Title: Stepwise Split Regularized Regression
Description: Functions to perform stepwise split regularized regression. The approach first
uses a stepwise algorithm to split the variables into the models with a goodness
of fit criterion, and then regularization is applied to each model. The weights
of the models in the ensemble are determined based on a criterion selected by
the user.
Author: Anthony Christidis [aut, cre],
Stefan Van Aelst [aut],
Ruben Zamar [aut]
Maintainer: Anthony Christidis <anthony.christidis@stat.ubc.ca>
Diff between stepSplitReg versions 1.0.1 dated 2022-03-16 and 1.0.2 dated 2022-06-26
DESCRIPTION | 8 ++++---- MD5 | 8 ++++---- NEWS | 6 +++++- src/Model.cpp | 11 ++++++----- src/stepSplitReg_Main.cpp | 26 ++++++++++++++------------ 5 files changed, 33 insertions(+), 26 deletions(-)
Title: Graph Neural Network-Based Framework for Single Cell Active
Pathways and Gene Modules Analysis
Description: It is a single cell active pathway analysis tool based on the graph neural network (F. Scarselli (2009) <doi:10.1109/TNN.2008.2005605>; Thomas N. Kipf (2017) <arXiv:1609.02907v4>) to construct the gene-cell association network, infer pathway activity scores from different single cell modalities data, integrate multiple modality data on the same cells into one pathway activity score matrix, identify cell phenotype activated gene modules and parse association networks of gene modules under multiple cell phenotype. In addition, abundant visualization programs are provided to display the results.
Author: Xudong Han [aut, cre, cph],
Xujiang Guo [fnd]
Maintainer: Xudong Han <hanxd1217@163.com>
Diff between scapGNN versions 0.1.0 dated 2022-06-10 and 0.1.1 dated 2022-06-26
DESCRIPTION | 14 - MD5 | 15 - R/plotCCNetwork.R | 65 ++--- build/vignette.rds |binary inst/doc/vignette.R | 8 inst/doc/vignette.Rmd | 25 +- inst/doc/vignette.html | 524 +++++++++++++++++++++++++++++++++++------------ inst/extdata/heatmap.png |only vignettes/vignette.Rmd | 25 +- 9 files changed, 498 insertions(+), 178 deletions(-)
Title: Compose Sentences to Describe Comparisons
Description: Create dynamic, data-driven text. Given two values, a list of
talking points is generated and can be combined using string
interpolation. Based on the 'glue' package.
Author: Jake Riley [aut, cre]
Maintainer: Jake Riley <rjake@sas.upenn.edu>
Diff between headliner versions 0.0.1 dated 2022-06-02 and 0.0.2 dated 2022-06-26
DESCRIPTION | 6 +- MD5 | 36 ++++++------ NAMESPACE | 5 + NEWS.md | 15 ++++- R/add-headline-column.R | 89 +++++++++++++++++------------- R/compare-values.R | 29 ++++++++- R/data.R | 10 +++ R/headline.R | 45 +++++++++------ R/trend-terms.R | 10 +-- README.md | 38 ++++++------ inst/doc/intro.html | 44 +++++++------- man/add_headline_column.Rd | 6 +- man/compare_values.Rd | 4 - man/headline.Rd | 10 +-- man/pixar_films.Rd | 10 +++ man/trend_terms.Rd | 7 -- tests/testthat/test-add-headline-column.R | 65 +++++++++++++++++++++ tests/testthat/test-compare-values.R | 20 ++++++ tests/testthat/test-headline.R | 28 +++++++++ 19 files changed, 329 insertions(+), 148 deletions(-)
Title: Censored Mixed-Effects Models with Different Correlation
Structures
Description: Left, right or interval censored mixed-effects linear model with autoregressive errors of order p or DEC correlation structure using the type-EM algorithm. The error distribution can be Normal or t-Student. It provides the parameter estimates, the standard errors and prediction of future observations (available only for the normal case). Olivari et all (2021) <doi:10.1080/10543406.2020.1852246>.
Author: Rommy C. Olivari, Kelin Zhong, Aldo M. Garay and Victor H. Lachos
Maintainer: Rommy C. Olivari <rco1@de.ufpe.br>
Diff between ARpLMEC versions 2.4 dated 2022-05-20 and 2.4.1 dated 2022-06-26
DESCRIPTION | 8 +- MD5 | 12 +-- R/ARpMMEC.est.R | 16 ++-- R/EMCensArpN.R | 29 +++----- R/EMCensArpT.R | 20 ++++- R/FunGeral.R | 187 ++++++++++++++++++++++++++++++++++++++++++++++++++++++-- R/MMsimu.R | 9 +- 7 files changed, 233 insertions(+), 48 deletions(-)
Title: Optimal Analysis of Test and Rating Scale Data
Description: Develop, evaluate, and score multiple choice examinations,
psychological scales, questionnaires, and similar types of data involving
sequences of choices among one or more sets of answers.
This version of the package should be considered as brand new. Almost all
of the functions have been changed, including their argument list.
See the file NEWS.Rd in the Inst folder for more information.
Using the package does not require any formal statistical knowledge
beyond what would be provided by a first course in statistics in a
social science department. There the user would encounter the concept
of probability and how it is used to model data and make decisions,
and would become familiar with basic mathematical and statistical notation.
Most of the output is in graphical form. Two
recent papers on the methodology are
Ramsay, James; Li, Juan; Wiberg, Marie (2020) <doi:10.3390/psych2040026> and
Ramsay, James; Wiberg, Marie; Li, Juan (2019) <doi:10.3102/1076998619885636>.
Author: James Ramsay [aut,cre],
Juan Li [aut,cre]
Maintainer: James Ramsay <james.ramsay@mcgill.ca>
Diff between TestGardener versions 2.0.0 dated 2021-11-10 and 3.0.0 dated 2022-06-26
TestGardener-2.0.0/TestGardener/R/Item.plot.R |only TestGardener-2.0.0/TestGardener/R/Wbinsmth.init.R |only TestGardener-2.0.0/TestGardener/R/growsurf.R |only TestGardener-2.0.0/TestGardener/data/Quant_U.rda |only TestGardener-2.0.0/TestGardener/data/Quant_dataList.rda |only TestGardener-2.0.0/TestGardener/data/Quant_key.rda |only TestGardener-2.0.0/TestGardener/data/Quant_parList.rda |only TestGardener-2.0.0/TestGardener/inst/doc/SDSAnalysis.R |only TestGardener-2.0.0/TestGardener/inst/doc/SDSAnalysis.Rmd |only TestGardener-2.0.0/TestGardener/inst/doc/SDSAnalysis.html |only TestGardener-2.0.0/TestGardener/inst/doc/SweSATQuantitativeAnalysis.R |only TestGardener-2.0.0/TestGardener/inst/doc/SweSATQuantitativeAnalysis.Rmd |only TestGardener-2.0.0/TestGardener/inst/doc/SweSATQuantitativeAnalysis.html |only TestGardener-2.0.0/TestGardener/man/Quant_U.Rd |only TestGardener-2.0.0/TestGardener/man/Quant_dataList.Rd |only TestGardener-2.0.0/TestGardener/man/Quant_key.Rd |only TestGardener-2.0.0/TestGardener/man/Quant_parList.Rd |only TestGardener-2.0.0/TestGardener/man/Wbinsmth.init.Rd |only TestGardener-2.0.0/TestGardener/man/Wbinsmth.plot.Rd |only TestGardener-2.0.0/TestGardener/man/item.plot.Rd |only TestGardener-2.0.0/TestGardener/vignettes/SDSAnalysis.Rmd |only TestGardener-2.0.0/TestGardener/vignettes/SweSATQuantitativeAnalysis.Rmd |only TestGardener-2.0.0/TestGardener/vignettes/Ushort.txt |only TestGardener-2.0.0/TestGardener/vignettes/keyshort.txt |only TestGardener-3.0.0/TestGardener/DESCRIPTION | 38 TestGardener-3.0.0/TestGardener/MD5 | 145 +-- TestGardener-3.0.0/TestGardener/NAMESPACE | 7 TestGardener-3.0.0/TestGardener/R/Analyze.R | 99 +- TestGardener-3.0.0/TestGardener/R/ArcLength.plot.R | 18 TestGardener-3.0.0/TestGardener/R/ConditionalSimulation.R | 2 TestGardener-3.0.0/TestGardener/R/Entropy.plot.R | 101 +- TestGardener-3.0.0/TestGardener/R/Hfuns.plot.R | 1 TestGardener-3.0.0/TestGardener/R/ICC.fit.R |only TestGardener-3.0.0/TestGardener/R/ICC.plot.R |only TestGardener-3.0.0/TestGardener/R/Power.plot.R | 112 +- TestGardener-3.0.0/TestGardener/R/Sensitivity.plot.R | 98 +- TestGardener-3.0.0/TestGardener/R/TG_density.fd.R | 3 TestGardener-3.0.0/TestGardener/R/Wbinsmth.R | 188 ++++ TestGardener-3.0.0/TestGardener/R/Wbinsmth.plot.R | 323 ++++---- TestGardener-3.0.0/TestGardener/R/density_plot.R |only TestGardener-3.0.0/TestGardener/R/make.dataList.R | 402 +++++++--- TestGardener-3.0.0/TestGardener/R/mu.plot.R | 2 TestGardener-3.0.0/TestGardener/R/scoreDensity.R | 29 TestGardener-3.0.0/TestGardener/R/testscore.R | 22 TestGardener-3.0.0/TestGardener/R/theta.distn.R | 47 - TestGardener-3.0.0/TestGardener/R/theta2arclen.R | 237 +++++ TestGardener-3.0.0/TestGardener/build/vignette.rds |binary TestGardener-3.0.0/TestGardener/data/Quantshort_U.rda |only TestGardener-3.0.0/TestGardener/data/Quantshort_dataList.rda |only TestGardener-3.0.0/TestGardener/data/Quantshort_infoList.rda |only TestGardener-3.0.0/TestGardener/data/Quantshort_key.rda |only TestGardener-3.0.0/TestGardener/data/Quantshort_parList.rda |only TestGardener-3.0.0/TestGardener/data/SDS_dataList.rda |binary TestGardener-3.0.0/TestGardener/data/SDS_infoList.rda |only TestGardener-3.0.0/TestGardener/data/SDS_parList.rda |binary TestGardener-3.0.0/TestGardener/demo/Quantshort.R | 166 +++- TestGardener-3.0.0/TestGardener/demo/SDS.R | 149 +++ TestGardener-3.0.0/TestGardener/inst/NEWS.Rd |only TestGardener-3.0.0/TestGardener/inst/doc/Quantshort.R |only TestGardener-3.0.0/TestGardener/inst/doc/Quantshort.Rmd |only TestGardener-3.0.0/TestGardener/inst/doc/Quantshort.html |only TestGardener-3.0.0/TestGardener/inst/doc/SDS.R |only TestGardener-3.0.0/TestGardener/inst/doc/SDS.Rmd |only TestGardener-3.0.0/TestGardener/inst/doc/SDS.html |only TestGardener-3.0.0/TestGardener/man/Analyze.Rd | 4 TestGardener-3.0.0/TestGardener/man/ArcLength.plot.Rd | 44 - TestGardener-3.0.0/TestGardener/man/ConditionalSimulation.Rd | 10 TestGardener-3.0.0/TestGardener/man/DHfun.Rd | 19 TestGardener-3.0.0/TestGardener/man/Entropy.plot.Rd | 44 - TestGardener-3.0.0/TestGardener/man/Hfun.Rd | 16 TestGardener-3.0.0/TestGardener/man/Hfuns.plot.Rd | 26 TestGardener-3.0.0/TestGardener/man/ICC.fit.Rd |only TestGardener-3.0.0/TestGardener/man/ICC.plot.Rd |only TestGardener-3.0.0/TestGardener/man/Power.plot.Rd | 58 - TestGardener-3.0.0/TestGardener/man/Quantshort_U.Rd |only TestGardener-3.0.0/TestGardener/man/Quantshort_dataList.Rd |only TestGardener-3.0.0/TestGardener/man/Quantshort_infoList.Rd |only TestGardener-3.0.0/TestGardener/man/Quantshort_key.Rd |only TestGardener-3.0.0/TestGardener/man/Quantshort_parList.Rd |only TestGardener-3.0.0/TestGardener/man/SDS_U.Rd | 2 TestGardener-3.0.0/TestGardener/man/SDS_dataList.Rd | 56 - TestGardener-3.0.0/TestGardener/man/SDS_infoList.Rd |only TestGardener-3.0.0/TestGardener/man/SDS_parList.Rd | 42 - TestGardener-3.0.0/TestGardener/man/Sensitivity.plot.Rd | 71 - TestGardener-3.0.0/TestGardener/man/Usimulate.Rd | 21 TestGardener-3.0.0/TestGardener/man/Wbinsmth.Rd | 109 +- TestGardener-3.0.0/TestGardener/man/Wpca.plot.Rd | 16 TestGardener-3.0.0/TestGardener/man/density_plot.Rd |only TestGardener-3.0.0/TestGardener/man/make.dataList.Rd | 83 +- TestGardener-3.0.0/TestGardener/man/mu.plot.Rd | 8 TestGardener-3.0.0/TestGardener/man/scoreDensity.Rd | 43 - TestGardener-3.0.0/TestGardener/man/scorePerformance.Rd | 55 - TestGardener-3.0.0/TestGardener/man/testscore.Rd | 31 TestGardener-3.0.0/TestGardener/man/theta.distn.Rd | 66 - TestGardener-3.0.0/TestGardener/man/theta2arclen.Rd | 75 + TestGardener-3.0.0/TestGardener/man/thetafun.Rd | 54 - TestGardener-3.0.0/TestGardener/vignettes/Quantshort.Rmd |only TestGardener-3.0.0/TestGardener/vignettes/SDS.Rmd |only TestGardener-3.0.0/TestGardener/vignettes/U_5000.txt |only TestGardener-3.0.0/TestGardener/vignettes/key_5000.txt |only 100 files changed, 2033 insertions(+), 1109 deletions(-)
Title: Functions to Work with NCBI Accessions and Taxonomy
Description: Functions for assigning taxonomy to NCBI accession numbers and taxon IDs based on NCBI's accession2taxid and taxdump files. This package allows the user to download NCBI data dumps and create a local database for fast and local taxonomic assignment.
Author: Scott Sherrill-Mix [aut, cre]
Maintainer: Scott Sherrill-Mix <shescott@upenn.edu>
Diff between taxonomizr versions 0.9.2 dated 2022-06-23 and 0.9.3 dated 2022-06-26
DESCRIPTION | 8 ++++---- MD5 | 12 ++++++------ README.md | 2 +- inst/doc/usage.Rmd | 3 +++ inst/doc/usage.html | 6 ++++++ tests/testthat/test_taxa.R | 14 +++++++------- vignettes/usage.Rmd | 3 +++ 7 files changed, 30 insertions(+), 18 deletions(-)
Title: Tools for Inference in the Presence of a Monotone Likelihood
Description: Proportional hazards estimation in the presence of a partially monotone likelihood has difficulties, in that finite estimators do not exist. These difficulties are related to those arising from logistic and multinomial regression. References for methods are given in the separate function documents. Supported by grant NSF DMS 1712839.
Author: John E. Kolassa and Juan Zhang
Maintainer: John E. Kolassa <kolassa@stat.rutgers.edu>
Diff between PHInfiniteEstimates versions 2.2 dated 2022-05-10 and 2.5 dated 2022-06-26
DESCRIPTION | 10 +++++----- MD5 | 24 ++++++++++++------------ NAMESPACE | 1 - R/bestbeta.R | 15 +++++++++++---- R/convertbaselineltolr.R | 6 ++++-- R/convertstoml.R | 3 ++- R/newllk.R | 6 ++++-- R/pllk.R | 20 +++++++++++--------- build/partial.rdb |binary man/bestbeta.Rd | 9 ++++++++- man/convertbaselineltolr.Rd | 6 ++++-- man/convertstoml.Rd | 2 ++ man/newllk.Rd | 5 ++++- 13 files changed, 67 insertions(+), 40 deletions(-)
More information about PHInfiniteEstimates at CRAN
Permanent link
Title: Matching Methods for Causal Inference with Time-Series
Cross-Sectional Data
Description: Implements a set of methodological tools
that enable researchers to apply matching methods to
time-series cross-sectional data. Imai, Kim, and Wang
(2021) <http://web.mit.edu/insong/www/pdf/tscs.pdf>
proposes a nonparametric generalization of the
difference-in-differences estimator, which does not rely
on the linearity assumption as often done in
practice. Researchers first select a method of matching
each treated observation for a given unit in a
particular time period with control observations from
other units in the same time period that have a similar
treatment and covariate history. These methods include
standard matching methods based on propensity score and
Mahalanobis distance, as well as weighting methods. Once
matching is done, both short-term and long-term average
treatment effects for the treated can be estimated with
standard errors. The package also offers a visualization
technique that allows researchers to assess the quality
of matches by examining the resulting covariate balance.
Author: In Song Kim [aut, cre],
Adam Rauh [aut],
Erik Wang [aut],
Kosuke Imai [aut]
Maintainer: In Song Kim <insong@mit.edu>
Diff between PanelMatch versions 2.0.0 dated 2021-09-02 and 2.0.1 dated 2022-06-26
PanelMatch-2.0.0/PanelMatch/inst/doc/using_panelmatch.html |only PanelMatch-2.0.0/PanelMatch/man/getSetTreatmentEffects.Rd |only PanelMatch-2.0.0/PanelMatch/man/placeboTest.Rd |only PanelMatch-2.0.1/PanelMatch/DESCRIPTION | 10 PanelMatch-2.0.1/PanelMatch/MD5 | 63 PanelMatch-2.0.1/PanelMatch/NAMESPACE | 4 PanelMatch-2.0.1/PanelMatch/R/DisplayTreatment.R | 556 -- PanelMatch-2.0.1/PanelMatch/R/PE_helpers.R | 685 --- PanelMatch-2.0.1/PanelMatch/R/PE_lower_level.R |only PanelMatch-2.0.1/PanelMatch/R/PanelEstimate.R | 80 PanelMatch-2.0.1/PanelMatch/R/PanelMatch.R | 76 PanelMatch-2.0.1/PanelMatch/R/RcppExports.R | 12 PanelMatch-2.0.1/PanelMatch/R/matched_set_R.r | 81 PanelMatch-2.0.1/PanelMatch/R/matched_set_obj.R | 2 PanelMatch-2.0.1/PanelMatch/R/network_and_caliper.R | 4 PanelMatch-2.0.1/PanelMatch/R/pm_helpers_r.R | 104 PanelMatch-2.0.1/PanelMatch/R/utilities.R | 99 PanelMatch-2.0.1/PanelMatch/build/vignette.rds |binary PanelMatch-2.0.1/PanelMatch/inst/doc/matched_set_objects.html | 2059 ++++++++-- PanelMatch-2.0.1/PanelMatch/inst/doc/using_panelmatch.R | 9 PanelMatch-2.0.1/PanelMatch/inst/doc/using_panelmatch.Rmd | 13 PanelMatch-2.0.1/PanelMatch/inst/doc/using_panelmatch.pdf |only PanelMatch-2.0.1/PanelMatch/man/DisplayTreatment.Rd | 18 PanelMatch-2.0.1/PanelMatch/man/PanelEstimate.Rd | 5 PanelMatch-2.0.1/PanelMatch/man/PanelMatch.Rd | 6 PanelMatch-2.0.1/PanelMatch/man/balance_scatter.Rd | 11 PanelMatch-2.0.1/PanelMatch/man/findBinaryTreated.Rd | 9 PanelMatch-2.0.1/PanelMatch/man/get.matchedsets.Rd | 4 PanelMatch-2.0.1/PanelMatch/man/get_set_treatment_effects.Rd |only PanelMatch-2.0.1/PanelMatch/man/placebo_test.Rd |only PanelMatch-2.0.1/PanelMatch/src/RcppExports.cpp | 40 PanelMatch-2.0.1/PanelMatch/src/init.c | 8 PanelMatch-2.0.1/PanelMatch/src/matched_set_helpers.cpp | 109 PanelMatch-2.0.1/PanelMatch/src/pm_helpers.cpp | 22 PanelMatch-2.0.1/PanelMatch/tests/testthat/test-PanelMatch.R | 96 PanelMatch-2.0.1/PanelMatch/vignettes/using_panelmatch.Rmd | 13 36 files changed, 2603 insertions(+), 1595 deletions(-)
Title: Statistical Methods for the Item Count Technique and List
Experiment
Description: Allows researchers to conduct multivariate
statistical analyses of survey data with list experiments. This
survey methodology is also known as the item count technique or
the unmatched count technique and is an alternative to the commonly
used randomized response method. The package implements the methods
developed by Imai (2011) <doi:10.1198/jasa.2011.ap10415>,
Blair and Imai (2012) <doi:10.1093/pan/mpr048>,
Blair, Imai, and Lyall (2013) <doi:10.1111/ajps.12086>,
Imai, Park, and Greene (2014) <doi:10.1093/pan/mpu017>,
Aronow, Coppock, Crawford, and Green (2015) <doi:10.1093/jssam/smu023>,
Chou, Imai, and Rosenfeld (2017) <doi:10.1177/0049124117729711>, and
Blair, Chou, and Imai (2018) <https://imai.fas.harvard.edu/research/files/listerror.pdf>.
This includes a Bayesian MCMC implementation of regression for the
standard and multiple sensitive item list experiment designs and a
random effects setup, a Bayesian MCMC hierarchical regression model
with up to three hierarchical groups, the combined list experiment
and endorsement experiment regression model, a joint model of the
list experiment that enables the analysis of the list experiment as
a predictor in outcome regression models, a method for combining
list experiments with direct questions, and methods for diagnosing and
adjusting for response error. In addition, the package implements the
statistical test that is designed to detect certain failures of list
experiments, and a placebo test for the list experiment using data from
direct questions.
Author: Graeme Blair [aut, cre],
Winston Chou [aut],
Kosuke Imai [aut],
Bethany Park [ctb],
Alexander Coppock [ctb]
Maintainer: Graeme Blair <graeme.blair@gmail.com>
Diff between list versions 9.2.2 dated 2022-05-25 and 9.2.4 dated 2022-06-26
ChangeLog | 6 DESCRIPTION | 6 MD5 | 10 - R/ictreg.R | 4 inst/doc/combined-list.html | 317 +++++++++++++++++++++++++++++++++++++++---- tests/testthat/test-ictreg.R | 3 6 files changed, 308 insertions(+), 38 deletions(-)
Title: Spatially Explicit Capture-Recapture by Inverse Prediction
Description: Estimates the density of a spatially distributed animal population sampled with an array of passive detectors, such as traps. Models incorporating distance-dependent detection are fitted by simulation and inverse prediction as proposed by Efford (2004) <doi:10.1111/j.0030-1299.2004.13043.x>.
Author: Murray Efford [aut, cre]
Maintainer: Murray Efford <murray.efford@otago.ac.nz>
Diff between ipsecr versions 1.1.1 dated 2022-06-20 and 1.1.2 dated 2022-06-26
DESCRIPTION | 8 - MD5 | 35 +++--- NEWS | 64 ++--------- R/simCH.R | 6 - R/utility.R | 4 inst/CITATION | 2 inst/doc/ipsecr-vignette.R | 61 ++++++---- inst/doc/ipsecr-vignette.Rmd | 222 +++++++++++++++++++++++----------------- inst/doc/ipsecr-vignette.pdf |binary inst/example/fittedmodels.RData |binary inst/example/ip.Fr.RData |only man/ipsecr-package.Rd | 8 - man/ipsecr.fit.Rd | 13 -- src/CH.cpp | 129 +++++++++++------------ src/autils.cpp | 34 ------ src/ipsecr.h | 11 - tests/testthat/test-ipsecr.R | 6 - tests/testthat/test-nontarget.R | 4 vignettes/ipsecr-vignette.Rmd | 222 +++++++++++++++++++++++----------------- 19 files changed, 409 insertions(+), 420 deletions(-)
Title: Intrinsic Peak Analysis (IPA) for HRMS Data
Description: A sophisticated pipeline for processing LC/HRMS data to extract signals of organic compounds. The package performs isotope pairing, peak detection, alignment, RT correction, gap filling, peak annotation and visualization of extracted ion chromatograms and total ion chromatograms.
Author: Sadjad Fakouri-Baygi [cre, aut]
,
Dinesh Barupal [aut]
Maintainer: Sadjad Fakouri-Baygi <sadjad.fakouri-baygi@mssm.edu>
Diff between IDSL.IPA versions 1.7 dated 2022-06-13 and 1.8 dated 2022-06-26
IDSL.IPA-1.7/IDSL.IPA/R/carbon_isotopes_explorer.R |only IDSL.IPA-1.7/IDSL.IPA/man/carbon_isotopes_explorer.Rd |only IDSL.IPA-1.8/IDSL.IPA/DESCRIPTION | 8 +- IDSL.IPA-1.8/IDSL.IPA/MD5 | 32 +++++----- IDSL.IPA-1.8/IDSL.IPA/R/IPA_GapFiller.R | 11 ++- IDSL.IPA-1.8/IDSL.IPA/R/IPA_PeakAnalyzer.R | 14 +++- IDSL.IPA-1.8/IDSL.IPA/R/IPA_PeaklistAnnotation.R | 23 ++++--- IDSL.IPA-1.8/IDSL.IPA/R/IPA_TargetedAnalysis.R | 50 +++++++++-------- IDSL.IPA-1.8/IDSL.IPA/R/IPA_isotope_pairing.R |only IDSL.IPA-1.8/IDSL.IPA/R/IPA_xlsxAnalyzer.R | 17 +++-- IDSL.IPA-1.8/IDSL.IPA/R/xlsxAnalyzer_EIC.R | 15 ++--- IDSL.IPA-1.8/IDSL.IPA/build/partial.rdb |binary IDSL.IPA-1.8/IDSL.IPA/inst/extdata/IPA_parameters.xlsx |binary IDSL.IPA-1.8/IDSL.IPA/man/EIC_plotter.Rd | 4 - IDSL.IPA-1.8/IDSL.IPA/man/IPA_isotope_pairing.Rd |only IDSL.IPA-1.8/IDSL.IPA/man/chromatography_analysis.Rd | 4 - IDSL.IPA-1.8/IDSL.IPA/man/mzRTindexer.Rd | 7 +- IDSL.IPA-1.8/IDSL.IPA/man/primary_peak_analyzer.Rd | 4 - IDSL.IPA-1.8/IDSL.IPA/man/recursive_mass_correction.Rd | 4 - 19 files changed, 106 insertions(+), 87 deletions(-)
Title: High Performance Cluster Models Based on Kiefer-Wolfowitz
Recursion
Description: Probabilistic models describing the behavior
of workload and queue on a High Performance Cluster and computing GRID
under FIFO service discipline basing on modified Kiefer-Wolfowitz
recursion. Also sample data for inter-arrival times, service times,
number of cores per task and waiting times of HPC of Karelian
Research Centre are included, measurements took place from 06/03/2009 to 02/30/2011.
Functions provided to import/export workload traces in Standard Workload Format (swf).
Stability condition of the model may be verified either exactly, or approximately.
Stability analysis: see Rumyantsev and Morozov (2017) <doi:10.1007/s10479-015-1917-2>,
workload recursion: see Rumyantsev (2014) <doi:10.1109/PDCAT.2014.36>.
Author: Alexander Rumyantsev [aut, cre]
Maintainer: Alexander Rumyantsev <ar0@sampo.ru>
Diff between hpcwld versions 0.6-4 dated 2022-04-22 and 0.6-5 dated 2022-06-26
DESCRIPTION | 14 ++++++++------ MD5 | 10 +++++----- R/Workload.R | 2 +- data/HPC_KRC.rda |binary data/HPC_KRC2.rda |binary data/X.rda |binary 6 files changed, 14 insertions(+), 12 deletions(-)
Title: Statistical Analysis in Epidemiology
Description: Functions for demographic and epidemiological analysis in
the Lexis diagram, i.e. register and cohort follow-up data. In
particular representation, manipulation, rate estimation and
simulation for multistate data - the Lexis suite of functions, which
includes interfaces to 'mstate', 'etm' and 'cmprsk' packages.
Contains functions for Age-Period-Cohort and Lee-Carter modeling and
a function for interval censored data and some useful functions for
tabulation and plotting, as well as a number of epidemiological data
sets.
Author: Bendix Carstensen [aut, cre],
Martyn Plummer [aut],
Esa Laara [ctb],
Michael Hills [ctb]
Maintainer: Bendix Carstensen <b@bxc.dk>
Diff between Epi versions 2.46 dated 2022-04-13 and 2.47 dated 2022-06-26
Epi-2.46/Epi/vignettes/2Bappended2adLexisrnw.txt |only Epi-2.46/Epi/vignettes/addLexis.rwl |only Epi-2.46/Epi/vignettes/crisk.rwl |only Epi-2.46/Epi/vignettes/flup.rwl |only Epi-2.46/Epi/vignettes/simLexis.rwl |only Epi-2.46/Epi/vignettes/yll.rwl |only Epi-2.47/Epi/CHANGES | 25 +++++ Epi-2.47/Epi/DESCRIPTION | 8 - Epi-2.47/Epi/MD5 | 51 +++++------ Epi-2.47/Epi/NAMESPACE | 1 Epi-2.47/Epi/R/Lexis2msm.R |only Epi-2.47/Epi/R/ci.lin.R | 26 +++-- Epi-2.47/Epi/R/cutLexis.R | 15 +-- Epi-2.47/Epi/R/mod.Lexis.R | 86 ++++++++----------- Epi-2.47/Epi/inst/doc/addLexis.pdf |binary Epi-2.47/Epi/inst/doc/crisk.pdf |binary Epi-2.47/Epi/inst/doc/flup.R | 65 +++++++------- Epi-2.47/Epi/inst/doc/flup.pdf |binary Epi-2.47/Epi/inst/doc/simLexis.pdf |binary Epi-2.47/Epi/inst/doc/yll.pdf |binary Epi-2.47/Epi/man/Lexis2msm.Rd |only Epi-2.47/Epi/man/ROC.Rd | 2 Epi-2.47/Epi/man/cal.yr.Rd | 2 Epi-2.47/Epi/man/ci.lin.Rd | 20 ++-- Epi-2.47/Epi/man/start.Lexis.Rd | 22 ++-- Epi-2.47/Epi/vignettes/2Bappended2addLexisrnw.txt |only Epi-2.47/Epi/vignettes/addLexis.tex | 10 +- Epi-2.47/Epi/vignettes/crisk.tex | 98 +++++++++++----------- Epi-2.47/Epi/vignettes/flup.tex | 76 ++++++++++------- Epi-2.47/Epi/vignettes/simLexis.tex | 23 +++-- Epi-2.47/Epi/vignettes/yll.tex | 2 31 files changed, 291 insertions(+), 241 deletions(-)
Title: The Gaussian Covariate Method for Variable Selection
Description: Given the standard linear model the traditional way of deciding whether to include the jth covariate is to apply the F-test to decide whether the corresponding beta coefficient is zero. The Gaussian covariate method is completely different. The question as to whether the beta coefficient is or is not zero is replaced by the question as to whether the covariate is better or worse than i.i.d. Gaussian noise. The P-value for the covariate is the probability that Gaussian noise is better. Surprisingly this can be given exactly and it is the same a the P-value for the classical model based on the F-distribution. The Gaussian covariate P-value is model free, it is the same for any data set. Using the idea it is possible to do covariate selection for a small number of covariates 25 by considering all subsets. Post selection inference causes no problems as the P-values hold whatever the data. The idea extends to stepwise regression again with exact probabilities. In the simplest version the only parameter is a specified cut-off P-value which can be interpreted as the probability of a false positive being included in the final selection. For more information see the web site below and the accompanying papers: L. Davies and L. Duembgen, "Covariate Selection Based on a Model-free Approach to Linear Regression with Exact Probabilities", 2022, <arxiv:2202.01553>. L. Davies, "Linear Regression, Covariate Selection and the Failure of Modelling", 2022, <arXiv:2112.08738>.
Author: Laurie Davies [aut, cre]
Maintainer: Laurie Davies <laurie.davies@uni-due.de>
Diff between gausscov versions 0.1.7 dated 2022-04-26 and 0.1.8 dated 2022-06-26
DESCRIPTION | 8 +++--- MD5 | 14 ++++++----- R/fcluster.R |only R/fgeninter.R | 10 +++---- R/fgr1st.R | 13 +++++++--- R/fpval.R | 2 - man/fcluster.Rd |only man/fgeninter.Rd | 4 +-- src/gaucov.f | 70 +++++++++++++++++++++++++++---------------------------- 9 files changed, 64 insertions(+), 57 deletions(-)
Title: Searching for Optimal MDS Procedure for Metric and
Interval-Valued Data
Description: Selecting the optimal multidimensional scaling (MDS) procedure for metric data via metric MDS (ratio, interval, mspline) and nonmetric MDS (ordinal). Selecting the optimal multidimensional scaling (MDS) procedure for interval-valued data via metric MDS (ratio, interval, mspline).Selecting the optimal multidimensional scaling procedure for interval-valued data by varying all combinations of normalization and optimization methods.Selecting the optimal MDS procedure for statistical data referring to the evaluation of tourist attractiveness of Lower Silesian counties.
(Borg, I., Groenen, P.J.F., Mair, P. (2013) <doi:10.1007/978-3-642-31848-1>,
Walesiak, M. (2016) <doi:10.15611/ekt.2016.2.01>,
Walesiak, M. (2017) <doi:10.15611/ekt.2017.3.01>).
Author: Marek Walesiak [aut] ,
Andrzej Dudek [aut, cre]
Maintainer: Andrzej Dudek <andrzej.dudek@ue.wroc.pl>
Diff between mdsOpt versions 0.6-3 dated 2022-06-15 and 0.7-1 dated 2022-06-26
mdsOpt-0.6-3/mdsOpt/R/findOptimalIscalInterval.r |only mdsOpt-0.6-3/mdsOpt/R/ispb.r |only mdsOpt-0.6-3/mdsOpt/R/optIscalInterval.r |only mdsOpt-0.6-3/mdsOpt/man/findOptimalIscalInterval.rd |only mdsOpt-0.6-3/mdsOpt/man/ispb.rd |only mdsOpt-0.6-3/mdsOpt/man/optIscalInterval.rd |only mdsOpt-0.6-3/mdsOpt/src |only mdsOpt-0.7-1/mdsOpt/DESCRIPTION | 11 +++---- mdsOpt-0.7-1/mdsOpt/MD5 | 29 ++++++-------------- mdsOpt-0.7-1/mdsOpt/NAMESPACE | 2 - mdsOpt-0.7-1/mdsOpt/inst/doc/mdsOpt.pdf |binary mdsOpt-0.7-1/mdsOpt/man/data_lower_silesian.rd | 6 ++-- mdsOpt-0.7-1/mdsOpt/man/drawIsoquants.rd | 4 +- mdsOpt-0.7-1/mdsOpt/man/findOptimalSmacofSym.rd | 8 ++++- mdsOpt-0.7-1/mdsOpt/man/optSmacofSymInterval.rd | 8 ++++- mdsOpt-0.7-1/mdsOpt/man/optSmacofSym_mMDS.rd | 8 ++++- mdsOpt-0.7-1/mdsOpt/man/optSmacofSym_nMDS.rd | 8 ++++- mdsOpt-0.7-1/mdsOpt/man/rotation2dAnimation.rd | 4 +- 18 files changed, 47 insertions(+), 41 deletions(-)
Title: Flux Rate Calculation from Dynamic Closed Chamber Measurements
Description: Functions for the calculation of greenhouse gas flux rates
from closed chamber concentration measurements. The package follows
a modular concept: Fluxes can be calculated in just two simple steps
or in several steps if more control in details is wanted. Additionally
plot and preparation functions as well as functions for modelling
gpp and reco are provided.
Author: Gerald Jurasinski, Franziska Koebsch, Anke Guenther, Sascha Beetz
Maintainer: Gerald Jurasinski <gerald.jurasinski@uni-rostock.de>
Diff between flux versions 0.3-0 dated 2014-04-25 and 0.3-0.1 dated 2022-06-26
DESCRIPTION | 9 +++++---- MD5 | 14 +++++++------- NAMESPACE | 8 ++++++-- data/amc.rda |binary data/amd.rda |binary data/tt.flux.rda |binary data/tt.nee.rda |binary data/tt.pre.rda |binary 8 files changed, 18 insertions(+), 13 deletions(-)
Title: Cut Numeric Values into Evenly Distributed Groups
Description: Implementation of algorithms for cutting numerical values
exhibiting a potentially highly skewed distribution into evenly distributed
groups (bins). This functionality can be applied for binning discrete
values, such as counts, as well as for discretization of continuous values,
for example, during generation of features used in machine learning
algorithms.
Author: Sergei Izrailev
Maintainer: Sergei Izrailev <sizrailev@jabiruventures.com>
Diff between binr versions 1.1 dated 2015-03-10 and 1.1.1 dated 2022-06-26
DESCRIPTION | 9 ++++----- MD5 | 4 ++-- NAMESPACE | 4 ++-- 3 files changed, 8 insertions(+), 9 deletions(-)