'FKF' package and is, in general, a faster Kalman filter.
Author: Thomas Aspinall [aut, cre] (<https://orcid.org/0000-0002-6968-1989>),
Adrian Gepp [aut] (<https://orcid.org/0000-0003-1666-5501>),
Geoff Harris [aut] (<https://orcid.org/0000-0003-4284-8619>),
Simone Kelly [aut] (<https://orcid.org/0000-0002-6528-8557>),
Colette Southam [aut] (<https://orcid.org/0000-0001-7263-2347>),
Bruce Vanstone [aut] (<https://orcid.org/0000-0002-3977-2468>),
David Luethi [ctb],
Philipp Erb [ctb],
Simon Otziger [ctb],
Paul Smith [ctb] (<https://orcid.org/0000-0002-0034-3412>)
Maintainer: Thomas Aspinall <tomaspinall2512@gmail.com>
Diff between FKF.SP versions 0.1.2 dated 2021-05-04 and 0.1.3 dated 2021-11-12
DESCRIPTION | 8 ++++---- MD5 | 12 ++++++------ NEWS.md | 4 ++++ build/FKF.SP.pdf |binary build/vignette.rds |binary inst/doc/FKFSP.html | 21 ++++++++++++++------- src/fkf_SP.c | 34 +++++++++++++++++++--------------- 7 files changed, 47 insertions(+), 32 deletions(-)
Title: A Tidy Tool for Phylogenetic Tree Data Manipulation
Description: Phylogenetic tree generally contains multiple components including node, edge, branch and associated data. 'tidytree' provides an approach to convert tree object to tidy data frame as well as provides tidy interfaces to manipulate tree data.
Author: Guangchuang Yu [aut, cre, cph]
(<https://orcid.org/0000-0002-6485-8781>),
Bradley Jones [ctb],
Zebulun Arendsee [ctb]
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>
Diff between tidytree versions 0.3.5 dated 2021-09-08 and 0.3.6 dated 2021-11-12
DESCRIPTION | 13 ++---- MD5 | 16 +++---- NAMESPACE | 1 NEWS.md | 4 + R/left-join.R | 4 - R/show.R | 73 ++++++++++++++++++++++-------------- R/tidy_utilities.R | 2 inst/doc/tidytree.html | 4 - tests/testthat/test-dplyr-methods.R | 9 +--- 9 files changed, 72 insertions(+), 54 deletions(-)
Title: Automated Retrieval of ACLED Conflict Event Data
Description: Access and manage the application programming interface (API) of the Armed Conflict Location & Event Data Project (ACLED) at <https://acleddata.com/>. The package makes it easy to retrieve a user-defined sample (or all of the available data) of ACLED, enabling a seamless integration of regular data updates into the research work flow. It requires a minimal number of dependencies. See the package's README file for a note on replicability when drawing on ACLED data. When using this package, you acknowledge that you have read ACLED's terms and conditions of use, and that you agree with their attribution requirements.
Author: Christoph Dworschak [aut, cre]
(<https://orcid.org/0000-0003-0196-9545>),
Rob Williams [ctb] (<https://orcid.org/0000-0001-9259-3883>)
Maintainer: Christoph Dworschak <dworschak@posteo.de>
Diff between acled.api versions 1.1.4 dated 2021-09-19 and 1.1.5 dated 2021-11-12
DESCRIPTION | 9 +- MD5 | 10 +- NEWS.md | 5 + R/acled.api.internal.R | 2 README.md | 38 ++++----- tests/testthat/test-acled.R | 182 -------------------------------------------- 6 files changed, 37 insertions(+), 209 deletions(-)
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2020-11-30 2.0.1
2020-04-07 2.0.0
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2020-05-11 3.6.3
2019-11-30 3.6.0
2019-01-30 3.4.10
2018-08-15 3.4.9
2018-08-14 3.4.8
2017-01-28 3.3.10
2015-10-01 3.3.1
2014-12-11 1.0-9102
2014-07-29 1.0-8877
2014-07-16 1.0-8847
2014-06-30 1.0-8809
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2021-10-05 1.1.1
2021-05-12 1.1.0
2020-12-07 1.0.0
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2019-07-28 0.1.4
Title: Board Game Graphics
Description: Functions to make board game graphics. Specializes in game diagrams, animations, and "Print & Play" layouts for the 'piecepack' <https://www.ludism.org/ppwiki> but can make graphics for other board game systems. Includes configurations for several public domain game systems.
Author: Trevor L Davis [aut, cre],
Delapouite <https://delapouite.com/> [dtc] (Meeple shape extracted from
"Meeple icon" <https://game-icons.net/1x1/delapouite/meeple.html> /
"CC BY 3.0" <https://creativecommons.org/licenses/by/3.0/>)
Maintainer: Trevor L Davis <trevor.l.davis@gmail.com>
Diff between piecepackr versions 1.8.1 dated 2021-08-11 and 1.9.1 dated 2021-11-12
DESCRIPTION | 11 MD5 | 52 - NAMESPACE | 1 NEWS.md | 23 R/game_systems.R | 113 ++- R/piece_mesh-rayvertex.R |only R/pp_cfg.R | 17 R/render_piece.R | 36 - R/save_piece_obj.R | 7 R/sysdata.rda |binary R/utils-boards.R | 164 ++++ R/utils-composite.R | 22 R/utils-opt.R | 2 R/utils-pips.R | 89 +- README.md | 42 + man/figures/README-dominoes-1.png |binary man/figures/README-rayvertex-1.png |only man/game_systems.Rd | 20 man/obj_fns.Rd | 7 man/piece_mesh.Rd |only man/render_piece.Rd | 13 tests/testthat/_snaps/game_systems/alquerque.svg |only tests/testthat/_snaps/game_systems/dominoes.svg | 636 +++++++++++++------ tests/testthat/_snaps/game_systems/nine-morris.svg |only tests/testthat/_snaps/game_systems/seven-morris.svg |only tests/testthat/_snaps/game_systems/six-morris.svg |only tests/testthat/_snaps/game_systems/three-morris.svg |only tests/testthat/_snaps/game_systems/twelve-morris.svg |only tests/testthat/_snaps/game_systems/two-morris.svg |only tests/testthat/test-game_systems.R | 38 + tests/testthat/test-obj.R | 21 tests/testthat/test-render_piece.R | 9 32 files changed, 1008 insertions(+), 315 deletions(-)
Title: Utilities for Importing Data from Plain Text Accounting Files
Description: Utilities for querying plain text accounting files from 'Ledger', 'HLedger', and 'Beancount'.
Author: Trevor L Davis [aut, cre],
Jenya Sovetkin [ctb],
Chris Lloyd [ctb]
Maintainer: Trevor L Davis <trevor.l.davis@gmail.com>
Diff between ledger versions 2.0.7 dated 2020-05-18 and 2.0.9 dated 2021-11-12
DESCRIPTION | 16 MD5 | 19 NAMESPACE | 5 NEWS.md | 7 R/register.r | 13 R/zzz.R |only README.md | 676 +++++++++++++------------------ inst/extdata/example.hledger | 4 man/figures/README-income_chart-1.png |binary man/figures/README-net_worth_chart-1.png |binary tests/testthat/test-ledger.R | 29 - 11 files changed, 337 insertions(+), 432 deletions(-)
Title: Species Distribution Modelling
Description: An extensible framework for developing species distribution
models using individual and community-based approaches, generate ensembles of
models, evaluate the models, and predict species potential distributions in
space and time. For more information, please check the following paper:
Naimi, B., Araujo, M.B. (2016) <doi:10.1111/ecog.01881>.
Author: Babak Naimi, Miguel B. Araujo
Maintainer: Babak Naimi <naimi.b@gmail.com>
Diff between sdm versions 1.0-89 dated 2020-04-29 and 1.1-8 dated 2021-11-12
DESCRIPTION | 12 - MD5 | 98 +++++++-------- R/AAAClasses.R | 38 ++++- R/arithm.R | 5 R/ensemble.R | 24 ++- R/evaluates.R | 91 +++++++++++++- R/gui.R | 10 - R/installAll.R | 9 - R/modelFrame.R | 234 +++++++++--------------------------- R/modelInfo.R | 47 ++++++- R/plot.R | 12 + R/sdm.R | 292 ++++++--------------------------------------- R/sdmData.R | 267 ++++++++++------------------------------- R/sdmFormula.R | 190 ++++++++++++++++++++++------- R/sdmMethods.R | 8 - R/show.R | 10 - R/subset.R | 8 - R/varImp.R | 9 - README.md | 12 + build/vignette.rds |binary inst/methods/sdm/gam.R | 13 +- inst/methods/sdm/glmp.R |only inst/methods/sdm/ranger.R |only inst/methods/sdm/svm.R | 14 +- man/add.Rd | 4 man/arithm.Rd | 4 man/as.data.frame.Rd | 4 man/boxplot.Rd | 4 man/calibration.Rd | 4 man/coordinates.Rd | 4 man/density.Rd | 4 man/ensemble.Rd | 4 man/evaluates.Rd | 75 ++++++++++- man/extractIndex.Rd | 4 man/featuresFrame-class.Rd | 4 man/getModelInfo.Rd | 20 ++- man/gui.Rd | 4 man/installAll.Rd | 4 man/names.Rd | 4 man/niche.Rd | 7 - man/predict.Rd | 4 man/read.sdm.Rd | 4 man/response.Rd | 4 man/roc.Rd | 4 man/sdm.Rd | 4 man/sdmData.Rd | 4 man/sdmModel-class.Rd | 4 man/sdmSetting.Rd | 4 man/sdmdata-class.Rd | 4 man/subset.Rd | 4 man/varImportance.Rd | 4 51 files changed, 749 insertions(+), 852 deletions(-)
Title: Data Menu for Radiant: Business Analytics using R and Shiny
Description: The Radiant Data menu includes interfaces for loading, saving,
viewing, visualizing, summarizing, transforming, and combining data. It also
contains functionality to generate reproducible reports of the analyses
conducted in the application.
Author: Vincent Nijs [aut, cre]
Maintainer: Vincent Nijs <radiant@rady.ucsd.edu>
Diff between radiant.data versions 1.3.12 dated 2020-11-27 and 1.4.1 dated 2021-11-12
DESCRIPTION | 28 ++++++------- MD5 | 66 +++++++++++++++---------------- NEWS.md | 7 ++- R/aaa.R | 2 R/combine.R | 2 R/explore.R | 27 ++++++------ R/manage.R | 2 R/pivotr.R | 22 +++++----- R/radiant.R | 40 +++++++++---------- R/transform.R | 10 ++-- R/view.R | 16 +++---- R/visualize.R | 68 +++++++++++++++++++++++++------- README.md | 13 +++--- inst/app/global.R | 31 ++++++++++---- inst/app/init.R | 4 - inst/app/radiant.R | 32 +++++++-------- inst/app/tools/app/about.md | 7 +-- inst/app/tools/app/help.R | 2 inst/app/tools/app/report_funs.R | 32 +++++++-------- inst/app/tools/app/report_r.R | 40 +++++++++---------- inst/app/tools/app/report_rmd.R | 40 +++++++++---------- inst/app/tools/app/state.R | 6 +- inst/app/tools/data/combine_ui.R | 8 +-- inst/app/tools/data/data_ui.R | 2 inst/app/tools/data/explore_ui.R | 24 +++++------ inst/app/tools/data/manage.R | 4 - inst/app/tools/data/manage_ui.R | 22 +++++----- inst/app/tools/data/pivotr_ui.R | 30 +++++++------- inst/app/tools/data/transform_ui.R | 74 +++++++++++++++++------------------ inst/app/tools/data/view_ui.R | 32 ++++++++------- inst/app/tools/data/visualize_ui.R | 77 ++++++++++++++++++++++--------------- inst/app/www/style.css | 42 ++++++++++++++++---- man/dtab.data.frame.Rd | 2 man/visualize.Rd | 2 34 files changed, 461 insertions(+), 355 deletions(-)
Title: Bayesian Screening and Variable Selection
Description: Performs Bayesian variable screening and selection for ultra-high dimensional linear regression models.
Author: Dongjin Li [aut, cre], Somak Dutta [aut], Vivekananda Roy [ctb]
Maintainer: Dongjin Li <liyangxiaobei@gmail.com>
Diff between bravo versions 2.1.1 dated 2021-10-25 and 2.1.2 dated 2021-11-12
DESCRIPTION | 8 ++++---- MD5 | 6 +++--- R/bits.r | 35 ++++++++++++++++++++--------------- man/bits.Rd | 34 ++++++++++++++++++++-------------- 4 files changed, 47 insertions(+), 36 deletions(-)