Title: Fit Continuous-Time State-Space Models for Filtering Argos
Satellite (and Other) Telemetry Data
Description: Fits continuous-time random walk and correlated random walk state-space models to filter Argos satellite location data. Template Model Builder ('TMB') is used for fast estimation. The Argos data can be: (older) least squares-based locations; (newer) Kalman filter-based locations with error ellipse information; or a mixture of both. Separate measurement models are used for these two data types. The models estimate two sets of location states corresponding to: 1) each observation, which are (usually) irregularly timed; and 2) user-specified time intervals (regular or irregular). Jonsen I, McMahon CR, Patterson TA, Auger-Methe M, Harcourt R, Hindell MA, Bestley S (2019) Movement responses to environment: fast inference of variation among southern elephant seals with a mixed effects model. Ecology 100:e02566 <doi:10.1002/ecy.2566>.
Author: Ian Jonsen [aut, cre],
Toby Patterson [aut, ctb]
Maintainer: Ian Jonsen <ian.jonsen@mq.edu.au>
Diff between foieGras versions 0.2.1 dated 2019-04-04 and 0.2.2 dated 2019-07-03
DESCRIPTION | 6 +++--- MD5 | 18 +++++++++--------- NEWS.md | 4 ++++ R/fit_ssm.R | 7 ++++--- R/prefilter.R | 6 +++--- README.md | 1 + build/vignette.rds |binary data/fit.RData |binary inst/doc/foiegras-basics.html | 22 +++++++++++----------- tests/testthat/test-prefilter.R | 3 +++ 10 files changed, 38 insertions(+), 29 deletions(-)
Title: Expokit in R
Description: An R-interface to the Fortran package Expokit.
Author: Roger B. Sidje [aut, cph],
Niels Richard Hansen [aut, cre, cph]
Maintainer: Niels Richard Hansen <Niels.R.Hansen@math.ku.dk>
Diff between expoRkit versions 0.9.2 dated 2018-05-06 and 0.9.4 dated 2019-07-03
DESCRIPTION | 27 ++++---- MD5 | 28 ++++---- NAMESPACE | 5 + R/data.R | 5 - R/expoRkit-package.R | 7 +- R/expoRkit.R | 2 R/expv.R | 8 +- README.md | 13 +-- man/Rexpv.Rd | 130 ++++++++++++++++++--------------------- man/expoRkit.Rd | 57 +++++++++-------- man/expv-methods.Rd | 170 ++++++++++++++++++++++++--------------------------- man/orani.Rd | 28 ++++---- man/padm.Rd | 42 ++++++------ src/Rinterface.f | 4 - src/expokit.f | 158 ++++++++++++++++++++++++++--------------------- 15 files changed, 347 insertions(+), 337 deletions(-)
Title: Functions for Hierarchical Bayesian Estimation: A Flexible
Approach
Description: Functions for estimating models using a Hierarchical Bayesian (HB) framework. The flexibility comes in allowing the user to specify the likelihood function directly instead of assuming predetermined model structures. Types of models that can be estimated with this code include the family of discrete choice models (Multinomial Logit, Mixed Logit, Nested Logit, Error Components Logit and Latent Class) as well ordered response models like ordered probit and ordered logit. In addition, the package allows for flexibility in specifying parameters as either fixed (non-varying across individuals) or random with continuous distributions. Parameter distributions supported include normal, positive/negative log-normal, positive/negative censored normal, and the Johnson SB distribution. Kenneth Train's Matlab and Gauss code for doing Hierarchical Bayesian estimation has served as the basis for a few of the functions included in this package. These Matlab/Gauss functions have been rewritten to be optimized within R. Considerable code has been added to increase the flexibility and usability of the code base. Train's original Gauss and Matlab code can be found here: <http://elsa.berkeley.edu/Software/abstracts/train1006mxlhb.html> See Train's chapter on HB in Discrete Choice with Simulation here: <http://elsa.berkeley.edu/books/choice2.html>; and his paper on using HB with non-normal distributions here: <http://eml.berkeley.edu//~train/trainsonnier.pdf>. The authors would also like to thank the invaluable contributions of Stephane Hess and the Choice Modelling Centre: <https://cmc.leeds.ac.uk/>.
Author: Jeff Dumont [aut, cre],
Jeff Keller [aut],
Chase Carpenter [ctb]
Maintainer: Jeff Dumont <Jeff.Dumont@rsginc.com>
Diff between RSGHB versions 1.2.1 dated 2019-01-06 and 1.2.2 dated 2019-07-03
DESCRIPTION | 8 ++++---- MD5 | 18 +++++++++--------- NEWS | 3 +++ R/doHB.R | 2 +- R/hb.R | 9 +++++---- build/vignette.rds |binary inst/doc/RSGHB_HowTo.pdf |binary man/doHB.Rd | 4 ---- man/plot.Rd | 2 -- man/writeModel.Rd | 4 ---- 10 files changed, 22 insertions(+), 28 deletions(-)
Title: Gene Set Analysis Toolkit WebGestaltR
Description: The web version WebGestalt <http://www.webgestalt.org> supports 12 organisms, 354 gene identifiers and 321,251 function categories. Users can upload the data and functional categories with their own gene identifiers. In addition to the Over-Representation Analysis, WebGestalt also supports Gene Set Enrichment Analysis and Network Topology Analysis. The user-friendly output report allows interactive and efficient exploration of enrichment results. The WebGestaltR package not only supports all above functions but also can be integrated into other pipeline or simultaneously analyze multiple gene lists.
Author: Jing Wang [aut],
Yuxing Liao [aut, cre],
Eric Jaehnig [ctb],
Zhiao Shi [ctb],
Quanhu Sheng [ctb]
Maintainer: Yuxing Liao <yuxingliao@gmail.com>
Diff between WebGestaltR versions 0.4.0 dated 2019-04-27 and 0.4.1 dated 2019-07-03
DESCRIPTION | 19 ++++++-- MD5 | 78 ++++++++++++++++++------------------ R/WebGestaltR.R | 23 ++++++---- R/WebGestaltRBatch.R | 2 R/WebGestaltRGsea.R | 10 ++-- R/WebGestaltRNta.R | 8 +-- R/WebGestaltROra.R | 12 ++--- R/cacheFile.R |only R/createReport.R | 21 ++++++--- R/errorMessage.R | 16 +++---- R/goSlimSummary.R | 6 +- R/gseaEnrichment.R | 4 - R/idMapping.R | 14 +++--- R/idMappingUtils.R | 8 +-- R/idToSymbol.R | 4 - R/listArchiveURL.R | 44 ++++++++++---------- R/listGeneSet.R | 6 +- R/listIdType.R | 64 ++++++++++++++--------------- R/listOrganism.R | 6 +- R/listReferenceSet.R | 50 +++++++++++------------ R/loadGeneList.R | 22 +++++----- R/loadGeneSet.R | 48 +++++++++++++++++----- R/oraEnrichment.R | 2 R/randomWalkEnrichment.R | 8 +-- R/readGmt.R | 9 ++-- R/summaryDescription.R | 8 +-- README.md | 2 inst/templates/ntaTemplate.mustache | 1 inst/templates/template.mustache | 1 man/WebGestaltR.Rd | 4 + man/cacheUrl.Rd |only man/goSlimSummary.Rd | 4 + man/idMapping.Rd | 6 +- man/listGeneSet.Rd | 4 + man/listIdType.Rd | 4 + man/listOrganism.Rd | 4 + man/listReferenceSet.Rd | 4 + man/loadGeneSet.Rd | 4 + man/readGmt.Rd | 4 + man/specificParameterSummaryOra.Rd | 2 man/summaryDescription.Rd | 3 - 41 files changed, 303 insertions(+), 236 deletions(-)
Title: Lilliefors-Corrected Kolmogorov-Smirnov Goodness-of-Fit Tests
Description: Implements the Lilliefors-corrected Kolmogorov-Smirnov test for use
in goodness-of-fit tests, suitable when population parameters are unknown and
must be estimated by sample statistics. P-values are estimated by simulation.
Can be used with a variety of continuous distributions, including normal,
lognormal, univariate mixtures of normals, uniform, loguniform, exponential,
gamma, and Weibull distributions. Functions to generate random numbers and
calculate density, distribution, and quantile functions are provided for use
with the log uniform and mixture distributions.
Author: Phil Novack-Gottshall, Steve C. Wang
Maintainer: Phil Novack-Gottshall <pnovack-gottshall@ben.edu>
Diff between KScorrect versions 1.2.4 dated 2018-08-14 and 1.4.0 dated 2019-07-03
DESCRIPTION | 16 + MD5 | 20 +- NAMESPACE | 6 NEWS.md | 17 + R/LcKS.R | 467 ++++++++++++++++++++++++++++++++-------------------- R/dmixnorm.R | 12 - R/ks_test_stat.R |only R/qmixnorm.R | 4 README.md | 4 man/LcKS.Rd | 136 +++++++++------ man/dmixnorm.Rd | 12 - man/ks_test_stat.Rd |only 12 files changed, 430 insertions(+), 264 deletions(-)
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2018-03-30 1.1.2
2017-03-03 1.1.1
2016-08-10 1.0
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2018-04-04 0.3.6
2018-02-21 0.3.5
2017-10-04 0.3.2
2017-06-30 0.3.1
2017-06-25 0.3
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2018-09-13 1.2.0
2018-05-27 1.0.3
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2018-07-21 0.2.1
2017-07-26 0.2.0
2017-06-12 0.1.0
Title: A Stable Isotope Mixing Model
Description: Fits Stable Isotope Mixing Models (SIMMs) and is meant as a longer term replacement to the previous widely-used package SIAR. SIMMs are used to infer dietary proportions of organisms consuming various food sources from observations on the stable isotope values taken from the organisms' tissue samples. However SIMMs can also be used in other scenarios, such as in sediment mixing or the composition of fatty acids. The main functions are simmr_load and simmr_mcmc. The two vignettes contain a quick start and a full listing of all the features. The methods used are detailed in the papers Parnell et al 2010 <doi:10.1371/journal.pone.0009672>, and Parnell et al 2013 <doi:10.1002/env.2221>.
Author: Andrew Parnell
Maintainer: Andrew Parnell <andrew.parnell@mu.ie>
Diff between simmr versions 0.4.0 dated 2019-06-14 and 0.4.1 dated 2019-07-03
DESCRIPTION | 14 - MD5 | 58 +++-- NEWS.md | 8 R/combine_sources.R | 8 R/compare_groups.R | 13 - R/data.R |only R/plot.simmr_output.R | 7 R/print.simmr_output.R | 11 - R/prior_viz.simmr_output.R | 110 +++++----- R/simmr.R | 14 - R/simmr_elicit.R | 8 R/simmr_mcmc_tdf.R | 3 R/summary.simmr_output_tdf.R | 47 +++- build/vignette.rds |binary data |only inst/doc/quick_start.html | 67 +++--- inst/doc/simmr.R | 6 inst/doc/simmr.Rmd | 12 - inst/doc/simmr.html | 398 +++++++++++++++++++------------------- inst/extdata/geese_data.xls |binary inst/extdata/geese_data_small.xls |only man/geese_data.Rd |only man/geese_data_day1.Rd |only man/plot.simmr_output.Rd | 2 man/simmr.Rd | 14 - man/simmr_data_1.Rd |only man/simmr_data_2.Rd |only man/simmr_elicit.Rd | 7 man/simmr_mcmc_tdf.Rd | 3 man/square_data.Rd |only man/summary.simmr_output_tdf.Rd | 47 +++- vignettes/simmr.Rmd | 12 - 32 files changed, 490 insertions(+), 379 deletions(-)
Title: Univariate Bootstrapping and Other Things
Description: Primarily devoted to implementing the Univariate Bootstrap (as well as the Traditional Bootstrap). In addition there are multiple functions for DeFries-Fulker behavioral genetics models. The univariate bootstrapping functions, DeFries-Fulker functions, regression and traditional bootstrapping functions form the original core. Additional features may come online later, however this software is a work in progress. For more information about univariate bootstrapping see: Lee and Rodgers (1998) and Beasley et al (2007) <doi.org/10.1037/1082-989X.12.4.414>.
Author: Patrick O'Keefe
Maintainer: Patrick O'Keefe <patrick.okeefe@vanderbilt.edu>
Diff between Omisc versions 0.1.1 dated 2019-04-19 and 0.1.2 dated 2019-07-03
DESCRIPTION | 6 +++--- MD5 | 26 +++++++++++++------------- R/BCa.R | 37 ++++++++++++++++++++----------------- R/NaiveBoot.R | 2 +- R/bootAnalysis.R | 2 +- R/bootsample.R | 2 +- R/lbind.R | 4 ++-- R/standardBootIntervals.R | 4 ++-- R/uniboot.R | 9 ++++----- man/BCa.Rd | 10 +++++----- man/bootAnalysis.Rd | 2 +- man/lbind.Rd | 4 ++-- man/standardBootIntervals.Rd | 2 +- man/uniboot.Rd | 2 +- 14 files changed, 57 insertions(+), 55 deletions(-)
Title: Market Matching and Causal Impact Inference
Description: For a given test market find the best control markets using time series matching and analyze the impact of an intervention. The intervention could be be a marketing event or some other local business tactic that is being tested. The workflow implemented in the Market Matching package utilizes dynamic time warping (the 'dtw' package) to do the matching and the 'CausalImpact' package to analyze the causal impact. In fact, this package can be considered a "workflow wrapper" for those two packages.
Author: Larsen Kim [aut, cre]
Maintainer: Larsen Kim <kblarsen4@gmail.com>
Diff between MarketMatching versions 1.1.1 dated 2018-11-14 and 1.1.2 dated 2019-07-03
DESCRIPTION | 12 MD5 | 18 - R/MarketMatching.R | 4 R/functions.R | 78 ++--- README.md | 12 build/vignette.rds |binary inst/doc/MarketMatching-Vignette.html | 517 ++++++++++++++++++++++++---------- man/MarketMatching.Rd | 8 man/best_matches.Rd | 2 man/inference.Rd | 5 10 files changed, 445 insertions(+), 211 deletions(-)
More information about MarketMatching at CRAN
Permanent link
Title: Age-Depth Modelling using Bayesian Statistics
Description: Bacon is an approach to age-depth modelling that uses Bayesian statistics to reconstruct accumulation histories for deposits, through combining radiocarbon and other dates with prior information. See Blaauw & Christen (2011) <doi:10.1214/11-BA618>.
Author: Maarten Blaauw [aut, cre],
J. Andres Christen [aut],
Judith Esquivel Vazquez [ctb],
Ted Belding [cph],
James Theiler [cph],
Brian Gough [cph],
Charles Karney [cph]
Maintainer: Maarten Blaauw <maarten.blaauw@qub.ac.uk>
Diff between rbacon versions 2.3.8 dated 2019-05-25 and 2.3.9.1 dated 2019-07-03
rbacon-2.3.8/rbacon/inst/extdata/Curves/mixed.14C |only rbacon-2.3.9.1/rbacon/DESCRIPTION | 8 rbacon-2.3.9.1/rbacon/MD5 | 67 +++--- rbacon-2.3.9.1/rbacon/NAMESPACE | 2 rbacon-2.3.9.1/rbacon/NEWS.md | 13 + rbacon-2.3.9.1/rbacon/R/Bacon.R | 121 ++++++----- rbacon-2.3.9.1/rbacon/R/MCMC.R | 6 rbacon-2.3.9.1/rbacon/R/accrate.R | 26 +- rbacon-2.3.9.1/rbacon/R/agedepth.R | 79 +++++-- rbacon-2.3.9.1/rbacon/R/calc.R | 227 +++++++++++++++------- rbacon-2.3.9.1/rbacon/R/calibrate.R | 66 +++--- rbacon-2.3.9.1/rbacon/R/internal_plots.R | 47 ++-- rbacon-2.3.9.1/rbacon/R/plots.R | 36 +-- rbacon-2.3.9.1/rbacon/R/read_write.R | 7 rbacon-2.3.9.1/rbacon/man/AgesOfEvents.Rd | 2 rbacon-2.3.9.1/rbacon/man/Bacon.Age.d.Rd | 7 rbacon-2.3.9.1/rbacon/man/Bacon.Rd | 14 - rbacon-2.3.9.1/rbacon/man/Bacon.hist.Rd | 2 rbacon-2.3.9.1/rbacon/man/Baconvergence.Rd | 2 rbacon-2.3.9.1/rbacon/man/accrate.age.Rd | 2 rbacon-2.3.9.1/rbacon/man/accrate.age.ghost.Rd | 4 rbacon-2.3.9.1/rbacon/man/accrate.depth.Rd | 2 rbacon-2.3.9.1/rbacon/man/accrate.depth.ghost.Rd | 4 rbacon-2.3.9.1/rbacon/man/add.dates.Rd | 2 rbacon-2.3.9.1/rbacon/man/age.pMC.Rd | 2 rbacon-2.3.9.1/rbacon/man/agedepth.Rd | 48 ++-- rbacon-2.3.9.1/rbacon/man/agemodel.it.Rd | 2 rbacon-2.3.9.1/rbacon/man/calib.plot.Rd | 17 + rbacon-2.3.9.1/rbacon/man/flux.age.ghost.Rd | 2 rbacon-2.3.9.1/rbacon/man/mix.curves.Rd | 4 rbacon-2.3.9.1/rbacon/man/pMC.age.Rd | 2 rbacon-2.3.9.1/rbacon/man/proxy.ghost.Rd | 2 rbacon-2.3.9.1/rbacon/man/scissors.Rd | 2 rbacon-2.3.9.1/rbacon/man/thinner.Rd | 2 rbacon-2.3.9.1/rbacon/src/cal.h | 2 35 files changed, 505 insertions(+), 326 deletions(-)
Title: Block Forests: Random Forests for Blocks of Clinical and Omics
Covariate Data
Description: A random forest variant 'block forest' ('BlockForest') tailored to the
prediction of binary, survival and continuous outcomes using block-structured
covariate data, for example, clinical covariates plus measurements of a certain
omics data type or multi-omics data, that is, data for which measurements of
different types of omics data and/or clinical data for each patient exist. Examples
of different omics data types include gene expression measurements, mutation data
and copy number variation measurements.
Block forest are presented in Hornung & Wright (2019). The package includes four
other random forest variants for multi-omics data: 'RandomBlock', 'BlockVarSel',
'VarProb', and 'SplitWeights'. These were also considered in Hornung & Wright (2019),
but performed worse than block forest in their comparison study based on 20 real
multi-omics data sets. Therefore, we recommend to use block forest ('BlockForest')
in applications. The other random forest variants can, however, be consulted for
academic purposes, for example, in the context of further methodological
developments.
Reference: Hornung, R. & Wright, M. N. (2019) Block Forests: random forests for blocks of clinical and omics covariate data. BMC Bioinformatics 20:358. <doi:10.1186/s12859-019-2942-y>.
Author: Roman Hornung, Marvin N. Wright
Maintainer: Marvin N. Wright <cran@wrig.de>
Diff between blockForest versions 0.2.0 dated 2019-04-10 and 0.2.3 dated 2019-07-03
DESCRIPTION | 16 +++++++--------- MD5 | 18 +++++++++--------- R/blockForest.R | 16 ++++++++-------- R/blockfor.R | 28 ++++++++++++++++++---------- R/importance.R | 2 +- R/predict.R | 2 +- man/blockForest.Rd | 16 ++++++++-------- man/blockfor.Rd | 28 ++++++++++++++++++---------- man/predict.blockForest.Rd | 2 +- src/Forest.cpp | 4 +++- 10 files changed, 74 insertions(+), 58 deletions(-)
Title: Non-Parametric Concordance Coefficient
Description: A non-parametric test for multi-observer concordance and
differences between concordances in (un)balanced data.
Author: Rowan Kuiper [cre, aut] (<https://orcid.org/0000-0002-3703-1762>),
Remco Hoogenboezem [aut],
Sjoerd Huisman [ctb] (<https://orcid.org/0000-0002-4322-8289>),
Pieter Sonneveld [ths],
Mark van Duin [ths]
Maintainer: Rowan Kuiper <r.kuiper.emc@gmail.com>
Diff between nopaco versions 1.0.4 dated 2019-06-26 and 1.0.5 dated 2019-07-03
DESCRIPTION | 16 ++++++++-------- MD5 | 20 ++++++++++---------- NEWS | 5 +++++ inst/CITATION | 4 ++-- inst/doc/nopaco.pdf |binary src/bootstrapCI.cpp | 38 ++++++++++++++------------------------ src/bootstrapCI.h | 6 ++++++ src/exactdistribution.cpp | 6 +----- src/exactdistribution.h | 3 --- src/getPsi.cpp | 7 +++---- src/getPsi.h | 3 --- 11 files changed, 49 insertions(+), 59 deletions(-)
Title: Import, Plot and Analyze Bathymetric and Topographic Data
Description: Import xyz data from the NOAA (National Oceanic and Atmospheric Administration, <http://www.noaa.gov>), GEBCO (General Bathymetric Chart of the Oceans, <http://www.gebco.net>) and other sources, plot xyz data to prepare publication-ready figures, analyze xyz data to extract transects, get depth / altitude based on geographical coordinates, or calculate z-constrained least-cost paths.
Author: Eric Pante, Benoit Simon-Bouhet, and Jean-Olivier Irisson
Maintainer: Benoit Simon-Bouhet <besibo@gmail.com>
Diff between marmap versions 1.0.2 dated 2018-10-15 and 1.0.3 dated 2019-07-03
DESCRIPTION | 8 MD5 | 28 +- R/space.pies.R | 504 +++++++++++++++++++++++++-------------------- build/vignette.rds |binary data/aleutians.rda |binary data/celt.rda |binary data/florida.rda |binary data/hawaii.rda |binary data/hawaii.sites.rda |binary data/irregular.rda |binary data/metallo.rda |binary data/nw.atlantic.coast.rda |binary data/nw.atlantic.rda |binary man/marmap.Rd | 4 man/subsetSQL.Rd | 6 15 files changed, 307 insertions(+), 243 deletions(-)
Title: Latent Variable Analysis
Description: Fit a variety of latent variable models, including confirmatory
factor analysis, structural equation modeling and latent growth curve models.
Author: Yves Rosseel [aut, cre] (<https://orcid.org/0000-0002-4129-4477>),
Terrence D. Jorgensen [aut] (<https://orcid.org/0000-0001-5111-6773>),
Daniel Oberski [ctb],
Jarrett Byrnes [ctb],
Leonard Vanbrabant [ctb],
Victoria Savalei [ctb],
Ed Merkle [ctb],
Michael Hallquist [ctb],
Mijke Rhemtulla [ctb],
Myrsini Katsikatsou [ctb],
Mariska Barendse [ctb],
Florian Scharf [ctb]
Maintainer: Yves Rosseel <Yves.Rosseel@UGent.be>
Diff between lavaan versions 0.6-3 dated 2018-09-22 and 0.6-4 dated 2019-07-03
lavaan-0.6-3/lavaan/R/xxx_twostep.R |only lavaan-0.6-3/lavaan/tests |only lavaan-0.6-4/lavaan/DESCRIPTION | 22 lavaan-0.6-4/lavaan/MD5 | 151 ++-- lavaan-0.6-4/lavaan/R/00class.R | 7 lavaan-0.6-4/lavaan/R/ctr_mplus2lavaan.R | 108 ++- lavaan-0.6-4/lavaan/R/lav_bootstrap.R | 8 lavaan-0.6-4/lavaan/R/lav_data.R | 143 ++++ lavaan-0.6-4/lavaan/R/lav_export.R | 3 lavaan-0.6-4/lavaan/R/lav_export_mplus.R | 17 lavaan-0.6-4/lavaan/R/lav_fit.R | 2 lavaan-0.6-4/lavaan/R/lav_fit_measures.R | 6 lavaan-0.6-4/lavaan/R/lav_fsr.R | 204 ++++-- lavaan-0.6-4/lavaan/R/lav_h1_implied.R | 18 lavaan-0.6-4/lavaan/R/lav_h1_logl.R | 5 lavaan-0.6-4/lavaan/R/lav_lavaanList_inspect.R | 82 ++ lavaan-0.6-4/lavaan/R/lav_lavaanList_methods.R | 1 lavaan-0.6-4/lavaan/R/lav_matrix.R | 8 lavaan-0.6-4/lavaan/R/lav_matrix_rotate.R |only lavaan-0.6-4/lavaan/R/lav_matrix_rotate_methods.R |only lavaan-0.6-4/lavaan/R/lav_matrix_rotate_utils.R |only lavaan-0.6-4/lavaan/R/lav_model.R | 37 + lavaan-0.6-4/lavaan/R/lav_model_compute.R | 47 + lavaan-0.6-4/lavaan/R/lav_model_efa.R |only lavaan-0.6-4/lavaan/R/lav_model_estimate.R | 30 lavaan-0.6-4/lavaan/R/lav_model_gradient.R | 1 lavaan-0.6-4/lavaan/R/lav_model_information.R | 6 lavaan-0.6-4/lavaan/R/lav_model_objective.R | 19 lavaan-0.6-4/lavaan/R/lav_model_vcov.R | 25 lavaan-0.6-4/lavaan/R/lav_mvnorm_cluster.R | 15 lavaan-0.6-4/lavaan/R/lav_nlminb_constr.R | 5 lavaan-0.6-4/lavaan/R/lav_object_generate.R | 3 lavaan-0.6-4/lavaan/R/lav_object_inspect.R | 709 +++++++++++++++++----- lavaan-0.6-4/lavaan/R/lav_object_methods.R | 114 ++- lavaan-0.6-4/lavaan/R/lav_object_print.R | 71 ++ lavaan-0.6-4/lavaan/R/lav_ols.R | 4 lavaan-0.6-4/lavaan/R/lav_options.R | 94 ++ lavaan-0.6-4/lavaan/R/lav_partable.R | 285 ++++++++ lavaan-0.6-4/lavaan/R/lav_partable_check.R | 5 lavaan-0.6-4/lavaan/R/lav_partable_constraints.R | 11 lavaan-0.6-4/lavaan/R/lav_partable_flat.R | 108 +++ lavaan-0.6-4/lavaan/R/lav_partable_labels.R | 3 lavaan-0.6-4/lavaan/R/lav_partable_merge.R | 34 - lavaan-0.6-4/lavaan/R/lav_partable_subset.R | 256 ++++++- lavaan-0.6-4/lavaan/R/lav_partable_unrestricted.R | 2 lavaan-0.6-4/lavaan/R/lav_partable_utils.R | 17 lavaan-0.6-4/lavaan/R/lav_partable_vnames.R | 42 + lavaan-0.6-4/lavaan/R/lav_predict.R | 385 ++++++++--- lavaan-0.6-4/lavaan/R/lav_print.R | 21 lavaan-0.6-4/lavaan/R/lav_representation_lisrel.R | 32 lavaan-0.6-4/lavaan/R/lav_residuals.R | 241 ++++++- lavaan-0.6-4/lavaan/R/lav_samplestats.R | 9 lavaan-0.6-4/lavaan/R/lav_simulate_old.R | 41 - lavaan-0.6-4/lavaan/R/lav_standardize.R | 108 ++- lavaan-0.6-4/lavaan/R/lav_start.R | 19 lavaan-0.6-4/lavaan/R/lav_syntax.R | 141 +++- lavaan-0.6-4/lavaan/R/lav_test_LRT.R | 6 lavaan-0.6-4/lavaan/R/lav_test_Wald.R | 2 lavaan-0.6-4/lavaan/R/lav_test_diff.R | 57 + lavaan-0.6-4/lavaan/R/lav_test_score.R | 91 ++ lavaan-0.6-4/lavaan/R/xxx_fsr.R | 379 ++++++----- lavaan-0.6-4/lavaan/R/xxx_lavaan.R | 243 ++++++- lavaan-0.6-4/lavaan/R/xxx_lavaanList.R | 7 lavaan-0.6-4/lavaan/R/xxx_sam.R |only lavaan-0.6-4/lavaan/man/cfa.Rd | 6 lavaan-0.6-4/lavaan/man/growth.Rd | 4 lavaan-0.6-4/lavaan/man/lavInspect.Rd | 94 ++ lavaan-0.6-4/lavaan/man/lavListInspect.Rd | 19 lavaan-0.6-4/lavaan/man/lavOptions.Rd | 42 + lavaan-0.6-4/lavaan/man/lavPredict.Rd | 21 lavaan-0.6-4/lavaan/man/lavResiduals.Rd | 30 lavaan-0.6-4/lavaan/man/lavTablesFit.Rd | 3 lavaan-0.6-4/lavaan/man/lavTestScore.Rd | 16 lavaan-0.6-4/lavaan/man/model.syntax.Rd | 48 + lavaan-0.6-4/lavaan/man/modificationIndices.Rd | 4 lavaan-0.6-4/lavaan/man/parameterEstimates.Rd | 5 lavaan-0.6-4/lavaan/man/sem.Rd | 6 lavaan-0.6-4/lavaan/man/standardizedSolution.Rd | 7 78 files changed, 3801 insertions(+), 1014 deletions(-)
Title: Create Tables from Different Types of Regression
Description: Create regression tables from generalized linear model(GLM), generalized estimating equation(GEE), generalized linear mixed-effects model(GLMM), Cox proportional hazards model, survey-weighted generalized linear model(svyglm) and survey-weighted Cox model results for publication.
Author: Jinseob Kim [aut, cre] (<https://orcid.org/0000-0002-9403-605X>),
Zarathu [cph, fnd]
Maintainer: Jinseob Kim <jinseob2kim@gmail.com>
Diff between jstable versions 0.8.3 dated 2019-06-19 and 0.8.4 dated 2019-07-03
DESCRIPTION | 8 ++++---- MD5 | 10 +++++----- NAMESPACE | 1 + NEWS.md | 4 ++++ R/forestcox.R | 21 ++++++++++++++++++--- inst/doc/jstable.html | 42 +++++++++++++++++++++--------------------- 6 files changed, 53 insertions(+), 33 deletions(-)
Title: Feature Extraction from Grouped Data
Description: An R6 implementation for calculating features from grouped data.
The output will be one row for each group.
This functionality is often needed in the feature extraction process of machine learning problems.
Very large datasets are supported, since data is only read into RAM when needed.
Calculation can be done in parallel and the process can be monitored.
Global error handling is supported.
Results are available in one final dataframe.
Author: Quay Au [aut, cre],
Clemens Stachl [ctb],
Ramona Schoedel [ctb],
Theresa Ullmann [ctb],
Andreas Hofheinz [ctb]
Maintainer: Quay Au <quayau@gmail.com>
Diff between fxtract versions 0.9.1 dated 2019-02-12 and 0.9.2 dated 2019-07-03
DESCRIPTION | 13 MD5 | 36 +- NAMESPACE | 1 NEWS.md | 3 R/dplyr_wrapper.R | 4 R/xtractor.R | 332 +++++++++++------------- README.md | 15 - build/vignette.rds |binary inst/doc/fxtract.R | 1 inst/doc/fxtract.Rmd | 5 inst/doc/fxtract.html | 15 - man/Xtractor.Rd | 8 tests/testthat/test_xtractor.R | 287 ++++++++++++++------ vignettes/fxtract.Rmd | 5 vignettes/tutorial/xtractor_basics.Rmd | 28 +- vignettes/tutorial/xtractor_error_handling.Rmd | 4 vignettes/tutorial/xtractor_preprocess_data.Rmd | 2 vignettes/tutorial/xtractor_setup_child.Rmd | 2 vignettes/tutorial/xtractor_update_data.Rmd | 2 19 files changed, 461 insertions(+), 302 deletions(-)
Title: Variable Importance Plots
Description: A general framework for constructing variable importance plots from
various types of machine learning models in R. Aside from some standard model-
specific variable importance measures, this package also provides model-
agnostic approaches that can be applied to any supervised learning algorithm.
These include an efficient permutation-based variable importance measure as
well as novel approaches based on partial dependence plots (PDPs) and
individual conditional expectation (ICE) curves which are described in
Greenwell et al. (2018) <arXiv:1805.04755>. An experimental method for
quantifying the relative strength of interaction effects is also included (see
the previous reference for details).
Author: Brandon Greenwell [aut, cre] (<https://orcid.org/0000-0002-8120-0084>),
Brad Boehmke [aut] (<https://orcid.org/0000-0002-3611-8516>),
Bernie Gray [aut] (<https://orcid.org/0000-0001-9190-6032>)
Maintainer: Brandon Greenwell <greenwell.brandon@gmail.com>
Diff between vip versions 0.1.2 dated 2018-09-30 and 0.1.3 dated 2019-07-03
vip-0.1.2/vip/tests |only vip-0.1.3/vip/DESCRIPTION | 36 - vip-0.1.3/vip/MD5 | 49 - vip-0.1.3/vip/NAMESPACE | 11 vip-0.1.3/vip/NEWS.md | 47 + vip-0.1.3/vip/R/add_sparklines.R |only vip-0.1.3/vip/R/get_predictions.R | 4 vip-0.1.3/vip/R/metrics.R | 43 + vip-0.1.3/vip/R/utils.R | 24 vip-0.1.3/vip/R/vi.R | 100 ++- vip-0.1.3/vip/R/vi_ice.R | 70 +- vip-0.1.3/vip/R/vi_model.R | 1029 ++++++++++++++++++++++++++++++------ vip-0.1.3/vip/R/vi_pdp.R | 74 +- vip-0.1.3/vip/R/vi_permute.R | 208 +++++-- vip-0.1.3/vip/R/vint.R | 54 + vip-0.1.3/vip/R/vip.R | 63 ++ vip-0.1.3/vip/README.md | 11 vip-0.1.3/vip/man/add_sparklines.Rd |only vip-0.1.3/vip/man/list_metrics.Rd |only vip-0.1.3/vip/man/vi.Rd | 67 +- vip-0.1.3/vip/man/vi_ice.Rd | 33 - vip-0.1.3/vip/man/vi_model.Rd | 289 +++++++++- vip-0.1.3/vip/man/vi_pdp.Rd | 37 - vip-0.1.3/vip/man/vi_permute.Rd | 67 +- vip-0.1.3/vip/man/vint.Rd | 50 + vip-0.1.3/vip/man/vip.Rd | 16 26 files changed, 1942 insertions(+), 440 deletions(-)
Title: Simple Features for R
Description: Support for simple features, a standardized way to
encode spatial vector data. Binds to 'GDAL' for reading and writing
data, to 'GEOS' for geometrical operations, and to 'PROJ' for
projection conversions and datum transformations.
Author: Edzer Pebesma [aut, cre] (<https://orcid.org/0000-0001-8049-7069>),
Roger Bivand [ctb] (<https://orcid.org/0000-0003-2392-6140>),
Etienne Racine [ctb],
Michael Sumner [ctb],
Ian Cook [ctb],
Tim Keitt [ctb],
Robin Lovelace [ctb],
Hadley Wickham [ctb],
Jeroen Ooms [ctb] (<https://orcid.org/0000-0002-4035-0289>),
Kirill Müller [ctb],
Thomas Lin Pedersen [ctb]
Maintainer: Edzer Pebesma <edzer.pebesma@uni-muenster.de>
Diff between sf versions 0.7-4 dated 2019-04-25 and 0.7-5 dated 2019-07-03
DESCRIPTION | 8 - MD5 | 111 ++++++++++---------- NEWS.md | 18 +++ R/RcppExports.R | 4 R/arith.R | 2 R/bbox.R | 2 R/cast_sfc.R | 1 R/db.R | 29 ++++- R/geom.R | 19 ++- R/graticule.R | 6 - R/grid.R | 4 R/init.R | 10 + R/jitter.R | 2 R/join.R | 22 ++-- R/nearest.R | 6 + R/plot.R | 6 - R/read.R | 40 ++++--- R/sf.R | 9 + R/sfg.R | 3 R/sp.R | 16 ++ R/tidyverse.R | 15 -- build/vignette.rds |binary configure | 72 ++++--------- configure.ac | 27 ++++ inst/doc/sf1.Rmd | 2 inst/doc/sf1.html | 32 +++-- inst/doc/sf2.html | 26 ++-- inst/doc/sf3.html | 20 ++- inst/doc/sf4.html | 22 ++-- inst/doc/sf5.html | 46 ++++---- inst/doc/sf6.html | 22 ++-- inst/docker/gdal/Dockerfile | 165 +++++++++++++----------------- inst/docker/postgis |only man/geos_measures.Rd | 2 man/st_jitter.Rd | 2 man/st_read.Rd | 5 man/st_write.Rd | 10 + man/tidyverse.Rd | 6 - src/RcppExports.cpp | 12 ++ src/gdal.cpp | 4 src/gdal_write.cpp | 12 +- src/geos.cpp | 55 +++++++--- src/proj.cpp | 17 ++- src/stars.cpp | 22 +++- tests/aggregate.Rout.save | 8 - tests/dplyr.Rout.save | 12 +- tests/geos.R | 5 tests/geos.Rout.save | 16 ++ tests/sfc.R | 18 +++ tests/sfc.Rout.save | 70 ++++++++++++ tests/stars.Rout.save | 6 - tests/testthat/test_postgis_RPostgreSQL.R | 17 ++- tests/testthat/test_postgis_RPostgres.R | 7 + tests/testthat/test_sp.R | 8 + tests/testthat/test_st_cast.R | 5 tests/testthat/test_tidy.R | 13 ++ vignettes/sf1.Rmd | 2 57 files changed, 700 insertions(+), 401 deletions(-)
Title: Markov Models for Health Economic Evaluations
Description: An implementation of the modelling and reporting features described
in reference textbook and guidelines (Briggs, Andrew, et al. Decision
Modelling for Health Economic Evaluation. Oxford Univ. Press, 2011;
Siebert, U. et al. State-Transition Modeling. Medical Decision Making
32, 690-700 (2012).): deterministic and probabilistic sensitivity analysis,
heterogeneity analysis, time dependency on state-time and model-time
(semi-Markov and non-homogeneous Markov models), etc.
Author: Kevin Zarca [aut, cre],
Antoine Filipovic-Pierucci [aut],
Matthew Wiener [ctb],
Zdenek Kabat [ctb],
Vojtech Filipec [ctb],
Jordan Amdahl [ctb],
Yonatan Carranza Alarcon [ctb],
Vince Daniels [ctb]
Maintainer: Kevin Zarca <kevin.zarca@gmail.com>
Diff between heemod versions 0.9.4 dated 2019-02-24 and 0.10.0 dated 2019-07-03
DESCRIPTION | 6 MD5 | 51 +- NEWS.md | 6 R/expand.R | 24 - R/states_define.R | 80 ++- R/states_eval.R | 4 R/states_print.R | 27 - R/strategy_define.R | 1 R/strategy_eval.R | 27 - R/tabular_input.R | 19 build/vignette.rds |binary inst/doc/a_introduction.html | 383 +++++++++++++--- inst/doc/b_time_dependency.html | 337 ++++++++++++-- inst/doc/c_homogeneous.html | 493 +++++++++++++++------ inst/doc/d_non_homogeneous.html | 579 +++++++++++++++++-------- inst/doc/e_probabilistic.html | 603 +++++++++++++++++--------- inst/doc/f_sensitivity.html | 375 ++++++++++++---- inst/doc/g_heterogeneity.html | 467 ++++++++++++++------ inst/doc/h_tabular.html | 323 +++++++++++--- inst/doc/i_reproduction.html | 773 +++++++++++++++++++++------------- inst/doc/j_survival.html | 567 +++++++++++++++++------- inst/doc/k_calibration.html | 365 ++++++++++++---- man/compute_values.Rd | 2 man/define_state.Rd | 9 tests/testthat/Rplots.pdf |binary tests/testthat/test_starting_values.R |only tests/testthat/test_states.R | 36 + 27 files changed, 3986 insertions(+), 1571 deletions(-)
Title: Raw Accelerometer Data Analysis
Description: A tool to process and analyse data collected with wearable raw acceleration sensors as described in van Hees and colleagues (2014) <doi: 10.1152/japplphysiol.00421.2014> and (2015) <doi: 10.1371/journal.pone.0142533>. The package has been developed and tested for binary data from 'GENEActiv' <https://www.activinsights.com/> and GENEA devices (not for sale), .csv-export data from 'Actigraph' <http://actigraphcorp.com> devices, and .cwa and .wav-format data from 'Axivity' <https://axivity.com/product/ax3>. These devices are currently widely used in research on human daily physical activity.
Author: Vincent T van Hees [aut, cre],
Zhou Fang [ctb],
Jing Hua Zhao [ctb],
Joe Heywood [ctb],
Evgeny Mirkes [ctb],
Severine Sabia [ctb],
Joan Capdevila Pujol [ctb],
Jairo H Migueles [ctb]
Maintainer: Vincent T van Hees <vincentvanhees@gmail.com>
Diff between GGIR versions 1.9-1 dated 2019-05-08 and 1.9-2 dated 2019-07-03
DESCRIPTION | 8 MD5 | 64 +- R/g.analyse.R | 2 R/g.cwaread.R | 11 R/g.getmeta.R | 4 R/g.getstarttime.R | 8 R/g.impute.R | 4 R/g.part1.R | 6 R/g.part2.R | 2 R/g.part3.R | 2 R/g.part4.R | 552 ++++++++++++------------- R/g.part5.R | 17 R/g.plot5.R | 2 R/g.readaccfile.R | 15 R/g.shell.GGIR.R | 94 ++-- R/g.sib.sum.R | 204 ++++----- README.md | 2 inst/NEWS.Rd | 20 inst/doc/GGIR.R | 22 inst/doc/GGIR.Rmd | 27 - inst/doc/GGIR.html | 31 + man/GGIR-package.Rd | 6 man/g.cwaread.Rd | 8 man/g.getmeta.Rd | 7 man/g.part1.Rd | 7 man/g.part3.Rd | 4 man/g.part4.Rd | 2 man/g.readaccfile.Rd | 7 man/g.shell.GGIR.Rd | 2 man/g.sib.sum.Rd | 2 tests/testthat/test_create_test_acc_csv.R | 2 tests/testthat/test_create_test_sleeplog_csv.R | 2 vignettes/GGIR.Rmd | 27 - 33 files changed, 644 insertions(+), 529 deletions(-)
Title: Automatic Description of Factorial Analysis
Description: Brings a set of tools to help and automatically realise the description of principal component analyses (from 'FactoMineR' functions). Detection of existing outliers, identification of the informative components, graphical views and dimensions description are performed threw dedicated functions. The Investigate() function performs all these functions in one, and returns the result as a report document (Word, PDF or HTML).
Author: Simon Thuleau, Francois Husson
Maintainer: Simon Thuleau <factoinvestigate@gmail.com>
Diff between FactoInvestigate versions 1.3 dated 2018-05-06 and 1.4 dated 2019-07-03
FactoInvestigate-1.3/FactoInvestigate/R/FactoInvestigate-internal.R |only FactoInvestigate-1.4/FactoInvestigate/DESCRIPTION | 9 FactoInvestigate-1.4/FactoInvestigate/MD5 | 68 FactoInvestigate-1.4/FactoInvestigate/R/Investigate.R | 210 FactoInvestigate-1.4/FactoInvestigate/R/classif.R | 216 FactoInvestigate-1.4/FactoInvestigate/R/createRmd.R | 68 FactoInvestigate-1.4/FactoInvestigate/R/description.R | 510 - FactoInvestigate-1.4/FactoInvestigate/R/dimActive.R | 11 FactoInvestigate-1.4/FactoInvestigate/R/getParam.R | 21 FactoInvestigate-1.4/FactoInvestigate/R/graphCA.R | 8 FactoInvestigate-1.4/FactoInvestigate/R/graphHab.R | 88 FactoInvestigate-1.4/FactoInvestigate/R/graphInd.R | 12 FactoInvestigate-1.4/FactoInvestigate/R/graphSup.R | 12 FactoInvestigate-1.4/FactoInvestigate/R/graphVar.R | 12 FactoInvestigate-1.4/FactoInvestigate/R/inertiaDistrib.R | 128 FactoInvestigate-1.4/FactoInvestigate/R/outliers.R | 104 FactoInvestigate-1.4/FactoInvestigate/R/selection.R | 65 FactoInvestigate-1.4/FactoInvestigate/README.md |only FactoInvestigate-1.4/FactoInvestigate/build/partial.rdb |binary FactoInvestigate-1.4/FactoInvestigate/inst/po/fr/LC_MESSAGES/R-FactoInvestigate.mo |binary FactoInvestigate-1.4/FactoInvestigate/man/Investigate.Rd | 280 FactoInvestigate-1.4/FactoInvestigate/man/createRmd.Rd | 15 FactoInvestigate-1.4/FactoInvestigate/man/description.Rd | 3 FactoInvestigate-1.4/FactoInvestigate/man/dimActive.Rd | 3 FactoInvestigate-1.4/FactoInvestigate/man/factoGraph.Rd | 2 FactoInvestigate-1.4/FactoInvestigate/man/getParam.Rd | 3 FactoInvestigate-1.4/FactoInvestigate/man/graphCA.Rd | 2 FactoInvestigate-1.4/FactoInvestigate/man/graphHab.Rd | 3 FactoInvestigate-1.4/FactoInvestigate/man/graphInd.Rd | 3 FactoInvestigate-1.4/FactoInvestigate/man/graphSup.Rd | 3 FactoInvestigate-1.4/FactoInvestigate/man/graphVar.Rd | 3 FactoInvestigate-1.4/FactoInvestigate/man/outliers.Rd | 3 FactoInvestigate-1.4/FactoInvestigate/man/selection.Rd | 3 FactoInvestigate-1.4/FactoInvestigate/man/whichFacto.Rd | 3 FactoInvestigate-1.4/FactoInvestigate/po/R-FactoInvestigate.pot | 3 FactoInvestigate-1.4/FactoInvestigate/po/R-fr.po | 3193 +++++----- 36 files changed, 2691 insertions(+), 2376 deletions(-)
More information about FactoInvestigate at CRAN
Permanent link
Title: FROC Analysis by Bayesian Approaches
Description: Before reading this, execute BayesianFROC::fit_GUI(), then reader will understand this package without any explanation. Provides new methods for the so-called Free-response Receiver Operating Characteristic (FROC) analysis. The ultimate aim of FROC analysis is to compare observer performances, which means comparing characteristics, such as area under the curve (AUC) or figure of merit (FOM). In this package, we only use the notion of AUC for modality comparison, where by "modality", we mean imaging methods such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT), Positron Emission Tomography (PET), ..., etc. So there is a problem that which imaging method is better to detect lesions from shadows in radiographs. To solve modality comparison issues, this package provides new methods using hierarchical Bayesian models proposed by the author of this package. Using this package, one can obtain at least one conclusion that which imaging methods are better for finding lesions in radiographs with the case of your data. Fitting FROC statistical models is sometimes not so good, it can easily confirm by drawing FROC curves and comparing these curves and the points constructed by False Positive fractions (FPFs) and True Positive Fractions (TPFs), we can validate the goodness of fit intuitively. Such validation is also implemented by the Chi square goodness of fit statistics in the Bayesian context which means that the parameter is not deterministic, thus by integrating it with the posterior predictive measure, we get a desired value. To compare modalities (imaging methods: MRI, CT, PET, ... , etc), we evaluate AUCs for each modality. FROC is developed by Dev Chakraborty, his FROC model in his 1989 paper relies on the maximal likelihood methodology. The author modified and provided the alternative Bayesian FROC model. Strictly speaking, his model does not coincide with models in this package. In FROC context, we means by multiple reader and multiple case (MRMC) the case of the number of reader or modality is two or more. The MRMC data is available for functions of this package. I hope that medical researchers use not only the frequentist method but also alternative Bayesian methods. In medical research, many problems are considered under only frequentist methods, such as the notion of p-values. But p-value is sometimes misunderstood. Bayesian methods provide very simple, direct, intuitive answer for research questions. Combining frequentist methods with Bayesian methods, we can obtain more reliable answer for research questions. Please execute the following R scripts from the R (R studio) console, demo(demo_MRMC, package = "BayesianFROC"); demo(demo_srsc, package = "BayesianFROC"); demo(demo_stan, package = "BayesianFROC"); demo(demo_drawcurves_srsc, package = "BayesianFROC"); demo_Bayesian_FROC(); demo_Bayesian_FROC_without_pause(). References: Dev Chakraborty (1989) <doi:10.1118/1.596358> Maximum likelihood analysis of free - response receiver operating characteristic (FROC) data. Pre-print: Issei Tsunoda; Bayesian Models for free-response receiver operating characteristic analysis. See the vignettes for more details.
Author: Issei Tsunoda [aut, cre]
Maintainer: Issei Tsunoda <tsunoda.issei1111@gmail.com>
Diff between BayesianFROC versions 0.1.3 dated 2019-06-11 and 0.1.4 dated 2019-07-03
BayesianFROC-0.1.3/BayesianFROC/R/document_dataset.R |only BayesianFROC-0.1.3/BayesianFROC/R/packageStartupMessage.R |only BayesianFROC-0.1.3/BayesianFROC/man/figures/README-pressure-1.png |only BayesianFROC-0.1.3/BayesianFROC/man/figures/README-pressure-2.png |only BayesianFROC-0.1.3/BayesianFROC/vignettes/presentation.md |only BayesianFROC-0.1.4/BayesianFROC/DESCRIPTION | 40 BayesianFROC-0.1.4/BayesianFROC/MD5 | 316 +-- BayesianFROC-0.1.4/BayesianFROC/NAMESPACE | 3 BayesianFROC-0.1.4/BayesianFROC/NEWS.md | 55 BayesianFROC-0.1.4/BayesianFROC/R/Author_vs_Chakraborty_for_AUC.R |only BayesianFROC-0.1.4/BayesianFROC/R/Chi_square_goodness_of_fit_in_case_of_MRMC_Posterior_Mean.R |only BayesianFROC-0.1.4/BayesianFROC/R/DrawCurves.R | 62 BayesianFROC-0.1.4/BayesianFROC/R/DrawCurves_MRMC.R | 3 BayesianFROC-0.1.4/BayesianFROC/R/DrawCurves_MRMC_pairwise.R | 4 BayesianFROC-0.1.4/BayesianFROC/R/DrawCurves_MRMC_pairwise_col.R | 2 BayesianFROC-0.1.4/BayesianFROC/R/Replicate_MRMC_data.R | 4 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Title: Three-Way / Multigroup Data Analysis Through Densities
Description: The data consist of a set of variables measured on several groups of individuals. To each group is associated an estimated probability density function. The package provides tools to create or manage such data and functional methods (principal component analysis, multidimensional scaling, cluster analysis, discriminant analysis...) for such probability densities.
Author: Rachid Boumaza[aut, cre], Pierre Santagostini [aut], Smail Yousfi [aut], Gilles Hunault [ctb], Julie Bourbeillon [ctb], Besnik Pumo [ctb], Sabine Demotes-Mainard [aut]
Maintainer: Rachid Boumaza <rachid.boumaza@agrocampus-ouest.fr>
Diff between dad versions 3.2.0 dated 2019-01-17 and 3.3.0 dated 2019-07-03
DESCRIPTION | 12 - MD5 | 111 +++++++++-- NAMESPACE | 32 ++- R/associations.R |only R/associations.folder.R |only R/ddchisqsym.R |only R/ddchisqsympar.R |only R/ddhellinger.R |only R/ddhellingerpar.R |only R/ddjeffreys.R |only R/ddjeffreyspar.R |only R/ddjensen.R |only R/ddjensenpar.R |only R/ddlp.R |only R/ddlppar.R |only R/distl2dnorm.R |only R/distl2dnormpar.R |only R/fdiscd.misclass.R | 2 R/fhclustd.R | 12 - R/fmdsd.R | 450 +++++++++++++++++++++++---------------------- R/interpret.R | 4 R/interpret.dstatis.R | 290 ++++++++++++++--------------- R/interpret.fmdsd.R | 290 ++++++++++++++--------------- R/interpret.fpcad.R | 290 ++++++++++++++--------------- R/interpret.fpcat.R | 20 +- R/interpret.mdsdd.R |only R/is.mdsdd.R |only R/matddchisqsym.R |only R/matddchisqsympar.R |only R/matddhellinger.R |only R/matddhellingerpar.R |only R/matddjeffreys.R |only R/matddjeffreyspar.R |only R/matddjensen.R |only R/matddjensenpar.R |only R/matddlp.R |only R/matddlppar.R |only R/matdistl2dnorm.R |only R/matdistl2dnormpar.R |only R/mdsdd.R |only R/plot.fmdsd.R | 2 R/plot.mdsdd.R |only R/plotframes.R | 152 +++++++-------- R/print.mdsdd.R |only data/departments.rda |only data/dspg.rda |only data/dspgd2015.RData |only data/dspgd2015.rda |only man/associations.Rd |only man/associations.folder.Rd |only man/dad-package.Rd | 17 + man/ddchisqsym.Rd |only man/ddchisqsympar.Rd |only man/ddhellinger.Rd |only man/ddhellingerpar.Rd |only man/ddjeffreys.Rd |only man/ddjeffreyspar.Rd |only man/ddjensen.Rd |only man/ddjensenpar.Rd |only man/ddlp.Rd |only man/ddlppar.Rd |only man/departments.Rd |only man/distl2d.Rd | 134 ++++++------- man/distl2dnorm.Rd |only man/distl2dnormpar.Rd |only man/dspg.Rd |only man/dspgd2015.Rd |only man/fhclustd.Rd | 9 man/fmdsd.Rd | 79 ++++--- man/interpret.Rd | 102 ++++------ man/interpret.dstatis.Rd | 5 man/interpret.fmdsd.Rd | 137 +++++++------ man/interpret.fpcad.Rd | 133 ++++++------- man/interpret.fpcat.Rd | 135 ++++++------- man/interpret.mdsdd.Rd |only man/is.mdsdd.Rd |only man/matddchisqsym.Rd |only man/matddchisqsympar.Rd |only man/matddhellinger.Rd |only man/matddhellingerpar.Rd |only man/matddjeffreys.Rd |only man/matddjeffreyspar.Rd |only man/matddjensen.Rd |only man/matddjensenpar.Rd |only man/matddlp.Rd |only man/matddlppar.Rd |only man/matdistl2dnorm.Rd |only man/matdistl2dnormpar.Rd |only man/mdsdd.Rd |only man/plot.mdsdd.Rd |only man/print.mdsdd.Rd |only 91 files changed, 1273 insertions(+), 1145 deletions(-)
Title: Analysis of Factorial Experiments
Description: Convenience functions for analyzing factorial experiments using ANOVA or
mixed models. aov_ez(), aov_car(), and aov_4() allow specification of
between, within (i.e., repeated-measures), or mixed (i.e., split-plot)
ANOVAs for data in long format (i.e., one observation per row),
automatically aggregating multiple observations per individual and cell
of the design. mixed() fits mixed models using lme4::lmer() and computes
p-values for all fixed effects using either Kenward-Roger or Satterthwaite
approximation for degrees of freedom (LMM only), parametric bootstrap
(LMMs and GLMMs), or likelihood ratio tests (LMMs and GLMMs).
afex_plot() provides a high-level interface for interaction or one-way
plots using ggplot2, combining raw data and model estimates. afex uses
type 3 sums of squares as default (imitating commercial statistical software).
Author: Henrik Singmann [aut, cre] (<https://orcid.org/0000-0002-4842-3657>),
Ben Bolker [aut],
Jake Westfall [aut],
Frederik Aust [aut] (<https://orcid.org/0000-0003-4900-788X>),
Mattan S. Ben-Shachar [aut],
Søren Højsgaard [ctb],
John Fox [ctb],
Michael A. Lawrence [ctb],
Ulf Mertens [ctb],
Jonathon Love [ctb],
Russell Lenth [ctb],
Rune Haubo Bojesen Christensen [ctb]
Maintainer: Henrik Singmann <singmann+afex@gmail.com>
Diff between afex versions 0.23-0 dated 2019-02-19 and 0.24-1 dated 2019-07-03
DESCRIPTION | 10 +-- MD5 | 55 +++++++++--------- NAMESPACE | 2 NEWS | 32 ++++++++++ R/afex_plot.R | 4 - R/aov_car.R | 90 ++++++++++++++--------------- R/helpers.R | 62 +++++++++++++++----- R/methods.afex_aov.R | 8 ++ R/mixed.R | 3 R/test_assumption.R |only R/zzz.R | 3 build/partial.rdb |binary build/vignette.rds |binary inst/doc/afex_anova_example.html | 67 +++++++++++----------- inst/doc/afex_mixed_example.html | 17 +++-- inst/doc/afex_plot_introduction.html | 33 +++++----- inst/doc/afex_plot_supported_models.R | 4 - inst/doc/afex_plot_supported_models.Rmd | 4 - inst/doc/afex_plot_supported_models.html | 29 +++++---- inst/doc/introduction-mixed-models.pdf |binary inst/extdata/plots_brms.rda |binary inst/extdata/plots_rstanarm.rda |binary man/afex_options.Rd | 56 ++++++++++++++---- man/afex_plot.Rd | 4 - man/aov_car.Rd | 94 +++++++++++++++++-------------- man/test_assumptions.Rd |only tests/testthat/test-afex_aov.R | 36 +++++++++++ tests/testthat/test-assumption_tests.R |only tests/testthat/test-mixed-bugs.R | 16 +++++ vignettes/afex_plot_supported_models.Rmd | 4 - 30 files changed, 412 insertions(+), 221 deletions(-)
Title: Statistical Analysis of Fuzzy Data
Description: The aim of the package is to provide some basic functions
for doing statistics with one dimensional Fuzzy Data (in the
form of polygonal fuzzy numbers). In particular, the package
contains functions for the basic operations on the class of
fuzzy numbers (sum, scalar product, mean, median, Hukuhara difference)
as well as for calculating (Bertoluzza) distance and sample variance.
Moreover a function to simulate fuzzy random variables and bootstrap tests
for the equality of means is included. Version 2.1 fixes some bugs
of previous versions.
Author: Wolfgang Trutschnig <wolfgang@trutschnig.net>, Asun Lubiano
<lubiano@uniovi.es>
Maintainer: Asun Lubiano
<lubiano@uniovi.es>
Diff between SAFD versions 2.0 dated 2018-09-12 and 2.1 dated 2019-07-03
SAFD-2.0/SAFD/R/btest.mean.R |only SAFD-2.0/SAFD/man/btest.mean.Rd |only SAFD-2.1/SAFD/DESCRIPTION | 18 ++++++++--- SAFD-2.1/SAFD/MD5 | 30 +++++++++---------- SAFD-2.1/SAFD/R/btest1.mean.R |only SAFD-2.1/SAFD/R/btest2.mean.R | 32 ++++++++------------ SAFD-2.1/SAFD/R/btestk.mean.R | 59 ++++++++++++++++---------------------- SAFD-2.1/SAFD/R/hukuhara.R | 12 ++++--- SAFD-2.1/SAFD/build/partial.rdb |binary SAFD-2.1/SAFD/man/SAFD-package.Rd | 18 +++++++---- SAFD-2.1/SAFD/man/Trees.Rd | 2 - SAFD-2.1/SAFD/man/XX.Rd | 1 SAFD-2.1/SAFD/man/bertoluzza.Rd | 1 SAFD-2.1/SAFD/man/btest1.mean.Rd |only SAFD-2.1/SAFD/man/btest2.mean.Rd | 6 +-- SAFD-2.1/SAFD/man/btestk.mean.Rd | 8 ++--- SAFD-2.1/SAFD/man/decomposer.Rd | 1 SAFD-2.1/SAFD/man/hukuhara.Rd | 1 18 files changed, 96 insertions(+), 93 deletions(-)
Title: Cross-Platform 'zip' Compression
Description: Cross-Platform 'zip' Compression Library. A replacement
for the 'zip' function, that does not require any additional
external tools on any platform.
Author: Gábor Csárdi, Kuba Podgórski, Rich Geldreich
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>
Diff between zip versions 2.0.2 dated 2019-05-13 and 2.0.3 dated 2019-07-03
DESCRIPTION | 6 +++--- MD5 | 22 +++++++++++----------- NEWS.md | 6 ++++++ R/process.R | 16 ++++++++++++---- R/utils.R | 10 ++++++++-- R/zip.R | 25 +++++++++++++++---------- man/zip.Rd | 16 ++++++++++++---- man/zip_process.Rd | 5 ++++- tests/testthat/helper.R | 5 +++-- tests/testthat/test-zip-process.R | 12 ++++++++++++ tests/testthat/test-zip.R | 25 +++++++++++++++++++++++++ tests/testthat/test-zipr.R | 25 +++++++++++++++++++++++++ 12 files changed, 136 insertions(+), 37 deletions(-)
Title: Multivariate Exploratory Data Analysis and Data Mining
Description: Exploratory data analysis methods to summarize, visualize and describe datasets. The main principal component methods are available, those with the largest potential in terms of applications: principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, Multiple Factor Analysis when variables are structured in groups, etc. and hierarchical cluster analysis. F. Husson, S. Le and J. Pages (2017).
Author: Francois Husson, Julie Josse, Sebastien Le, Jeremy Mazet
Maintainer: Francois Husson <francois.husson@agrocampus-ouest.fr>
Diff between FactoMineR versions 1.41 dated 2018-05-06 and 1.42 dated 2019-07-03
DESCRIPTION | 10 MD5 | 35 NAMESPACE | 3 R/CA.R | 2 R/HMFA.R | 2 R/condes.r | 6 R/plot.FAMD.R | 117 +- R/plot.MCA.R | 780 +++++++++--------- R/plot.MFA.R | 2173 +++++++++++++++++++++++++-------------------------- R/plot.PCA.R | 744 ++++++++--------- R/plot.catdes.R | 510 ++++++----- README.md |only build/vignette.rds |binary data/children.rda |binary data/poison.rda |binary data/poison.text.rda |binary man/plot.HCPC.Rd | 2 man/plot.MFA.Rd | 3 man/poison.Rd | 2 19 files changed, 2210 insertions(+), 2179 deletions(-)
Title: Stochastic Simulation of Streamflow Time Series using Phase
Randomization
Description: Provides a simulation framework to simulate streamflow time series with similar
main characteristics as observed data. These characteristics include the distribution of daily
streamflow values and their temporal correlation as expressed by short- and long-range
dependence. The approach is based on the randomization of the phases of the Fourier
transform. We further use the flexible four-parameter Kappa distribution, which allows
for the extrapolation to yet unobserved low and high flows. Alternatively, the empirical or any other distribution can be used. A detailed description of
the simulation approach and an application example can be found
in <https://www.hydrol-earth-syst-sci-discuss.net/hess-2019-142/>.
Author: Manuela Brunner [aut, cre] (<https://orcid.org/0000-0001-8824-877X>),
Reinhard Furrer [aut] (<https://orcid.org/0000-0002-6319-2332>)
Maintainer: Manuela Brunner <manuela.brunner@wsl.ch>
Diff between PRSim versions 1.0 dated 2019-03-29 and 1.1 dated 2019-07-03
PRSim-1.0/PRSim/R/sssf-internal.R |only PRSim-1.1/PRSim/DESCRIPTION | 16 - PRSim-1.1/PRSim/MD5 | 19 - PRSim-1.1/PRSim/NAMESPACE | 7 PRSim-1.1/PRSim/R/fun_stoch_sim.R | 333 ++++++++++++++-------- PRSim-1.1/PRSim/build/partial.rdb |binary PRSim-1.1/PRSim/demo/PRSim.R | 16 - PRSim-1.1/PRSim/man/fun_stoch_sim.Rd | 60 ++- PRSim-1.1/PRSim/tests/Examples/PRSim-Ex.Rout.save | 45 ++ PRSim-1.1/PRSim/tests/basic.R | 40 ++ PRSim-1.1/PRSim/tests/basic.Rout.save | 122 ++++++-- 11 files changed, 480 insertions(+), 178 deletions(-)
Title: Execute and Control System Processes
Description: Tools to run system processes in the background.
It can check if a background process is running; wait on a background
process to finish; get the exit status of finished processes; kill
background processes. It can read the standard output and error of
the processes, using non-blocking connections. 'processx' can poll
a process for standard output or error, with a timeout. It can also
poll several processes at once.
Author: Gábor Csárdi [aut, cre, cph] (<https://orcid.org/0000-0001-7098-9676>),
Winston Chang [aut],
RStudio [cph, fnd],
Mango Solutions [cph, fnd]
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>
Diff between processx versions 3.3.1 dated 2019-05-08 and 3.4.0 dated 2019-07-03
DESCRIPTION | 12 + LICENSE | 2 MD5 | 105 ++++++++-------- NAMESPACE | 2 NEWS.md | 31 ++++ R/aaassertthat.R | 17 +- R/base64.R | 4 R/client-lib.R |only R/connections.R | 35 +++-- R/errors.R |only R/initialize.R | 44 +++++- R/io.R | 26 ++- R/named_pipe.R | 10 - R/on-load.R | 2 R/poll.R | 2 R/process-helpers.R | 2 R/process.R | 74 ++++++++--- R/run.R | 170 ++++++++++++++++++------- R/supervisor.R | 2 R/utils.R | 26 +++ README.md | 5 man/default_pty_options.Rd |only man/process.Rd | 19 ++ man/process_initialize.Rd | 8 - man/processx_connections.Rd | 5 man/run.Rd | 35 +++++ src/Makevars | 15 +- src/Makevars.win | 18 +- src/base64.c | 4 src/client.c |only src/create-time.c | 6 src/errors.c |only src/errors.h |only src/init.c | 8 - src/processx-connection.c | 89 +++++++------ src/processx-connection.h | 10 - src/processx-vector.c | 7 - src/processx.h | 10 + src/tools/px.c | 16 ++ src/unix/connection.c | 16 ++ src/unix/named_pipe.c | 14 +- src/unix/processx-unix.h | 4 src/unix/processx.c | 210 +++++++++++++++++++++++++------- src/unix/sigchld.c | 4 src/unix/utils.c | 35 +++++ src/win/named_pipe.c | 25 +-- src/win/processx-stdio.h |only src/win/processx-win.h | 3 src/win/processx.c | 96 +++++--------- src/win/stdio.c | 52 ------- src/win/thread.c | 4 src/win/utils.c | 10 + tests/testthat/helper.R | 15 ++ tests/testthat/test-client-lib.R |only tests/testthat/test-err.R |only tests/testthat/test-errors.R |only tests/testthat/test-extra-connections.R | 4 tests/testthat/test-pty.R |only tests/testthat/test-run.R | 29 ++++ 59 files changed, 913 insertions(+), 429 deletions(-)
Title: Rapid Digital Image Analysis of Leaf Area
Description: An interface for the image processing program 'ImageJ', which
allows a rapid digital image analysis for particle sizes. This package includes
function to write an 'ImageJ' macro which is optimized for a leaf area analysis by
default.
Author: Masatoshi Katabuchi <mattocci27@gmail.com>
Maintainer: Masatoshi Katabuchi <mattocci27@gmail.com>
Diff between LeafArea versions 0.1.7 dated 2017-03-12 and 0.1.8 dated 2019-07-03
LeafArea-0.1.7/LeafArea/R/find.ij.R |only LeafArea-0.1.7/LeafArea/R/readtext.ij.R |only LeafArea-0.1.7/LeafArea/R/resmerge.ij.R |only LeafArea-0.1.7/LeafArea/R/run.ij.R |only LeafArea-0.1.7/LeafArea/data/leafdata.RData |only LeafArea-0.1.7/LeafArea/man/leafdata.rd |only LeafArea-0.1.8/LeafArea/DESCRIPTION | 10 - LeafArea-0.1.8/LeafArea/MD5 | 33 ++-- LeafArea-0.1.8/LeafArea/NAMESPACE | 3 LeafArea-0.1.8/LeafArea/R/LeafArea.r |only LeafArea-0.1.8/LeafArea/R/eximg.r | 67 +++++--- LeafArea-0.1.8/LeafArea/R/find.ij.r |only LeafArea-0.1.8/LeafArea/R/leafdata.r |only LeafArea-0.1.8/LeafArea/R/readtext.ij.r |only LeafArea-0.1.8/LeafArea/R/resmerge.ij.r |only LeafArea-0.1.8/LeafArea/R/run.ij.r |only LeafArea-0.1.8/LeafArea/data/leafdata.rda |only LeafArea-0.1.8/LeafArea/inst/CITATION |only LeafArea-0.1.8/LeafArea/man/LeafArea-package.Rd | 51 +++--- LeafArea-0.1.8/LeafArea/man/eximg.Rd | 30 +--- LeafArea-0.1.8/LeafArea/man/find.ij.Rd | 34 +--- LeafArea-0.1.8/LeafArea/man/leafdata.Rd |only LeafArea-0.1.8/LeafArea/man/readtext.ij.Rd | 47 ++---- LeafArea-0.1.8/LeafArea/man/resmerge.ij.Rd | 64 ++------ LeafArea-0.1.8/LeafArea/man/run.ij.Rd | 180 ++++++++++++------------ 25 files changed, 239 insertions(+), 280 deletions(-)
Title: Geographically-Weighted Models
Description: In GWmodel, we introduce techniques from a particular branch of spatial statistics,termed geographically-weighted (GW) models. GW models suit situations when data are not described well by some global model, but where there are spatial regions where a suitably localised calibration provides a better description. GWmodel includes functions to calibrate: GW summary statistics, GW principal components analysis, GW discriminant analysis and various forms of GW regression; some of which are provided in basic and robust (outlier resistant) forms.
Author: Binbin Lu[aut], Paul Harris[aut], Martin Charlton[aut], Chris Brunsdon[aut], Tomoki Nakaya[aut], Daisuke Murakami[aut],Isabella Gollini[ctb]
Maintainer: Binbin Lu <binbinlu@whu.edu.cn>
Diff between GWmodel versions 2.0-9 dated 2019-04-29 and 2.1-1 dated 2019-07-03
DESCRIPTION | 18 - MD5 | 130 +++---- NAMESPACE | 10 R/RcppExports.R | 23 + R/bw.sel.r | 32 + R/gw.weight.r | 653 ++++++++++++++++++------------------- R/gwr.basic.r | 569 +++++++++++++++++--------------- R/gwr.scalable.r |only R/zzz.r | 2 man/DubVoter.rd | 3 man/EWHP.Rd | 3 man/EWOutline.rd | 3 man/GWmodel-package.Rd | 8 man/Georgia.Rd | 3 man/GeorgiaCounties.rd | 3 man/LondonBorough.rd | 3 man/LondonHP.Rd | 3 man/USelect.rd | 3 man/bw.ggwr.Rd | 3 man/bw.gtwr.Rd | 4 man/bw.gwda.rd | 1 man/bw.gwpca.rd | 3 man/bw.gwr.Rd | 3 man/bw.gwr.lcr.rd | 3 man/bw.gwss.average.Rd | 3 man/ggwr.basic.Rd | 2 man/ggwr.cv.Rd | 3 man/ggwr.cv.contrib.Rd | 4 man/gtwr.Rd | 2 man/gw.dist.Rd | 3 man/gw.pcplot.rd | 3 man/gw.weight.Rd | 3 man/gwpca.check.components.rd | 4 man/gwpca.cv.Rd | 3 man/gwpca.cv.contrib.Rd | 3 man/gwpca.glyph.plot.rd | 4 man/gwpca.montecarlo.1.rd | 3 man/gwpca.montecarlo.2.rd | 3 man/gwpca.rd | 2 man/gwr.basic.rd | 238 ++++++------- man/gwr.bootstrap.rd | 3 man/gwr.collin.diagno.Rd | 4 man/gwr.cv.Rd | 3 man/gwr.cv.contrib.Rd | 4 man/gwr.hetero.rd | 2 man/gwr.lcr.cv.Rd | 4 man/gwr.lcr.cv.contrib.Rd | 3 man/gwr.lcr.rd | 2 man/gwr.mink.approach.rd | 3 man/gwr.mink.matrixview.rd | 3 man/gwr.mink.pval.rd | 8 man/gwr.mixed.rd | 3 man/gwr.model.selection.Rd | 3 man/gwr.model.sort.Rd | 3 man/gwr.model.view.rd | 3 man/gwr.montecarlo.Rd | 3 man/gwr.multiscale.rd | 4 man/gwr.predict.Rd | 3 man/gwr.robust.Rd | 2 man/gwr.scalable.rd |only man/gwr.t.adjust.rd | 3 man/gwr.write.Rd | 3 man/gwss.montecarlo.Rd | 3 man/gwss.rd | 2 src/GWmodel.cpp | 735 +++++++++++++++++++++++++++++------------- src/RcppExports.cpp | 107 +++++- src/init.c | 12 67 files changed, 1604 insertions(+), 1093 deletions(-)
Title: Tools for Analyzing MCMC Simulations from Bayesian Inference
Description: Tools for assessing and diagnosing convergence of
Markov Chain Monte Carlo simulations, as well as for graphically display
results from full MCMC analysis. The package also facilitates the graphical
interpretation of models by providing flexible functions to plot the
results against observed variables.
Author: Xavier Fernández i Marín <xavier.fim@gmail.com>
Maintainer: Xavier Fernández i Marín <xavier.fim@gmail.com>
Diff between ggmcmc versions 1.2 dated 2019-02-15 and 1.3 dated 2019-07-03
DESCRIPTION | 12 ++-- MD5 | 51 +++++++++--------- NAMESPACE | 5 + NEWS | 45 +++++++++++++++ R/functions.R | 66 +++++++++++++++++++++++ R/ggmcmc.R | 15 ++++- R/ggs.R | 46 ++++++++++++++-- R/ggs_Rhat.R | 79 +++++++++++++++++++++++++-- R/ggs_caterpillar.R | 7 ++ R/ggs_effective.R |only R/ggs_geweke.R | 34 +++++------- R/ggs_pcp.R |only R/ggs_traceplot.R | 2 R/globals.R | 7 ++ R/help.R | 2 README.md | 7 +- inst/doc/using_ggmcmc.R | 38 +++++++------ inst/doc/using_ggmcmc.Rmd | 62 ++++++++++++++------- inst/doc/using_ggmcmc.html | 127 ++++++++++++++++++++++++++------------------- inst/doc/v70i09.pdf |binary man/ggmcmc.Rd | 4 + man/ggs.Rd | 8 ++ man/ggs_Rhat.Rd | 9 ++- man/ggs_caterpillar.Rd | 4 + man/ggs_effective.Rd |only man/ggs_pcp.Rd |only man/plab.Rd |only vignettes/bibliography.bib | 7 ++ vignettes/using_ggmcmc.Rmd | 62 ++++++++++++++------- 29 files changed, 514 insertions(+), 185 deletions(-)
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2019-07-01 0.3.1
Title: Generalized Additive Models
Description: Functions for fitting and working with generalized
additive models, as described in chapter 7 of "Statistical Models in
S" (Chambers and Hastie (eds), 1991), and "Generalized Additive
Models" (Hastie and Tibshirani, 1990).
Author: Trevor Hastie
Maintainer: Trevor Hastie <hastie@stanford.edu>
Diff between gam versions 1.16 dated 2018-07-20 and 1.16.1 dated 2019-07-03
DESCRIPTION | 6 MD5 | 6 src/linear.f | 355 ----------------------------------------------------------- src/loessc.c | 18 ++ 4 files changed, 21 insertions(+), 364 deletions(-)
Title: Summarize and Explore the Data
Description: Exploratory analysis on any input data describing the structure and the relationships present in the data. The package automatically select the variable and does related descriptive statistics. Analyzing information value, weight of evidence, custom tables, summary statistics, graphical techniques will be performed for both numeric and categorical predictors.
Author: Dayanand Ubrangala [aut, cre],
Kiran R [aut, ctb],
Ravi Prasad Kondapalli [aut, ctb],
Sayan Putatunda [aut, ctb]
Maintainer: Dayanand Ubrangala <daya6489@gmail.com>
Diff between SmartEDA versions 0.3.1 dated 2019-05-04 and 0.3.2 dated 2019-07-03
DESCRIPTION | 19 ++ MD5 | 36 ++--- NAMESPACE | 1 NEWS.md | 36 ++--- R/fn_exp_numeric.R | 2 R/fn_exp_numeric_viz.R | 238 +++++++++++++++++++++++-------------- R/fn_exp_report.R | 14 +- README.md | 118 +++++++++++++++--- inst/doc/CustomTable.html | 78 ++++++------ inst/doc/SmartEDA.R | 12 + inst/doc/SmartEDA.Rmd | 19 ++ inst/doc/SmartEDA.html | 84 +++++++------ inst/rmd_template/report_tmp.Rmd | 19 ++ inst/rmd_template/report_tmp_1.Rmd | 11 + inst/rmd_template/report_tmp_2.Rmd | 21 ++- man/ExpNumViz.Rd | 27 ++-- man/ExpReport.Rd | 13 +- man/figures |only vignettes/SmartEDA.Rmd | 19 ++ 19 files changed, 499 insertions(+), 268 deletions(-)
Title: Random Partition Distribution Indexed by Pairwise Information
Description: Implementations are provided for the models described in the paper D. B. Dahl, R. Day, J. Tsai (2017) <DOI:10.1080/01621459.2016.1165103>. The Ewens, Ewens-Pitman, Ewens attraction, Ewens-Pitman attraction, and ddCRP distributions are available for prior and posterior simulation. Posterior simulation is based on a user-supplied likelihood. Supporting functions for partition estimation and plotting are also provided.
Author: David B. Dahl [aut, cre]
Maintainer: David B. Dahl <dahl@stat.byu.edu>
Diff between shallot versions 0.4.5 dated 2018-10-30 and 0.4.6 dated 2019-07-03
shallot-0.4.5/shallot/inst/java/scala-2.11/shallot_2.11-0.4.5.jar |only shallot-0.4.5/shallot/inst/java/scala-2.12/shallot_2.12-0.4.5.jar |only shallot-0.4.5/shallot/java/shallot_2.12-0.4.5-sources.jar |only shallot-0.4.5/shallot/man/decay.Rd |only shallot-0.4.5/shallot/man/nsubsets.Rd |only shallot-0.4.5/shallot/man/partition.distribution.Rd |only shallot-0.4.6/shallot/DESCRIPTION | 12 shallot-0.4.6/shallot/MD5 | 58 shallot-0.4.6/shallot/NAMESPACE | 87 - shallot-0.4.6/shallot/NEWS | 4 shallot-0.4.6/shallot/R/default.mass.R |only shallot-0.4.6/shallot/R/onLoad.R | 10 shallot-0.4.6/shallot/R/shallot-package.R |only shallot-0.4.6/shallot/R/shallot.R | 691 +++++++++- shallot-0.4.6/shallot/inst/java/scala-2.11/shallot.jar |only shallot-0.4.6/shallot/inst/java/scala-2.12/shallot.jar |only shallot-0.4.6/shallot/inst/java/scala-2.13 |only shallot-0.4.6/shallot/java/README | 3 shallot-0.4.6/shallot/java/shallot-source.jar |only shallot-0.4.6/shallot/man/adj.rand.index.Rd | 37 shallot-0.4.6/shallot/man/association.matrix.Rd |only shallot-0.4.6/shallot/man/attraction.Rd | 50 shallot-0.4.6/shallot/man/decay.reciprocal.Rd |only shallot-0.4.6/shallot/man/default.mass.Rd |only shallot-0.4.6/shallot/man/enumerate.partitions.Rd | 28 shallot-0.4.6/shallot/man/estimate.partition.Rd | 62 shallot-0.4.6/shallot/man/ewens.Rd |only shallot-0.4.6/shallot/man/mass.Rd | 58 shallot-0.4.6/shallot/man/mass.algorithm.Rd |only shallot-0.4.6/shallot/man/nsubsets.random.Rd |only shallot-0.4.6/shallot/man/pairwise.probabilities.Rd | 53 shallot-0.4.6/shallot/man/partition.confidence.Rd |only shallot-0.4.6/shallot/man/partition.pmf.Rd | 22 shallot-0.4.6/shallot/man/permutation.Rd | 45 shallot-0.4.6/shallot/man/process.samples.Rd | 31 shallot-0.4.6/shallot/man/sample.partitions.Rd | 48 shallot-0.4.6/shallot/man/sample.partitions.posterior.Rd | 71 - shallot-0.4.6/shallot/man/sampling.model.Rd | 30 shallot-0.4.6/shallot/man/shallot-package.Rd | 44 shallot-0.4.6/shallot/man/variance.ratio.Rd |only 40 files changed, 1144 insertions(+), 300 deletions(-)
Title: High Performance Tools for Combinatorics and Computational
Mathematics
Description: Provides optimized functions implemented in C++ with 'Rcpp'
for solving problems in combinatorics and computational mathematics.
Utilizes parallel programming via 'RcppThread' for maximal performance.
Also makes use of the RMatrix class from the 'RcppParallel' library.
There are combination/permutation functions with constraint parameters
that allow for generation of all combinations/permutations of a vector
meeting specific criteria (e.g. finding all combinations such
that the sum is between two bounds). Capable of generating specific
combinations/permutations (e.g. retrieve only the nth lexicographical
result) which sets up nicely for parallelization as well as random
sampling. Gmp support permits exploration where the total number of
results is large (e.g. comboSample(10000, 500, n = 4)). Additionally,
there are several high performance number theoretic functions that
are useful for problems common in computational mathematics. Some of
these functions make use of the fast integer division library
'libdivide' by <http://ridiculousfish.com>. The primeSieve function
is based on the segmented sieve of Eratosthenes implementation by
Kim Walisch. It is also efficient for large numbers by using the
cache friendly improvements originally developed by Tomás Oliveira.
Finally, there is a prime counting function that implements Legendre's
formula based on the algorithm by Kim Walisch.
Author: Joseph Wood
Maintainer: Joseph Wood <jwood000@gmail.com>
Diff between RcppAlgos versions 2.3.3 dated 2019-06-30 and 2.3.4 dated 2019-07-03
DESCRIPTION | 6 +- MD5 | 44 ++++++++++----------- inst/NEWS.Rd | 7 +++ inst/include/ConstraintsMaster.h | 18 +++----- inst/include/ConstraintsUtils.h | 3 - inst/include/Eratosthenes.h | 15 ++----- inst/include/GeneralPartitions.h | 73 ++++++++++++++++------------------- inst/include/MotleyPrimes.h | 2 inst/include/importExportMPZ.h | 6 -- man/combinatoricsGeneral.Rd | 2 src/CombPermUtils.cpp | 22 ++++------ src/Combinatorics.cpp | 57 +++++++++++++++------------ src/CountGmp.cpp | 18 +++----- src/DivNumSieve.cpp | 2 src/NthResult.cpp | 17 +++----- src/PollardRho.cpp | 8 +-- src/Primes.cpp | 22 +++++----- src/importExportMPZ.cpp | 3 - tests/testthat/testCombPermResults.R | 1 tests/testthat/testParallel.R | 2 tests/testthat/testPrimeFactorize.R | 2 tests/testthat/testPrimeSieve.R | 41 ++++++++++--------- tests/testthat/testSample.R | 2 23 files changed, 185 insertions(+), 188 deletions(-)
Title: Inverse-Regression Estimation of Radioactive Doses
Description: Radioactive doses estimation using individual chromosomal aberrations information. See Higueras M, Puig P, Ainsbury E, Rothkamm K. (2015) <doi:10.1088/0952-4746/35/3/557>.
Author: David Moriña (Barcelona Graduate School of Mathematics), Manuel Higueras (Basque Center for Applied Mathematics) and Pedro Puig (Universitat Autònoma de Barcelona)
Maintainer: David Moriña Soler <david.morina@uab.cat>
Diff between radir versions 1.0.3 dated 2018-06-03 and 1.0.4 dated 2019-07-03
DESCRIPTION | 12 ++++++------ MD5 | 14 +++++++------- R/b.R | 2 +- R/dose.distr.R | 10 +++++----- man/ci.dose.radir.Rd | 2 +- man/dose.distr.Rd | 6 ++++-- man/pr.dose.radir.Rd | 2 +- man/radir-package.Rd | 6 +++--- 8 files changed, 28 insertions(+), 26 deletions(-)
Title: Visualizes a Matrix as Heatmap
Description: Visualizes a matrix object plainly as heatmap. It provides S3 functions to plot simple matrices and loading matrices.
Author: Sigbert Klinke
Maintainer: Sigbert Klinke <sigbert@hu-berlin.de>
Diff between plot.matrix versions 1.1 dated 2019-05-13 and 1.2 dated 2019-07-03
DESCRIPTION | 9 +++--- MD5 | 19 ++++++++------ R/bfi.2.R |only R/plot.loadings.R | 11 ++++---- README.md | 1 data |only inst/doc/plot.matrix.R | 12 ++++---- inst/doc/plot.matrix.Rmd | 12 ++++---- inst/doc/plot.matrix.html | 62 +++++++++++++++++++++++----------------------- man/bfi.2.Rd |only man/plot.loadings.Rd | 11 ++++---- vignettes/plot.matrix.Rmd | 12 ++++---- 12 files changed, 78 insertions(+), 71 deletions(-)
Title: Health-Economic Simulation Modeling and Decision Analysis
Description: Parameterize, simulate, and analyze health-economic simulation
models. Supports N-state partitioned survival models (Glasziou et al. 1990)
<doi:10.1002/sim.4780091106> and continuous time state transition models
(Siebert et al. 2012) <doi:10.1016/j.jval.2012.06.014> parameterized using
survival or multi-state modeling (de Wreede et al. 2011, Jackson 2015)
<doi:10.18637/jss.v038.i07>, <doi:10.18637/jss.v070.i08>. Decision uncertainty
from a cost-effectiveness analysis is quantified with standard graphical and
tabular summaries of a probabilistic sensitivity analysis (Claxton et al. 2005,
Barton et al. 2008) <doi:10.1002/hec.985>, <doi:10.1111/j.1524-4733.2008.00358.x>.
Simulation code written in C++ to boost performance.
Author: Devin Incerti [aut, cre],
Jeroen P. Jansen [aut]
Maintainer: Devin Incerti <devin.incerti@gmail.com>
Diff between hesim versions 0.2.0 dated 2019-03-28 and 0.2.1 dated 2019-07-03
DESCRIPTION | 18 MD5 | 58 - R/input-data.R | 8 R/statevals.R | 7 README.md | 14 build/vignette.rds |binary inst/doc/ctstm.Rmd | 6 inst/doc/ctstm.html | 293 +++++- inst/doc/icea.Rmd | 2 inst/doc/icea.html | 460 +++++++--- inst/doc/intro.R | 24 inst/doc/intro.Rmd | 26 inst/doc/intro.html | 262 ++++- inst/doc/psm.Rmd | 6 inst/doc/psm.html | 250 ++++- inst/include/hesim/statmods/obs_index.h | 8 man/StateVals.Rd | 2 man/create_StateVals.Rd | 6 man/input_mats.Rd | 7 src/indiv-ctstm.cpp | 52 - tests/testthat/test-ctstm.R | 34 tests/testthat/test-distributions.R | 3 tests/testthat/test-statevals.R | 4 vignettes/ctstm.Rmd | 6 vignettes/icea.Rmd | 2 vignettes/intro.Rmd | 26 vignettes/psm.Rmd | 6 vignettes/psm_cache/html/unnamed-chunk-7_6c494040b5411a6c217251593dd1bbcb.RData |binary vignettes/psm_cache/html/unnamed-chunk-7_6c494040b5411a6c217251593dd1bbcb.rdb |binary vignettes/psm_cache/html/unnamed-chunk-7_6c494040b5411a6c217251593dd1bbcb.rdx |binary 30 files changed, 1220 insertions(+), 370 deletions(-)
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2019-06-14 0.9.1
2019-01-23 0.9.0
2018-04-27 0.8.12
2018-04-26 0.8.11
2017-11-01 0.8.10
2017-08-28 0.8.9
2017-03-16 0.8.6
2017-03-12 0.8.2
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2019-02-27 0.2-5
2019-01-15 0.2-4
2017-04-27 0.2-3
2015-12-19 0.2-1
2015-10-27 0.1-5
2014-06-24 0.1-4
2014-05-01 0.1-3
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2019-06-05 0.3-15
2019-05-19 0.3-13
2019-04-15 0.3-12
2019-02-27 0.3-7
2019-01-14 0.3-6
2018-07-21 0.3-5
2017-10-23 0.3-4
2017-08-18 0.3-3
2016-08-30 0.2-4
2016-08-29 0.2-3
2016-02-04 0.2-1
2015-11-22 0.1-20
2015-07-23 0.1-19
2015-06-10 0.1-18
2014-11-10 0.1-17
2014-11-09 0.1-16
2014-09-23 0.1-15
2014-09-22 0.1-14
Title: Bootstrap Functions (Originally by Angelo Canty for S)
Description: Functions and datasets for bootstrapping from the
book "Bootstrap Methods and Their Application" by A. C. Davison and
D. V. Hinkley (1997, CUP), originally written by Angelo Canty for S.
Author: Angelo Canty [aut],
Brian Ripley [aut, trl, cre] (author of parallel support)
Maintainer: Brian Ripley <ripley@stats.ox.ac.uk>
Diff between boot versions 1.3-22 dated 2019-04-02 and 1.3-23 dated 2019-07-03
ChangeLog | 4 ++++ DESCRIPTION | 8 ++++---- MD5 | 6 +++--- man/catsM.Rd | 8 ++++---- 4 files changed, 15 insertions(+), 11 deletions(-)
Title: Treatment of Zeros, Left-Censored and Missing Values in
Compositional Data Sets
Description: Principled methods for the imputation of zeros, left-censored and missing data in
compositional data sets.
Author: Javier Palarea-Albaladejo and Josep Antoni Martin-Fernandez
Maintainer: Javier Palarea-Albaladejo <javier.palarea@bioss.ac.uk>
Diff between zCompositions versions 1.3.2 dated 2019-06-02 and 1.3.2-1 dated 2019-07-03
DESCRIPTION | 10 +++++----- MD5 | 12 ++++++------ NAMESPACE | 1 - NEWS | 7 +++++++ R/lrDA.R | 23 ++++++++++++++++++++--- man/lrDA.Rd | 4 ++-- man/zCompositions-package.Rd | 4 ++-- 7 files changed, 42 insertions(+), 19 deletions(-)
Title: Summarizing Distributions of Latent Structures
Description: Summaries of distributions on clusterings and feature allocations are provided. Specifically, point estimates are obtained by the sequentially-allocated latent structure optimization (SALSO) algorithm to minimize squared error loss, absolute error loss, Binder loss, or the lower bound of the variation of information loss. Clustering uncertainty can be assessed with the confidence calculations and the associated plot.
Author: David B. Dahl [aut, cre],
Peter Müller [aut]
Maintainer: David B. Dahl <dahl@stat.byu.edu>
Diff between sdols versions 1.7 dated 2018-10-30 and 1.7.5 dated 2019-07-03
sdols-1.7.5/sdols/DESCRIPTION | 12 +- sdols-1.7.5/sdols/MD5 | 26 ++--- sdols-1.7.5/sdols/NAMESPACE | 1 sdols-1.7.5/sdols/NEWS | 7 + sdols-1.7.5/sdols/R/expectedPairwiseAllocationMatrix.R | 52 ++++++---- sdols-1.7.5/sdols/R/onLoad.R | 8 + sdols-1.7.5/sdols/R/salso.R | 5 sdols-1.7.5/sdols/data/USArrests.featureAllocations.RData |binary sdols-1.7.5/sdols/data/iris.clusterings.RData |binary sdols-1.7.5/sdols/inst/java/scala-2.11/sdols.jar |only sdols-1.7.5/sdols/inst/java/scala-2.12/sdols.jar |only sdols-1.7.5/sdols/inst/java/scala-2.13 |only sdols-1.7.5/sdols/java/sdols-source.jar |only sdols-1.7.5/sdols/java/sdols_2.12-1.7.3.5-SNAPSHOT-sources.jar |only sdols-1.7.5/sdols/man/expectedPairwiseAllocationMatrix.Rd | 44 +++++--- sdols-1.7/sdols/inst/java/scala-2.11/sdols_2.11-1.7.jar |only sdols-1.7/sdols/inst/java/scala-2.12/sdols_2.12-1.7.jar |only sdols-1.7/sdols/java/sdols_2.12-1.7-sources.jar |only 18 files changed, 98 insertions(+), 57 deletions(-)
Title: Learning Interactions via Hierarchical Group-Lasso
Regularization
Description: Group-Lasso INTERaction-NET. Fits linear pairwise-interaction models that satisfy strong hierarchy: if an interaction coefficient is estimated to be nonzero, then its two associated main effects also have nonzero estimated coefficients. Accommodates categorical variables (factors) with arbitrary numbers of levels, continuous variables, and combinations thereof. Implements the machinery described in the paper "Learning interactions via hierarchical group-lasso regularization" (JCGS 2015, Volume 24, Issue 3). Michael Lim & Trevor Hastie (2015) <DOI:10.1080/10618600.2014.938812>.
Author: Michael Lim, Trevor Hastie
Maintainer: Michael Lim <michael626@gmail.com>
Diff between glinternet versions 1.0.9 dated 2019-06-12 and 1.0.10 dated 2019-07-03
DESCRIPTION | 8 ++++---- MD5 | 4 ++-- R/glinternet.r | 8 +++++++- 3 files changed, 13 insertions(+), 7 deletions(-)
Title: Data Science Labs
Description: Datasets and functions that can be used for data analysis practice, homework and projects in data science courses and workshops. 26 datasets are available for case studies in data visualization, statistical inference, modeling, linear regression, data wrangling and machine learning.
Author: Rafael A. Irizarry, Amy Gill
Maintainer: Rafael A. Irizarry <rafa@jimmy.harvard.edu>
Diff between dslabs versions 0.6.0 dated 2019-05-17 and 0.7.0 dated 2019-07-03
DESCRIPTION | 8 +-- MD5 | 79 ++++++++++++++++++++----------- NAMESPACE | 16 +++--- R/brca.R |only R/death_prob.R |only R/greenhouse_gases.R |only R/historic_co2.R |only R/stars.R |only R/temp_carbon.R |only data/brca.rda |only data/datalist | 6 ++ data/death_prob.rda |only data/greenhouse_gases.rda |only data/historic_co2.rda |only data/stars.rda |only data/temp_carbon.rda |only inst/extdata/HRlist2.txt |only inst/extdata/carbon_emissions.csv |only inst/extdata/ssa-death-probability.csv |only inst/script/make-brca.R |only inst/script/make-death_prob.R |only inst/script/make-greenhouse_gases.R |only inst/script/make-historic_co2.R |only inst/script/make-stars.R |only inst/script/make-temp_carbon.R |only man/admissions.Rd | 58 +++++++++++----------- man/brca.Rd |only man/brexit_polls.Rd | 68 +++++++++++++------------- man/death_prob.Rd |only man/divorce_margarine.Rd | 56 +++++++++++----------- man/ds_theme_set.Rd | 68 +++++++++++++------------- man/gapminder.Rd | 72 ++++++++++++++-------------- man/greenhouse_gases.Rd |only man/heights.Rd | 48 +++++++++--------- man/historic_co2.Rd |only man/mnist_27.Rd | 70 +++++++++++++-------------- man/movielens.Rd | 70 +++++++++++++-------------- man/murders.Rd | 60 +++++++++++------------ man/na_example.Rd | 36 +++++++------- man/nyc_regents_scores.Rd | 64 ++++++++++++------------- man/olive.Rd | 70 +++++++++++++-------------- man/outlier_example.Rd | 38 +++++++------- man/polls_2008.Rd | 58 +++++++++++----------- man/polls_us_election_2016.Rd | 84 ++++++++++++++++----------------- man/read_mnist.Rd | 78 +++++++++++++++--------------- man/reported_heights.Rd | 52 ++++++++++---------- man/research_funding_rates.Rd | 78 +++++++++++++++--------------- man/rfalling_object.Rd | 82 ++++++++++++++++---------------- man/stars.Rd |only man/take_poll.Rd | 46 +++++++++--------- man/temp_carbon.Rd |only man/tissue_gene_expression.Rd | 68 +++++++++++++------------- man/trump_tweets.Rd | 68 +++++++++++++------------- man/us_contagious_diseases.Rd | 62 ++++++++++++------------ 54 files changed, 798 insertions(+), 765 deletions(-)
Title: Verbal Autopsy Data Transformation for InSilicoVA and InterVA5
Algorithms
Description: Enables transformation of Verbal Autopsy data collected with the WHO 2016 questionnaire (versions 1.4.1 & 1.5.1)
or the WHO 2014 questionnaire for automated coding of Cause of Death using the InSilicoVA (data.type = "WHO2016") and
InterVA5 algorithms. Previous versions of this package supported user-supplied mappings (via the map_records function), but
this functionality has been removed. This package is made available by WHO and the Bloomberg Data for Health Initiative.
Author: Peter Byass [aut],
Eungang Choi [aut],
Sam Clark [aut],
Zehang Li [aut],
Nicolas Maire [aut],
Tyler McCormick [aut],
Jason Thomas [aut, cre]
Maintainer: Jason Thomas <jarathomas@gmail.com>
Diff between CrossVA versions 0.9.8 dated 2019-05-17 and 0.9.9 dated 2019-07-03
DESCRIPTION | 6 MD5 | 14 - R/odk2openVA_2014.R | 245 +++++++++++++++++++++++++++------ R/odk2openVA_v141.R | 237 ++++++++++++++++++++++++++----- R/odk2openVA_v151.R | 185 +++++++++++++++++++++--- inst/doc/using-crossva-and-openva.html | 50 +++--- tests/testthat/test-return.R | 15 ++ tests/testthat/test-warnings.R | 33 +++- 8 files changed, 643 insertions(+), 142 deletions(-)