Title: Multi-Objective Simultaneous Model and Feature Selection
Description: Performs simultaneous hyperparameter tuning and
feature selection through both single-objective and multi-objective
optimization as described in Binder, Moosbauer et al. (2019) <arXiv:1912.12912>.
Uses the 'ecr'-package as basis but adds mixed integer
evolutionary strategies and multi-fidelity functionality as well as operators
specific for the problem of feature selection.
Author: Martin Binder [aut, cre],
Susanne Dandl [aut],
Julia Moosbauer [aut]
Maintainer: Martin Binder <developer.mb706@mb706.com>
Diff between mosmafs versions 0.1.2 dated 2020-04-05 and 0.1.2-1 dated 2022-11-02
DESCRIPTION | 10 +++++----- MD5 | 20 ++++++++++---------- NEWS | 3 +++ README.md | 9 ++++----- inst/doc/demo.R | 2 ++ inst/doc/demo.Rmd | 5 ++++- inst/doc/demo.html | 2 +- inst/doc/multifidelity.R | 2 ++ inst/doc/multifidelity.Rmd | 3 +++ vignettes/demo.Rmd | 5 ++++- vignettes/multifidelity.Rmd | 3 +++ 11 files changed, 41 insertions(+), 23 deletions(-)
Title: Data and Function to Work with Emojis
Description: Contains data about emojis with relevant metadata, and functions
to work with emojis when they are in strings.
Author: Emil Hvitfeldt [aut, cre] ,
Hadley Wickham [ctb] ,
Romain Francois [ctb]
Maintainer: Emil Hvitfeldt <emilhhvitfeldt@gmail.com>
Diff between emoji versions 0.2.0 dated 2021-09-18 and 15.0 dated 2022-11-02
DESCRIPTION | 10 ++++----- MD5 | 32 ++++++++++++++++++----------- NAMESPACE | 3 ++ NEWS.md | 9 ++++++++ R/data.R | 46 +++++++++++++++++++++++++++++++----------- R/modifiers.R |only R/zoo.R |only README.md | 43 ++++++++++++++++++++++----------------- data/emoji_keyword.rda |binary data/emoji_modifiers.rda |only data/emoji_name.rda |binary data/emojis.rda |binary man/emoji_glue.Rd | 4 +-- man/emoji_keyword.Rd | 8 +++---- man/emoji_modifier_extract.Rd |only man/emoji_modifier_remove.Rd |only man/emoji_modifiers.Rd |only man/emoji_name.Rd | 8 +++---- man/emojis.Rd | 10 ++++----- man/figures |only man/zoo.Rd |only 21 files changed, 111 insertions(+), 62 deletions(-)
Title: Fetching Tweet Data for Sentiment Analysis
Description: Which uses Twitter APIs for the necessary data in sentiment analysis, acts as a middleware with the approved Twitter Application.
A special access key is given to users who subscribe to the application with their Twitter account. With this special access key, the user defined keyword for sentiment analysis can be searched in twitter recent searches and results can be obtained( more information <https://github.com/hakkisabah/tsentiment> ).
In addition, a service named tsentiment-services has been developed to provide all these operations ( for more information <https://github.com/hakkisabah/tsentiment-services> ).
After the successful results obtained and in line with the permissions given by the user, the results of the analysis of the word cloud and bar graph saved in the user folder directory can be seen. In each analysis performed, the previous analysis visual result is deleted and this is the basic information you need to know as a practice rule.
'tsentiment' package pr [...truncated...]
Author: Hakki Sabah <hakkisabah@hotmail.com>
Maintainer: Hakki Sabah <hakkisabah@hotmail.com>
Diff between tsentiment versions 1.0.4 dated 2021-11-30 and 1.0.5 dated 2022-11-02
DESCRIPTION | 10 ++-- MD5 | 22 ++++---- NAMESPACE | 5 ++ R/barPlot.R | 107 +++++++++++++++++++++---------------------- R/comparisonCloud.R | 125 +++++++++++++++++++++++++++++--------------------- R/env.R | 20 ++++---- R/fileConfirmation.R | 92 ++++++++++++++++++------------------- R/getAnalysis.R | 90 ++++++++++++++++++------------------ R/getTweet.R | 126 ++++++++++++++++++++++++++------------------------- R/tweetFetcher.R | 106 +++++++++++++++++------------------------- R/writeCSV.R |only man/tweetFetcher.Rd | 2 man/writeToCSV.Rd |only 13 files changed, 360 insertions(+), 345 deletions(-)
Title: Linear Model with Breakpoint
Description: Exact significance tests for a changepoint in linear or multiple linear regression.
Confidence regions with exact coverage probabilities for the changepoint. Based on
Knowles, Siegmund and Zhang (1991) <doi:10.1093/biomet/78.1.15>.
Author: Marc Adams [aut, cre],
authors of R function 'lm' [ctb] ,
authors of 'lm.gls' [ctb] ,
U.S. NIST [ctb]
Maintainer: Marc Adams <lm.br.pkg@gmail.com>
Diff between lm.br versions 2.9.5 dated 2022-09-29 and 2.9.6 dated 2022-11-02
DESCRIPTION | 13 +++++-------- MD5 | 4 ++-- inst/doc/lm.br.pdf |binary 3 files changed, 7 insertions(+), 10 deletions(-)
Title: Retrieve and Analyze Clinical Trials in Public Registers
Description: A system for querying, retrieving and analyzing
protocol- and results-related information on clinical trials from
three public registers, the 'European Union Clinical Trials Register'
('EUCTR', <https://www.clinicaltrialsregister.eu/>),
'ClinicalTrials.gov' ('CTGOV', <https://clinicaltrials.gov/>) and
the 'ISRCTN' (<http://www.isrctn.com/>).
Trial information is downloaded, converted and stored in a database
('PostgreSQL', 'SQLite', 'DuckDB' or 'MongoDB'; via package 'nodbi').
Functions are included to identify deduplicated records,
to easily find and extract variables (fields) of interest even
from complex nesting as used by the registers, and
to update previous queries.
The package can be used for meta-analysis and trend-analysis of
the design and conduct as well as for results of clinical trials.
Author: Ralf Herold [aut, cre]
Maintainer: Ralf Herold <ralf.herold@mailbox.org>
Diff between ctrdata versions 1.10.2 dated 2022-08-20 and 1.11.0 dated 2022-11-02
DESCRIPTION | 10 +-- MD5 | 29 +++++---- NAMESPACE | 2 NEWS.md | 4 + R/ctrdata-package.R | 3 R/main.R | 4 - R/utils.R | 54 +++++++++++++++-- README.md | 89 ++++++++++++++++++----------- build/vignette.rds |binary inst/tinytest/ctrdata_isrctn.R | 26 +++++++- inst/tinytest/setup_ctrdata.R | 6 + inst/tinytest/test_ctrdata_duckdb_ctgov.R |only inst/tinytest/test_ctrdata_duckdb_euctr.R |only inst/tinytest/test_ctrdata_duckdb_isrctn.R |only man/ctrLoadQueryIntoDb.Rd | 4 - man/ctrdata-package.Rd | 13 +--- tests/tinytest.R | 1 17 files changed, 172 insertions(+), 73 deletions(-)
Title: Custom 'Bootstrap' 'Sass' Themes for 'shiny' and 'rmarkdown'
Description: Simplifies custom 'CSS' styling of both 'shiny' and 'rmarkdown' via 'Bootstrap' 'Sass'. Supports both 'Bootstrap' 3 and 4 as well as their various 'Bootswatch' themes. An interactive widget is also provided for previewing themes in real time.
Author: Carson Sievert [aut, cre] ,
Joe Cheng [aut],
RStudio [cph],
Bootstrap contributors [ctb] ,
Twitter, Inc [cph] ,
Javi Aguilar [ctb, cph] ,
Thomas Park [ctb, cph] ,
PayPal [ctb, cph]
Maintainer: Carson Sievert <carson@rstudio.com>
Diff between bslib versions 0.4.0 dated 2022-07-16 and 0.4.1 dated 2022-11-02
DESCRIPTION | 10 +++++----- MD5 | 8 ++++---- NEWS.md | 6 ++++++ man/bs_bundle.Rd | 12 ++++++------ man/nav.Rd | 12 ++++++------ 5 files changed, 27 insertions(+), 21 deletions(-)
Title: Chemical Information from the Web
Description: Chemical information from around the web. This package interacts
with a suite of web services for chemical information. Sources include: Alan
Wood's Compendium of Pesticide Common Names, Chemical Identifier Resolver,
ChEBI, Chemical Translation Service, ChemIDplus, ChemSpider, ETOX,
Flavornet, NIST Chemistry WebBook, OPSIN, PAN Pesticide Database, PubChem,
SRS, Wikidata.
Author: Eduard Szoecs [aut],
Robert Allaway [ctb],
Daniel Muench [ctb],
Johannes Ranke [ctb],
Andreas Scharmueller [ctb],
Eric R Scott [ctb],
Jan Stanstrup [ctb],
Joao Vitor F Cavalcante [ctb],
Gordon Getzinger [ctb],
Tamas Stirling [ctb, cre]
Maintainer: Tamas Stirling <stirling.tamas@gmail.com>
Diff between webchem versions 1.1.3 dated 2022-06-15 and 1.2.0 dated 2022-11-02
DESCRIPTION | 10 +++++----- MD5 | 35 ++++++++++++++++++++--------------- NAMESPACE | 7 +++++++ NEWS.md | 12 ++++++++++++ R/chembl.R |only R/chemspider.R | 8 +++++++- R/nist.R | 6 +++--- R/ping.R | 27 +++++++++++++++++++-------- R/utils.R | 11 +++-------- build/partial.rdb |binary build/vignette.rds |binary inst/doc/webchem.html | 13 ++++++++++--- man/chembl_atc_classes.Rd |only man/chembl_query.Rd |only man/chembl_resources.Rd |only man/ping_service.Rd | 11 ++++++++--- tests/testthat/test-bcpc.R | 14 +++++++------- tests/testthat/test-chembl.R |only tests/testthat/test-opsin.R | 2 +- tests/testthat/test-pubchem.R | 2 +- tests/testthat/test-wikidata.R | 2 +- 21 files changed, 104 insertions(+), 56 deletions(-)
Title: Exhaustive Chemical Enumeration for United Formula Annotation
Description: A pipeline to annotate a number of peaks from the IDSL.IPA peaklists using an exhaustive chemical enumeration-based approach. This package can perform elemental composition calculations using the following 15 elements : C, B, Br, Cl, K, S, Se, Si, N, H, As, F, I, Na, O, and P.
Author: Sadjad Fakouri-Baygi [cre, aut]
,
Dinesh Barupal [aut]
Maintainer: Sadjad Fakouri-Baygi <sadjad.fakouri-baygi@mssm.edu>
Diff between IDSL.UFAx versions 1.6 dated 2022-09-26 and 1.7 dated 2022-11-02
DESCRIPTION | 11 +++++------ MD5 | 10 +++++----- NAMESPACE | 9 +-------- R/UFAx_score_coefficient_corrector.R | 2 +- R/UFAx_workflow.R | 9 ++++++--- inst/CITATION | 8 +++++--- 6 files changed, 23 insertions(+), 26 deletions(-)
Title: Parser for mzML, mzXML, and netCDF Files (Mass Spectrometry
Data)
Description: A tiny parser to extract mass spectra data and metadata table of MS acquisition properties from mzML, mzXML and netCDF mass spectrometry files.
Author: Sadjad Fakouri-Baygi [cre, aut]
,
Dinesh Barupal [aut]
Maintainer: Sadjad Fakouri-Baygi <sadjad.fakouri-baygi@mssm.edu>
Diff between IDSL.MXP versions 1.6 dated 2022-09-27 and 1.7 dated 2022-11-02
DESCRIPTION | 9 +++++---- MD5 | 4 ++-- NAMESPACE | 3 +-- 3 files changed, 8 insertions(+), 8 deletions(-)
Title: Robust Inference for Absolute Abundance in Microbiome Analysis
Description: This package offers a robust approach to make inference on the association of covariates with the absolute abundance (AA) of microbiome in an ecosystem. It can be also directly applied to relative abundance (RA) data to make inference on AA because the ratio of two RA is equal ratio of their AA. This algorithm can estimate and test the associations of interest while adjusting for potential confounders. High-dimensional covariates are handled with regularization. The estimates of this method have easy interpretation like a typical regression analysis. High-dimensional covariates are handled with regularization and it is implemented by parallel computing. False discovery rate is automatically controlled by this approach. Zeros do not need to be imputed by a positive value for the analysis. The IFAA package also offers the 'MZILN' function for estimating and testing associations of abundance ratios with covariates.
Author: Quran Wu [aut],
Zhigang Li [aut, cre]
Maintainer: Zhigang Li <zhigang.li@ufl.edu>
Diff between IFAA versions 1.0.9 dated 2022-09-15 and 1.1.0 dated 2022-11-02
IFAA-1.0.9/IFAA/vignettes/IFAA.html |only IFAA-1.1.0/IFAA/DESCRIPTION | 8 - IFAA-1.1.0/IFAA/MD5 | 32 +++--- IFAA-1.1.0/IFAA/R/IFAAfunc.R | 78 +++++++++----- IFAA-1.1.0/IFAA/R/MZILN.R | 44 +++++++- IFAA-1.1.0/IFAA/R/allUserDefinedFuncs.R | 3 IFAA-1.1.0/IFAA/R/originDataScreen.R | 78 ++++++++------ IFAA-1.1.0/IFAA/R/regulariz.R | 43 ++++---- IFAA-1.1.0/IFAA/R/regulariz_MZILN.R | 14 +- IFAA-1.1.0/IFAA/R/runlinear.R |only IFAA-1.1.0/IFAA/README.md | 37 +++---- IFAA-1.1.0/IFAA/build/IFAA.pdf |binary IFAA-1.1.0/IFAA/inst/doc/IFAA.R | 117 ++++++++++++++-------- IFAA-1.1.0/IFAA/inst/doc/IFAA.Rmd | 169 +++++++++++++++++++++----------- IFAA-1.1.0/IFAA/inst/doc/IFAA.pdf |binary IFAA-1.1.0/IFAA/man/IFAA.Rd | 49 ++++++--- IFAA-1.1.0/IFAA/man/MZILN.Rd | 35 +++++- IFAA-1.1.0/IFAA/vignettes/IFAA.Rmd | 169 +++++++++++++++++++++----------- 18 files changed, 570 insertions(+), 306 deletions(-)
Title: Parallel Digital Soil Mapping using Machine Learning
Description: Parallel computing, multi-core CPU is used to efficiently compute
and process multi-dimensional soil data.This package includes the
parallelized 'Quantile Regression Forests' algorithm for Digital Soil Mapping
and is mainly dependent on the package 'quantregForest' and 'snowfall'.
Detailed references to the R package and the web site are described in the
methods, as detailed in the method documentation.
Author: Xiaodong Song [aut],
Peicong Tang [aut, cre],
Wentao Zhu [aut],
Gaoqiang Ge [aut],
Jun Zhu [aut],
Ganlin Zhang [aut]
Maintainer: Peicong Tang <peicongtang0409@163.com>
Diff between ParallelDSM versions 0.3.5 dated 2022-08-13 and 0.3.6 dated 2022-11-02
DESCRIPTION | 6 - MD5 | 12 +- R/InsepectionVariable.R | 204 +++++++++++++++++++++++++++++++++++---------- R/ParallelInit.R | 14 +-- man/InsepectionVariable.Rd | 11 +- man/ParallelComputing.Rd | 2 man/ParallelInit.Rd | 6 - 7 files changed, 189 insertions(+), 66 deletions(-)
Title: Network Structural Equation Modeling
Description: The network structural equation modeling conducts a network
statistical analysis on a data frame of coincident observations of
multiple continuous variables [1].
It builds a pathway model by exploring a pool of domain knowledge guided
candidate statistical relationships between each of the variable pairs,
selecting the 'best fit' on the basis of a specific criteria such as
adjusted r-squared value.
This material is based upon work supported by the U.S. National Science
Foundation Award EEC-2052776 and EEC-2052662 for the MDS-Rely IUCRC Center,
under the NSF Solicitation:
NSF 20-570 Industry-University Cooperative Research Centers Program
[1] Bruckman, Laura S., Nicholas R. Wheeler, Junheng Ma, Ethan Wang,
Carl K. Wang, Ivan Chou, Jiayang Sun, and Roger H. French. (2013)
<doi:10.1109/ACCESS.2013.2267611>.
Author: Wei-Heng Huang [aut] ,
Nicholas R. Wheeler [aut] ,
Addison G. Klinke [aut] ,
Yifan Xu [aut] ,
Wenyu Du [aut] ,
Amit K. Verma [aut] ,
Abdulkerim Gok [aut] ,
Devin A. Gordon [ctb] ,
Yu Wang [ctb] ,
Sameera Nalin Venkat [ctb] ,
HeinHtet Aung [ctb] ,
Lee [...truncated...]
Maintainer: Laura S. Bruckman <lsh41@case.edu>
Diff between netSEM versions 0.6.0 dated 2022-08-29 and 0.6.1 dated 2022-11-02
DESCRIPTION | 13 +++++++------ MD5 | 20 ++++++++++---------- NEWS.md | 6 ++++++ inst/doc/Backsheet.html | 17 ++++++++++++----- inst/doc/IVfeature.html | 17 ++++++++++++----- inst/doc/PVmodule.html | 17 ++++++++++++----- inst/doc/acrylic.html | 17 ++++++++++++----- inst/doc/crack.html | 17 ++++++++++++----- inst/doc/metal.html | 17 ++++++++++++----- inst/doc/netSEM.html | 17 ++++++++++++----- inst/doc/pet.html | 17 ++++++++++++----- 11 files changed, 119 insertions(+), 56 deletions(-)
Title: Marginal Effects, Marginal Means, Predictions, and Contrasts
Description: Compute and plot adjusted predictions, contrasts, marginal effects, and marginal means for over 70 classes of statistical models in R. Conduct linear and non-linear hypothesis tests using the delta method.
Author: Vincent Arel-Bundock [aut, cre, cph]
,
Marcio Augusto Diniz [ctb] ,
Noah Greifer [ctb]
Maintainer: Vincent Arel-Bundock <vincent.arel-bundock@umontreal.ca>
Diff between marginaleffects versions 0.7.1 dated 2022-09-25 and 0.8.0 dated 2022-11-02
marginaleffects-0.7.1/marginaleffects/vignettes/contrasts.html |only marginaleffects-0.7.1/marginaleffects/vignettes/marginalmeans.html |only marginaleffects-0.7.1/marginaleffects/vignettes/modelsummary.html |only marginaleffects-0.8.0/marginaleffects/DESCRIPTION | 37 marginaleffects-0.8.0/marginaleffects/MD5 | 182 ++-- marginaleffects-0.8.0/marginaleffects/NAMESPACE | 3 marginaleffects-0.8.0/marginaleffects/NEWS.md | 43 marginaleffects-0.8.0/marginaleffects/R/comparisons.R | 56 - marginaleffects-0.8.0/marginaleffects/R/datagrid.R | 41 marginaleffects-0.8.0/marginaleffects/R/find_categorical.R | 21 marginaleffects-0.8.0/marginaleffects/R/get_contrast_data.R | 14 marginaleffects-0.8.0/marginaleffects/R/get_contrast_data_character.R | 39 marginaleffects-0.8.0/marginaleffects/R/get_contrast_data_factor.R | 43 marginaleffects-0.8.0/marginaleffects/R/get_contrast_data_numeric.R | 15 marginaleffects-0.8.0/marginaleffects/R/get_contrasts.R | 86 + marginaleffects-0.8.0/marginaleffects/R/get_se_delta.R | 13 marginaleffects-0.8.0/marginaleffects/R/get_vcov.R | 4 marginaleffects-0.8.0/marginaleffects/R/marginaleffects.R | 2 marginaleffects-0.8.0/marginaleffects/R/marginalmeans.R | 64 - marginaleffects-0.8.0/marginaleffects/R/methods_betareg.R | 29 marginaleffects-0.8.0/marginaleffects/R/methods_crch.R | 42 marginaleffects-0.8.0/marginaleffects/R/methods_glmmTMB.R | 51 - marginaleffects-0.8.0/marginaleffects/R/methods_rms.R |only marginaleffects-0.8.0/marginaleffects/R/package.R | 1 marginaleffects-0.8.0/marginaleffects/R/plot_cap.R | 259 ++++- marginaleffects-0.8.0/marginaleffects/R/plot_cco.R | 127 +- marginaleffects-0.8.0/marginaleffects/R/predictions.R | 39 marginaleffects-0.8.0/marginaleffects/R/sanitize_interaction.R | 14 marginaleffects-0.8.0/marginaleffects/R/sanitize_transform_pre.R | 4 marginaleffects-0.8.0/marginaleffects/R/sanitize_variables.R | 221 +++-- marginaleffects-0.8.0/marginaleffects/R/sanity.R | 24 marginaleffects-0.8.0/marginaleffects/R/sanity_dots.R | 9 marginaleffects-0.8.0/marginaleffects/R/sanity_model.R | 3 marginaleffects-0.8.0/marginaleffects/R/settings.R |only marginaleffects-0.8.0/marginaleffects/R/summary.R | 6 marginaleffects-0.8.0/marginaleffects/R/tidy.R | 3 marginaleffects-0.8.0/marginaleffects/R/tidy.comparisons.R | 8 marginaleffects-0.8.0/marginaleffects/R/tidy.predictions.R | 8 marginaleffects-0.8.0/marginaleffects/R/type_dictionary.R | 7 marginaleffects-0.8.0/marginaleffects/R/warn_once.R | 4 marginaleffects-0.8.0/marginaleffects/README.md | 53 - marginaleffects-0.8.0/marginaleffects/inst/WORDLIST | 11 marginaleffects-0.8.0/marginaleffects/inst/doc/documentation.Rmd | 3 marginaleffects-0.8.0/marginaleffects/inst/doc/documentation.html | 5 marginaleffects-0.8.0/marginaleffects/inst/tinytest/test-analytic.R | 2 marginaleffects-0.8.0/marginaleffects/inst/tinytest/test-bugfix.R | 4 marginaleffects-0.8.0/marginaleffects/inst/tinytest/test-comparisons-interaction.R | 43 marginaleffects-0.8.0/marginaleffects/inst/tinytest/test-comparisons.R | 9 marginaleffects-0.8.0/marginaleffects/inst/tinytest/test-conf.level.R | 8 marginaleffects-0.8.0/marginaleffects/inst/tinytest/test-contrast.R | 2 marginaleffects-0.8.0/marginaleffects/inst/tinytest/test-factor.R | 13 marginaleffects-0.8.0/marginaleffects/inst/tinytest/test-interaction.R | 7 marginaleffects-0.8.0/marginaleffects/inst/tinytest/test-marginaleffects.R | 2 marginaleffects-0.8.0/marginaleffects/inst/tinytest/test-marginalmeans.R | 20 marginaleffects-0.8.0/marginaleffects/inst/tinytest/test-newdata.R | 35 marginaleffects-0.8.0/marginaleffects/inst/tinytest/test-pkg-afex.R | 2 marginaleffects-0.8.0/marginaleffects/inst/tinytest/test-pkg-brms.R | 53 + marginaleffects-0.8.0/marginaleffects/inst/tinytest/test-pkg-fixest.R | 32 marginaleffects-0.8.0/marginaleffects/inst/tinytest/test-pkg-gam.R | 5 marginaleffects-0.8.0/marginaleffects/inst/tinytest/test-pkg-geepack.R | 25 marginaleffects-0.8.0/marginaleffects/inst/tinytest/test-pkg-glmmTMB.R | 53 - marginaleffects-0.8.0/marginaleffects/inst/tinytest/test-pkg-pscl.R | 19 marginaleffects-0.8.0/marginaleffects/inst/tinytest/test-pkg-rms.R | 27 marginaleffects-0.8.0/marginaleffects/inst/tinytest/test-pkg-stats.R | 14 marginaleffects-0.8.0/marginaleffects/inst/tinytest/test-plot_cap.R | 15 marginaleffects-0.8.0/marginaleffects/inst/tinytest/test-plot_cco.R | 10 marginaleffects-0.8.0/marginaleffects/inst/tinytest/test-predictions.R | 54 + marginaleffects-0.8.0/marginaleffects/inst/tinytest/test-typical.R | 2 marginaleffects-0.8.0/marginaleffects/inst/tinytest/test-variables.R | 4 marginaleffects-0.8.0/marginaleffects/man/comparisons.Rd | 31 marginaleffects-0.8.0/marginaleffects/man/datagrid.Rd | 3 marginaleffects-0.8.0/marginaleffects/man/datagridcf.Rd | 24 marginaleffects-0.8.0/marginaleffects/man/get_vcov.Rd | 5 marginaleffects-0.8.0/marginaleffects/man/marginaleffects.Rd | 5 marginaleffects-0.8.0/marginaleffects/man/marginalmeans.Rd | 24 marginaleffects-0.8.0/marginaleffects/man/meffects.Rd | 5 marginaleffects-0.8.0/marginaleffects/man/plot_cap.Rd | 15 marginaleffects-0.8.0/marginaleffects/man/plot_cco.Rd | 2 marginaleffects-0.8.0/marginaleffects/man/predictions.Rd | 48 - marginaleffects-0.8.0/marginaleffects/man/set_coef.Rd | 4 marginaleffects-0.8.0/marginaleffects/man/summary.comparisons.Rd | 2 marginaleffects-0.8.0/marginaleffects/man/summary.marginaleffects.Rd | 2 marginaleffects-0.8.0/marginaleffects/man/summary.predictions.Rd | 2 marginaleffects-0.8.0/marginaleffects/man/tidy.comparisons.Rd | 4 marginaleffects-0.8.0/marginaleffects/man/tidy.marginaleffects.Rd | 4 marginaleffects-0.8.0/marginaleffects/man/tidy.marginalmeans.Rd | 2 marginaleffects-0.8.0/marginaleffects/man/tidy.predictions.Rd | 4 marginaleffects-0.8.0/marginaleffects/man/typical.Rd | 3 marginaleffects-0.8.0/marginaleffects/vignettes/documentation.Rmd | 3 marginaleffects-0.8.0/marginaleffects/vignettes/logistic_contrasts.html | 436 ++++++++-- marginaleffects-0.8.0/marginaleffects/vignettes/mcmc_posterior_draws.pickle |only marginaleffects-0.8.0/marginaleffects/vignettes/plot.html |only marginaleffects-0.8.0/marginaleffects/vignettes/predictions.html | 85 - marginaleffects-0.8.0/marginaleffects/vignettes/python.html |only marginaleffects-0.8.0/marginaleffects/vignettes/sandwich.html | 287 +++--- marginaleffects-0.8.0/marginaleffects/vignettes/supported_models.html |only marginaleffects-0.8.0/marginaleffects/vignettes/transformation.html |only 97 files changed, 2125 insertions(+), 929 deletions(-)
More information about marginaleffects at CRAN
Permanent link
Title: Call R from R
Description: It is sometimes useful to perform a computation in a separate
R process, without affecting the current R process at all. This
packages does exactly that.
Author: Gabor Csardi [aut, cre, cph] ,
Winston Chang [aut],
RStudio [cph, fnd],
Mango Solutions [cph, fnd]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>
Diff between callr versions 3.7.2 dated 2022-08-22 and 3.7.3 dated 2022-11-02
callr-3.7.2/callr/man/new_callr_error.Rd |only callr-3.7.3/callr/DESCRIPTION | 10 callr-3.7.3/callr/MD5 | 31 +- callr-3.7.3/callr/NEWS.md | 7 callr-3.7.3/callr/R/error.R | 76 ++++- callr-3.7.3/callr/R/errors.R | 100 +++++- callr-3.7.3/callr/R/eval.R | 4 callr-3.7.3/callr/R/r-session.R | 5 callr-3.7.3/callr/R/result.R | 40 +- callr-3.7.3/callr/R/script.R | 33 +- callr-3.7.3/callr/R/setup.R | 3 callr-3.7.3/callr/man/callr-package.Rd | 102 +++--- callr-3.7.3/callr/man/new_callr_crash_error.Rd |only callr-3.7.3/callr/man/r.Rd | 8 callr-3.7.3/callr/man/r_bg.Rd | 8 callr-3.7.3/callr/tests/testthat/_snaps |only callr-3.7.3/callr/tests/testthat/helper.R | 37 ++ callr-3.7.3/callr/tests/testthat/test-error.R | 369 ++++++++++++------------- 18 files changed, 522 insertions(+), 311 deletions(-)
Title: Explicitly Qualifying Namespaces by Automatically Adding 'pkg::'
to Functions
Description: Automatically adding 'pkg::' to a function, i.e. mutate()
becomes dplyr::mutate(). It is up to the user to determine which
packages should be used explicitly, whether to include base R packages
or use the functionality on selected text, a file, or a complete
directory. User friendly logging is provided in the 'RStudio' Markers
pane. Lives in the spirit of 'lintr' and 'styler'. Can also be used
for checking which packages are actually used in a project.
Author: Matthias Nistler
Maintainer: Matthias Nistler <m_nistler@web.de>
Diff between origin versions 1.0.0 dated 2022-10-24 and 1.1.0 dated 2022-11-02
DESCRIPTION | 8 MD5 | 93 +++---- NAMESPACE | 17 + NEWS.md | 27 +- R/apply_changes.R | 61 ++-- R/check_pkg_usage.R | 346 +++++++++++++-------------- R/exclude_local_functions.R | 16 + R/find_functions.R | 2 R/fix_html_tokens.R | 94 +++---- R/get_function_calls.R | 22 + R/get_function_definitions.R | 4 R/get_parsed_data.R | 9 R/get_pkgs_from_description.R | 49 ++- R/get_project_package.R | 26 +- R/originize.R | 53 ++-- R/originize_dir.R | 54 ++-- R/originize_pkg.R | 36 +- R/originize_wrap.R | 132 ++++++---- R/print.pkg_usage.R | 212 +++++++++++++--- R/revert_parse_data.R | 58 ++++ R/solve_fun_duplicates.R | 45 +-- R/solve_local_duplicates.R | 42 +-- R/testscript.R | 2 README.md | 12 inst/doc/origin.Rmd | 31 +- inst/doc/origin.html | 31 +- inst/testdata/testscript.csv | 43 +++ inst/testpath/file1.R | 4 man/get_pkgs_from_description.Rd | 6 man/originize_dir.Rd | 4 man/originize_file.Rd | 4 man/originize_pkg.Rd | 4 man/originize_selection.Rd | 4 man/print.pkg_usage.Rd | 4 tests/testthat/_snaps |only tests/testthat/test-apply_changes.R |only tests/testthat/test-check_pkg_usage.R | 200 ++++++++++++--- tests/testthat/test-duplicated_all.R | 6 tests/testthat/test-find_functions.R | 1 tests/testthat/test-get_exported_functions.R | 8 tests/testthat/test-get_local_functions.R | 3 tests/testthat/test-get_project_package.R | 4 tests/testthat/test-list_files.R | 16 - tests/testthat/test-originize_dir.R | 30 ++ tests/testthat/test-originize_file.R | 7 tests/testthat/test-originize_wrap.R | 103 ++++++++ tests/testthat/test-print.R |only tests/testthat/test-revert_parse_data.R |only vignettes/origin.Rmd | 31 +- 49 files changed, 1275 insertions(+), 689 deletions(-)
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2016-10-14 0.4.3
2016-09-12 0.4.2
2016-08-01 0.4.1
2016-06-26 0.4.0
2016-05-13 0.3.1
2016-04-26 0.3.0
2016-03-15 0.2.2
2016-03-14 0.2.1
Title: Analyze Experimental High-Throughput (Omics) Data
Description: The efficient treatment and convenient analysis of experimental high-throughput (omics) data gets facilitated through this collection of diverse functions.
Several functions address advanced object-conversions, like manipulating lists of lists or lists of arrays, reorganizing lists to arrays or into separate vectors, merging of multiple entries, etc.
Another set of functions provides speed-optimized calculation of standard deviation (sd), coefficient of variance (CV) or standard error of the mean (SEM)
for data in matrixes or means per line with respect to additional grouping (eg n groups of replicates).
Other functions facilitate dealing with non-redundant information, by indexing unique, adding counters to redundant or eliminating lines with respect redundancy in a given reference-column, etc.
Help is provided to identify very closely matching numeric values to generate (partial) distance matrixes for very big data in a memory efficient manner or to reduce the complexity of large dat [...truncated...]
Author: Wolfgang Raffelsberger [aut, cre]
Maintainer: Wolfgang Raffelsberger <w.raffelsberger@gmail.com>
Diff between wrMisc versions 1.10.1 dated 2022-10-17 and 1.10.2 dated 2022-11-02
DESCRIPTION | 6 MD5 | 22 + NAMESPACE | 1 R/packageDownloadStat.R | 79 ++++-- R/replicateStructure.R | 105 ++++---- R/unifyEnumerator.R |only inst/doc/wrMiscVignette1.R | 5 inst/doc/wrMiscVignette1.Rmd | 32 ++ inst/doc/wrMiscVignette1.html | 493 +++++++++++++++++++++--------------------- man/packageDownloadStat.Rd | 12 - man/replicateStructure.Rd | 22 - man/unifyEnumerator.Rd |only vignettes/wrMiscVignette1.Rmd | 32 ++ 13 files changed, 458 insertions(+), 351 deletions(-)
Title: Manage R Configuration at the Command Line
Description: Configuration management using files (JSON, YAML, separated text),
JSON strings, and command line arguments. Command line arguments
can be used to override configuration. Period-separated command line
flags are parsed as hierarchical lists.
Author: Peter Solymos [aut, cre] ,
Analythium Solutions Inc. [cph, fnd]
Maintainer: Peter Solymos <peter@analythium.io>
Diff between rconfig versions 0.1.3 dated 2022-06-22 and 0.1.5 dated 2022-11-02
DESCRIPTION | 10 +++++----- MD5 | 12 ++++++------ NEWS.md | 7 +++++++ R/config.R | 25 +++++++++++++++---------- R/parsers.R | 17 +++++------------ inst/examples/plumber/index.R | 2 -- man/rconfig.Rd | 5 ++++- 7 files changed, 42 insertions(+), 36 deletions(-)
Title: Breeding Program Simulations
Description: The successor to the 'AlphaSim' software for breeding program
simulation [Faux et al. (2016) <doi:10.3835/plantgenome2016.02.0013>].
Used for stochastic simulations of breeding programs to the level of DNA
sequence for every individual. Contained is a wide range of functions for
modeling common tasks in a breeding program, such as selection and crossing.
These functions allow for constructing simulations of highly complex plant and
animal breeding programs via scripting in the R software environment. Such
simulations can be used to evaluate overall breeding program performance and
conduct research into breeding program design, such as implementation of
genomic selection. Included is the 'Markovian Coalescent Simulator' ('MaCS')
for fast simulation of biallelic sequences according to a population
demographic history [Chen et al. (2009) <doi:10.1101/gr.083634.108>].
Author: Chris Gaynor [aut, cre] ,
Gregor Gorjanc [ctb] ,
John Hickey [ctb] ,
Daniel Money [ctb] ,
David Wilson [ctb],
Thiago Oliveira [ctb]
Maintainer: Chris Gaynor <gaynor.robert@hotmail.com>
Diff between AlphaSimR versions 1.3.1 dated 2022-08-25 and 1.3.2 dated 2022-11-02
DESCRIPTION | 8 ++++---- MD5 | 26 +++++++++++++------------- NEWS.md | 16 ++++++++++++---- R/Class-Pop.R | 11 +++++++++++ R/Class-SimParam.R | 2 +- R/GS.R | 3 +++ R/founderPop.R | 12 ++++++++++++ R/misc.R | 6 ++++++ R/pullGeno.R | 4 ---- build/partial.rdb |binary inst/doc/intro.html | 6 +++--- inst/doc/traits.pdf |binary src/misc.cpp | 6 +++++- src/simulator.cpp | 7 ++----- 14 files changed, 72 insertions(+), 35 deletions(-)
Title: Machine Learning in R - Next Generation
Description: Efficient, object-oriented programming on the
building blocks of machine learning. Provides 'R6' objects for tasks,
learners, resamplings, and measures. The package is geared towards
scalability and larger datasets by supporting parallelization and
out-of-memory data-backends like databases. While 'mlr3' focuses on
the core computational operations, add-on packages provide additional
functionality.
Author: Michel Lang [cre, aut] ,
Bernd Bischl [aut] ,
Jakob Richter [aut] ,
Patrick Schratz [aut] ,
Giuseppe Casalicchio [ctb] ,
Stefan Coors [ctb] ,
Quay Au [ctb] ,
Martin Binder [aut],
Florian Pfisterer [aut] ,
Raphael Sonabend [aut] ,
Lennart Schneider [c [...truncated...]
Maintainer: Michel Lang <michellang@gmail.com>
Diff between mlr3 versions 0.14.0 dated 2022-08-11 and 0.14.1 dated 2022-11-02
DESCRIPTION | 89 +- MD5 | 92 +- NAMESPACE | 8 NEWS.md | 12 R/DataBackendCbind.R | 4 R/DataBackendMatrix.R | 4 R/Learner.R | 9 R/LearnerClassifRpart.R | 8 R/LearnerRegr.R | 3 R/LearnerRegrRpart.R | 10 R/MeasureElapsedTime.R | 1 R/PredictionDataRegr.R | 2 R/PredictionRegr.R | 14 R/ResamplingSubsampling.R | 2 R/ResultData.R | 3 R/Task.R | 39 - R/as_learner.R | 12 R/as_measure.R | 16 R/as_prediction_classif.R | 1 R/as_resampling.R | 10 R/as_task.R | 14 R/helper_hashes.R | 2 R/helper_print.R | 4 R/mlr_reflections.R | 11 R/worker.R | 19 README.md | 243 +++--- inst/testthat/helper_expectations.R | 6 man/LearnerRegr.Rd | 3 man/PredictionRegr.Rd | 10 man/Task.Rd | 6 man/as_learner.Rd | 8 man/as_measure.Rd | 10 man/as_resampling.Rd | 6 man/as_task.Rd | 6 man/figures/mlr3verse.svg | 855 +++++++++++++---------- man/mlr3-package.Rd | 6 man/mlr_learners_classif.rpart.Rd | 16 man/mlr_learners_regr.rpart.Rd | 17 man/mlr_reflections.Rd | 4 man/mlr_resamplings_subsampling.Rd | 4 tests/testthat/test_Measure.R | 7 tests/testthat/test_PredictionClassif.R | 4 tests/testthat/test_Task.R | 6 tests/testthat/test_as_learner.R |only tests/testthat/test_as_measure.R |only tests/testthat/test_as_resampling.R |only tests/testthat/test_as_task.R |only tests/testthat/test_convert_task.R | 8 tests/testthat/test_mlr_learners_classif_debug.R | 15 49 files changed, 918 insertions(+), 711 deletions(-)
Title: 'IP' Address 'Lookup'
Description: A micro-package for getting your 'IP' address, either the
local/internal or the public/external one. Currently only 'IPv4' addresses
are supported.
Author: Drew Schmidt [aut, cre],
Wei-Chen Chen [aut]
Maintainer: Drew Schmidt <wrathematics@gmail.com>
Diff between getip versions 0.1-0 dated 2021-11-02 and 0.1-2 dated 2022-11-02
ChangeLog | 6 ++++++ DESCRIPTION | 6 +++--- MD5 | 16 ++++++++-------- README.md | 29 ++++++++++++++++++++++++++--- configure | 27 +++++++++++++++++++-------- configure.ac | 27 +++++++++++++++++++-------- src/Makevars.in | 2 +- src/getip_native.c | 2 +- src/ip_internal.c | 10 +++++----- 9 files changed, 88 insertions(+), 37 deletions(-)
Title: Gadget is the Globally-Applicable Area Disaggregated General
Ecosystem Toolbox
Description: A statistical ecosystem modelling package, taking many features of
the ecosystem into account. Gadget works by running an internal
model based on many parameters, and then comparing the data from
the output of this model to real data to get a goodness-of-fit
likelihood score. These parameters can then be adjusted, and the
model re-run, until an optimum is found, which corresponds to the
model with the lowest likelihood score. Gadget allows the user to
include a number of features into an ecosystem model: One or more
species, each of which may be split into multiple stocks; multiple
areas with migration between areas; predation between and within
species; maturation; reproduction and recruitment; multiple
commercial and survey fleets taking catches from the populations.
For more details see <https://gadget-framework.github.io/gadget2/>.
This is the C++ Gadget2 runtime, making it available for R.
Author: Bjarki Thor Elvarsson [aut, cre],
James Begley [aut],
Hoskuldur Bjornsson [aut],
Jamie Lentin [ctb],
Gunnar Stefansson [ctb],
Lorna Taylor [ctb],
Daniel Howell [ctb],
Sigurdur Hannesson [ctb],
Narfi Stefansson [aut],
Hersir Sigurgeirsson [ctb],
Morte [...truncated...]
Maintainer: Bjarki Thor Elvarsson <bjarki.elvarsson@hafogvatn.is>
Diff between gadget2 versions 2.3.7 dated 2020-11-21 and 2.3.9 dated 2022-11-02
gadget2-2.3.7/gadget2/README.md |only gadget2-2.3.7/gadget2/cleanup |only gadget2-2.3.9/gadget2/DESCRIPTION | 14 +- gadget2-2.3.9/gadget2/MD5 | 10 - gadget2-2.3.9/gadget2/src/likelihoodprinter.cc | 2 gadget2-2.3.9/gadget2/src/proglikelihood.cc | 134 ++++++++++++------------- gadget2-2.3.9/gadget2/src/spawner.cc | 24 ++-- 7 files changed, 91 insertions(+), 93 deletions(-)
Title: Generalized Hyperbolic Distribution and Its Special Cases
Description: Detailed functionality for working
with the univariate and multivariate Generalized Hyperbolic
distribution and its special cases (Hyperbolic (hyp), Normal
Inverse Gaussian (NIG), Variance Gamma (VG), skewed Student-t
and Gaussian distribution). Especially, it contains fitting
procedures, an AIC-based model selection routine, and functions
for the computation of density, quantile, probability, random
variates, expected shortfall and some portfolio optimization
and plotting routines as well as the likelihood ratio test. In
addition, it contains the Generalized Inverse Gaussian
distribution. See Chapter 3 of A. J. McNeil, R. Frey, and P. Embrechts.
Quantitative risk management: Concepts, techniques and tools.
Princeton University Press, Princeton (2005).
Author: Marc Weibel, David Luethi, Wolfgang Breymann
Maintainer: Marc Weibel <marc.weibel@quantsulting.ch>
Diff between ghyp versions 1.6.2 dated 2022-05-10 and 1.6.3 dated 2022-11-02
DESCRIPTION | 8 MD5 | 10 build/vignette.rds |binary inst/doc/Generalized_Hyperbolic_Distribution.R | 368 +++++++++++------------ inst/doc/Generalized_Hyperbolic_Distribution.pdf |binary src/rgig.c | 14 6 files changed, 196 insertions(+), 204 deletions(-)
Title: Stochastic Newton Sampler (SNS)
Description: Stochastic Newton Sampler (SNS) is a Metropolis-Hastings-based, Markov Chain Monte Carlo sampler for twice differentiable, log-concave probability density functions (PDFs) where the proposal density function is a multivariate Gaussian resulting from a second-order Taylor-series expansion of log-density around the current point. The mean of the Gaussian proposal is the full Newton-Raphson step from the current point. A Boolean flag allows for switching from SNS to Newton-Raphson optimization (by choosing the mean of proposal function as next point). This can be used during burn-in to get close to the mode of the PDF (which is unique due to concavity). For high-dimensional densities, mixing can be improved via 'state space partitioning' strategy, in which SNS is applied to disjoint subsets of state space, wrapped in a Gibbs cycle. Numerical differentiation is available when analytical expressions for gradient and Hessian are not available. Facilities for validation and numerical differen [...truncated...]
Author: Alireza S. Mahani, Asad Hasan, Marshall Jiang, Mansour T.A. Sharabiani
Maintainer: Alireza Mahani <alireza.s.mahani@gmail.com>
Diff between sns versions 1.1.2 dated 2016-10-25 and 1.2.2 dated 2022-11-02
ChangeLog | 9 DESCRIPTION | 10 MD5 | 22 build/vignette.rds |binary inst/CITATION | 52 - inst/doc/SNS.R | 506 +++++++++++---- inst/doc/SNS.Rnw | 1722 +++++++++++++++++++++++++++++------------------------ inst/doc/SNS.pdf |binary man/ess.Rd | 2 man/sns.Rd | 5 man/sns.run.Rd | 5 vignettes/SNS.Rnw | 1722 +++++++++++++++++++++++++++++------------------------ 12 files changed, 2330 insertions(+), 1725 deletions(-)
More information about RcmdrPlugin.EACSPIR at CRAN
Permanent link
Title: 'Tweedie' Compound Poisson Model in the Reproducing Kernel
Hilbert Space
Description: Kernel-based 'Tweedie' compound Poisson gamma model using high-dimensional predictors for the analyses of zero-inflated response variables. The package features built-in estimation, prediction and cross-validation tools and supports choice of different kernel functions.
Author: Yi Lian [aut, cre],
Archer Yi Yang [aut, cph],
Boxiang Wang [aut],
Peng Shi [aut],
Robert W. Platt [aut]
Maintainer: Yi Lian <yi.lian@mail.mcgill.ca>
Diff between ktweedie versions 1.0.0 dated 2022-10-20 and 1.0.1 dated 2022-11-02
ktweedie-1.0.0/ktweedie/src/ktweedie_init.c |only ktweedie-1.0.1/ktweedie/DESCRIPTION | 8 ktweedie-1.0.1/ktweedie/MD5 | 19 ktweedie-1.0.1/ktweedie/R/datadoc.R | 4 ktweedie-1.0.1/ktweedie/README.md |only ktweedie-1.0.1/ktweedie/inst/doc/ktweedie-vignette.R | 3 ktweedie-1.0.1/ktweedie/inst/doc/ktweedie-vignette.Rmd | 11 ktweedie-1.0.1/ktweedie/inst/doc/ktweedie-vignette.html | 334 +++++++--------- ktweedie-1.0.1/ktweedie/man/dat.Rd | 4 ktweedie-1.0.1/ktweedie/src/TD_SK.f90 | 2 ktweedie-1.0.1/ktweedie/src/init.c |only ktweedie-1.0.1/ktweedie/vignettes/ktweedie-vignette.Rmd | 11 12 files changed, 196 insertions(+), 200 deletions(-)
Title: Bayesian Meta-Analysis of Pleiotropic Effects Using Group
Structure
Description: Run a Gibbs sampler for a multivariate Bayesian sparse group selection model with Dirac, continuous and hierarchical spike prior for detecting pleiotropy on the traits. This package is designed for summary statistics containing estimated regression coefficients and its estimated covariance matrix. The methodology is available from: Baghfalaki, T., Sugier, P. E., Truong, T., Pettitt, A. N., Mengersen, K., & Liquet, B. (2021) <doi:10.1002/sim.8855>.
Author: Taban Baghfalaki
Maintainer: Taban Baghfalaki <t.baghfalaki@gmail.com>
Diff between GCPBayes versions 3.1.0 dated 2021-10-21 and 4.0.0 dated 2022-11-02
GCPBayes-3.1.0/GCPBayes/data/datalist |only GCPBayes-4.0.0/GCPBayes/DESCRIPTION | 11 GCPBayes-4.0.0/GCPBayes/MD5 | 44 - GCPBayes-4.0.0/GCPBayes/NAMESPACE | 9 GCPBayes-4.0.0/GCPBayes/NEWS.md | 16 GCPBayes-4.0.0/GCPBayes/R/CS.R | 583 ++++++++-------- GCPBayes-4.0.0/GCPBayes/R/DS.R | 604 ++++++++--------- GCPBayes-4.0.0/GCPBayes/R/GCPBayes.R | 53 - GCPBayes-4.0.0/GCPBayes/R/HS.R | 835 ++++++++++++------------ GCPBayes-4.0.0/GCPBayes/R/MCMCplot.R | 184 ++--- GCPBayes-4.0.0/GCPBayes/R/summaryCS.R |only GCPBayes-4.0.0/GCPBayes/R/summaryDS.R |only GCPBayes-4.0.0/GCPBayes/R/summaryHS.R |only GCPBayes-4.0.0/GCPBayes/inst/exampleCS.R | 450 ++++++------ GCPBayes-4.0.0/GCPBayes/inst/exampleDS.R | 303 ++++---- GCPBayes-4.0.0/GCPBayes/inst/exampleHS.R | 331 +++++---- GCPBayes-4.0.0/GCPBayes/inst/exampleMCMCplot.R | 222 +++--- GCPBayes-4.0.0/GCPBayes/inst/examplesummaryCS.R |only GCPBayes-4.0.0/GCPBayes/inst/examplesummaryDS.R |only GCPBayes-4.0.0/GCPBayes/inst/examplesummaryHS.R |only GCPBayes-4.0.0/GCPBayes/man/CS.Rd | 392 ++++++----- GCPBayes-4.0.0/GCPBayes/man/DS.Rd | 276 ++++--- GCPBayes-4.0.0/GCPBayes/man/GCPBayes.Rd | 3 GCPBayes-4.0.0/GCPBayes/man/HS.Rd | 313 ++++---- GCPBayes-4.0.0/GCPBayes/man/MCMCplot.Rd | 56 + GCPBayes-4.0.0/GCPBayes/man/summaryCS.Rd |only GCPBayes-4.0.0/GCPBayes/man/summaryDS.Rd |only GCPBayes-4.0.0/GCPBayes/man/summaryHS.Rd |only 28 files changed, 2478 insertions(+), 2207 deletions(-)
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 prior [...truncated...]
Author: Merlise Clyde [aut, cre, cph] ,
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 1.6.3 dated 2022-10-19 and 1.6.4 dated 2022-11-02
DESCRIPTION | 8 +- MD5 | 15 ++-- NEWS.md | 12 +++ R/bas_lm.R | 32 +++++--- inst/doc/BAS-vignette.html | 126 +++++++++++++++++------------------ man/bas.glm.Rd | 43 +++++++---- man/bas.lm.Rd | 36 ++++++---- tests/testthat/test-bas-lm-lowrank.R |only tests/testthat/test-bas-lm.R | 50 ------------- 9 files changed, 155 insertions(+), 167 deletions(-)
Title: Tools for ABC Analyses
Description: Tools for approximate Bayesian computation including summary statistic selection and assessing coverage.
Author: Matt Nunes [aut, cre],
Dennis Prangle [aut],
Guilhereme Rodrigues [ctb]
Maintainer: Matt Nunes <nunesrpackages@gmail.com>
Diff between abctools versions 1.1.3 dated 2018-07-17 and 1.1.4 dated 2022-11-02
DESCRIPTION | 13 +++++----- MD5 | 21 ++++++++--------- NAMESPACE | 1 R/semiauto.abc.R | 2 - data/coal.rda |binary data/coalobs.rda |binary man/abctools-package.Rd | 12 ++++----- man/mincrit.Rd | 4 +-- man/selectsumm.Rd | 2 + man/semiauto.abc.Rd | 2 - src/abctools.c | 59 ++++++++++++------------------------------------ src/abctools.h |only 12 files changed, 45 insertions(+), 71 deletions(-)
Title: Zero-Variance Control Variates
Description: Stein control variates can be used to improve Monte Carlo estimates of expectations when the derivatives of the log target are available. This package implements a variety of such methods, including zero-variance control variates (ZV-CV, Mira et al. (2013) <doi:10.1007/s11222-012-9344-6>), regularised ZV-CV (South et al., 2018 <arXiv:1811.05073>), control functionals (CF, Oates et al. (2017) <doi:10.1111/rssb.12185>) and semi-exact control functionals (SECF, South et al., 2020 <arXiv:2002.00033>). ZV-CV is a parametric approach that is exact for (low order) polynomial integrands with Gaussian targets. CF is a non-parametric alternative that offers better than the standard Monte Carlo convergence rates. SECF has both a parametric and a non-parametric component and it offers the advantages of both for an additional computational cost. Functions for applying ZV-CV and CF to two estimators for the normalising constant of the posterior distribution in Bayesian statis [...truncated...]
Author: Leah F. South [aut, cre]
Maintainer: Leah F. South <leah.south@hdr.qut.edu.au>
Diff between ZVCV versions 2.1.1 dated 2021-06-30 and 2.1.2 dated 2022-11-02
DESCRIPTION | 8 ++++---- MD5 | 6 +++--- NEWS.md | 6 ------ src/fnToExport.cpp | 4 ++-- 4 files changed, 9 insertions(+), 15 deletions(-)
Title: Variable Table for Variable Documentation
Description: Automatically generates HTML variable documentation including variable names, labels, classes, value labels (if applicable), value ranges, and summary statistics. See the vignette "vtable" for a package overview.
Author: Nick Huntington-Klein [aut, cre]
Maintainer: Nick Huntington-Klein <nhuntington-klein@seattleu.edu>
Diff between vtable versions 1.3.4 dated 2022-07-16 and 1.4.1 dated 2022-11-02
DESCRIPTION | 10 ++--- MD5 | 26 +++++++------- NEWS.md | 7 +++ R/helpers.R | 79 +++++++++++++++++++++++++++---------------- R/labeltable.R | 26 ++++++++++---- R/sumtable.R | 54 ++++++++++++++++++++++++++--- inst/doc/dftotable.html | 17 ++++++--- inst/doc/labeltable.html | 17 ++++++--- inst/doc/sumtable.html | 17 ++++++--- inst/doc/vtable.html | 4 +- inst/doc/vtablefunction.html | 17 ++++++--- inst/doc/vtablehelpers.html | 23 ++++++++---- man/labeltable.Rd | 6 +++ man/sumtable.Rd | 8 ++++ 14 files changed, 223 insertions(+), 88 deletions(-)
Title: Transformation Models
Description: Formula-based user-interfaces to specific transformation models
implemented in package 'mlt'. Available models include Cox models, some parametric
survival models (Weibull, etc.), models for ordered categorical variables,
normal and non-normal (Box-Cox type) linear models, and continuous outcome logistic regression
(Lohse et al., 2017, <DOI:10.12688/f1000research.12934.1>). The underlying theory
is described in Hothorn et al. (2018) <DOI:10.1111/sjos.12291>. An extension to
transformation models for clustered data is provided (Barbanti and Hothorn, 2022, <arxiv:1910.09219>).
Multivariate conditional transformation models (Klein et al, 2022, <DOI:10.1111/sjos.12501>)
can be fitted as well.
Author: Torsten Hothorn [aut, cre] ,
Luisa Barbanti [aut] ,
Sandra Siegfried [aut] ,
Brian Ripley [ctb],
Bill Venables [ctb],
Douglas M. Bates [ctb],
Nadja Klein [ctb]
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>
Diff between tram versions 0.7-2 dated 2022-08-07 and 0.8-0 dated 2022-11-02
DESCRIPTION | 16 MD5 | 38 NAMESPACE | 17 R/ltmatrices.R |only R/mmlt.R | 738 +--- R/mtram.R | 11 build/partial.rdb |binary build/vignette.rds |binary demo/mtram.R | 6478 +------------------------------------------ demo/undernutrition.R | 42 inst/NEWS.Rd | 12 inst/doc/mtram.pdf |binary inst/doc/tram.pdf |binary inst/simulations/README.txt | 16 inst/simulations/mtram_sim.R |only inst/simulations/sim2d.R | 2 inst/simulations/sim5d.R | 2 man/ltmatrices.Rd |only man/mmlt.Rd | 79 man/mtram.Rd | 22 tests/ltmatrices-Ex.R |only vignettes/mtram-rendered.pdf |binary 22 files changed, 689 insertions(+), 6784 deletions(-)
Title: Inferring Differentially Expressed Genes using Generalized
Linear Mixed Models
Description: Genes that are differentially expressed between two or more experimental conditions can be detected in RNA-Seq. A high biological variability may impact the discovery of these genes once it may be divergent between the fixed effects. However, this variability can be covered by the random effects. 'DEGRE' was designed to identify the differentially expressed genes considering fixed and random effects on individuals. These effects are identified earlier in the experimental design matrix. 'DEGRE' has the implementation of preprocessing procedures to clean the near zero gene reads in the count matrix, normalize by 'RLE' published in the 'DESeq2' package, 'Love et al. (2014)' <doi:10.1186/s13059-014-0550-8> and it fits a regression for each gene using the Generalized Linear Mixed Model with the negative binomial distribution, followed by a Wald test to assess the regression coefficients.
Author: Douglas Terra Machado [aut, cre]
,
Otavio Jose Bernardes Brustolini [aut]
,
Yasmmin Cortes Martins [aut] ,
Marco Antonio Grivet Mattoso Maia [aut]
,
Ana Tereza Ribeiro de Vasconcelos [aut]
Maintainer: Douglas Terra Machado <dougterra@gmail.com>
Diff between DEGRE versions 0.1.0 dated 2022-11-01 and 0.2.0 dated 2022-11-02
DESCRIPTION | 14 +++++++------- MD5 | 4 ++-- README.md | 6 ++---- 3 files changed, 11 insertions(+), 13 deletions(-)
Title: Spatio-Temporal Modeling of Large Data Using a Spectral SPDE
Approach
Description: Functionality for spatio-temporal modeling of large data sets is provided. A Gaussian process in space and time is defined through a stochastic partial differential equation (SPDE). The SPDE is solved in the spectral space, and after discretizing in time and space, a linear Gaussian state space model is obtained. When doing inference, the main computational difficulty consists in evaluating the likelihood and in sampling from the full conditional of the spectral coefficients, or equivalently, the latent space-time process. In comparison to the traditional approach of using a spatio-temporal covariance function, the spectral SPDE approach is computationally advantageous. See Sigrist, Kuensch, and Stahel (2015) <doi:10.1111/rssb.12061> for more information on the methodology. This package aims at providing tools for two different modeling approaches. First, the SPDE based spatio-temporal model can be used as a component in a customized hierarchical Bayesian model (HBM). The functio [...truncated...]
Author: Fabio Sigrist, Hans R. Kuensch, Werner A. Stahel
Maintainer: Fabio Sigrist <fabiosigrist@gmail.com>
Diff between spate versions 1.7.3 dated 2022-10-21 and 1.7.4 dated 2022-11-02
DESCRIPTION | 6 +++--- MD5 | 4 ++-- inst/doc/spate_tutorial.pdf |binary 3 files changed, 5 insertions(+), 5 deletions(-)
Title: Poisson Network Autoregressive Models
Description: Quasi likelihood-based methods for estimating Poisson Network Autoregression with p lags, PNAR, following generalized linear models are provided. PNAR models with the identity and with the logarithmic link function are allowed. The inclusion of exogenous covariates is also possible. Moreover, it provides tools for testing the linearity of linear PNAR model versus several nonlinear alternatives. Finally, it allows generating multivariate count distributions, from linear and nonlinear PNAR models, where the dependence between Poisson random variables is generated by suitable copulas. References include: Armillotta, M. and K. Fokianos (2022a). Poisson network autoregression. <arXiv:2104.06296>. Armillotta, M. and K. Fokianos (2022b). Testing linearity for network autoregressive models. <arXiv:2202.03852>.
Author: Michail Tsagris [aut, cre],
Mirko Armillotta [aut, cph],
Konstantinos Fokianos [aut]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>
Diff between PNAR versions 1.2 dated 2022-10-05 and 1.3 dated 2022-11-02
DESCRIPTION | 8 ++++---- MD5 | 14 +++++++++----- NAMESPACE | 7 +++++-- R/lin_estimnarpq.R | 14 +++++++++++--- R/lin_ic_plot.R |only R/log_lin_estimnarpq.R | 41 ++++++++++++++++++++++++++++------------- R/log_lin_ic_plot.R |only man/PNAR-package.Rd | 4 ++-- man/lin_ic_plot.Rd |only man/log_lin_ic_plot.Rd |only 10 files changed, 59 insertions(+), 29 deletions(-)
Title: Nonlinear Mixed Effects Models in Population PK/PD, Estimation
Routines
Description: Fit and compare nonlinear mixed-effects models in
differential equations with flexible dosing information commonly seen
in pharmacokinetics and pharmacodynamics (Almquist, Leander, and
Jirstrand 2015 <doi:10.1007/s10928-015-9409-1>). Differential equation
solving is by compiled C code provided in the 'rxode2' package (Wang,
Hallow, and James 2015 <doi:10.1002/psp4.12052>).
Author: Matthew Fidler [aut, cre] ,
Yuan Xiong [aut],
Rik Schoemaker [aut] ,
Justin Wilkins [aut] ,
Wenping Wang [aut],
Robert Leary [ctb],
Mason McComb [ctb] ,
Vipul Mann [aut],
Mirjam Trame [ctb],
Mahmoud Abdelwahab [ctb],
Teun Post [ctb],
Richard Hooijmai [...truncated...]
Maintainer: Matthew Fidler <matthew.fidler@gmail.com>
Diff between nlmixr2est versions 2.1.1 dated 2022-10-22 and 2.1.2 dated 2022-11-02
DESCRIPTION | 9 +++-- MD5 | 53 ++++++++++++++++----------------- NAMESPACE | 1 NEWS.md | 9 +++++ R/focei.R | 15 ++++++++- R/nlme.R | 1 R/nlmixr2_md5.R | 2 - R/nmObjGet.R | 14 ++++++++ R/resid.R | 7 ++++ R/saem.R | 10 +++--- R/saemRxUiGet.R | 4 +- man/figures/README-example-1.png |binary man/nlmixr2CreateOutputFromUi.Rd | 1 man/nmObjGet.Rd | 3 + src/Makevars.in | 2 - src/censResid.cpp | 2 - src/censResid.h | 2 - src/cwres.cpp | 18 +++++------ src/inner.cpp | 50 ++++++++++++++----------------- src/ires.cpp | 14 ++++---- src/npde.cpp | 38 +++++++++++------------ src/res.cpp | 16 ++++----- src/res.h | 2 - src/shrink.cpp | 4 +- src/shrink.h | 2 - tests/testthat/test-focei-char.R |only tests/testthat/test-focei-preprocess.R | 22 +++++++++++++ tests/testthat/test-timing.R | 37 +++++++++++------------ 28 files changed, 205 insertions(+), 133 deletions(-)
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2022-10-18 2.0.1
2022-04-05 1.0.1
2021-02-17 0.0.1
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2022-10-28 0.4
2020-04-02 0.2
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2022-10-15 0.12