Title: Bayesian Spatial Blind Source Separation
Description: Gibbs sampling for Bayesian spatial blind source separation (BSP-BSS). BSP-BSS is designed for spatially dependent signals in high dimensional and large-scale data, such as neuroimaging. The method assumes the expectation of the observed images as a linear mixture of multiple sparse and piece-wise smooth latent source signals, and constructs a Bayesian nonparametric prior by thresholding Gaussian processes. Details can be found in our paper: Wu et al. (2022+) "Bayesian Spatial Blind Source Separation via the Thresholded Gaussian Process" <doi:10.1080/01621459.2022.2123336>.
Author: Ben Wu [aut, cre],
Ying Guo [aut],
Jian Kang [aut]
Maintainer: Ben Wu <wuben@ruc.edu.cn>
Diff between BSPBSS versions 1.0.2 dated 2022-09-02 and 1.0.3 dated 2022-09-17
DESCRIPTION | 8 +++---- MD5 | 10 ++++----- inst/doc/BSPBSS-vignette.R | 2 - inst/doc/BSPBSS-vignette.Rmd | 2 - inst/doc/BSPBSS-vignette.html | 43 ++++++++++++++++++++---------------------- vignettes/BSPBSS-vignette.Rmd | 2 - 6 files changed, 33 insertions(+), 34 deletions(-)
Title: Understand and Describe Bayesian Models and Posterior
Distributions
Description: Provides utilities to describe posterior
distributions and Bayesian models. It includes point-estimates such as
Maximum A Posteriori (MAP), measures of dispersion (Highest Density
Interval - HDI; Kruschke, 2015 <doi:10.1016/C2012-0-00477-2>) and
indices used for null-hypothesis testing (such as ROPE percentage, pd
and Bayes factors).
Author: Dominique Makowski [aut, cre] ,
Daniel Luedecke [aut] ,
Mattan S. Ben-Shachar [aut] ,
Indrajeet Patil [aut] ,
Michael D. Wilson [aut] ,
Brenton M. Wiernik [aut] ,
Paul-Christian Buerkner [rev],
Tristan Mahr [rev] ,
Henrik Singmann [ctb] ,
Quentin F. Gr [...truncated...]
Maintainer: Dominique Makowski <dom.makowski@gmail.com>
Diff between bayestestR versions 0.12.1 dated 2022-05-02 and 0.13.0 dated 2022-09-17
bayestestR-0.12.1/bayestestR/R/backports.R |only bayestestR-0.12.1/bayestestR/R/contr.orthonorm.R |only bayestestR-0.12.1/bayestestR/man/contr.orthonorm.Rd |only bayestestR-0.12.1/bayestestR/tests/spelling.R |only bayestestR-0.13.0/bayestestR/DESCRIPTION | 26 - bayestestR-0.13.0/bayestestR/MD5 | 199 +++++----- bayestestR-0.13.0/bayestestR/NAMESPACE | 27 + bayestestR-0.13.0/bayestestR/NEWS.md | 22 + bayestestR-0.13.0/bayestestR/R/area_under_curve.R | 3 bayestestR-0.13.0/bayestestR/R/bayesfactor_models.R | 27 - bayestestR-0.13.0/bayestestR/R/bayesfactor_parameters.R | 6 bayestestR-0.13.0/bayestestR/R/bayesfactor_restricted.R | 9 bayestestR-0.13.0/bayestestR/R/bci.R | 4 bayestestR-0.13.0/bayestestR/R/check_prior.R | 6 bayestestR-0.13.0/bayestestR/R/ci.R | 5 bayestestR-0.13.0/bayestestR/R/contr.equalprior.R |only bayestestR-0.13.0/bayestestR/R/cwi.R | 1 bayestestR-0.13.0/bayestestR/R/describe_posterior.R | 141 ++++--- bayestestR-0.13.0/bayestestR/R/describe_prior.R | 3 bayestestR-0.13.0/bayestestR/R/diagnostic_posterior.R | 11 bayestestR-0.13.0/bayestestR/R/distribution.R | 1 bayestestR-0.13.0/bayestestR/R/effective_sample.R | 37 + bayestestR-0.13.0/bayestestR/R/equivalence_test.R | 5 bayestestR-0.13.0/bayestestR/R/estimate_density.R | 82 +++- bayestestR-0.13.0/bayestestR/R/eti.R | 5 bayestestR-0.13.0/bayestestR/R/format.R | 1 bayestestR-0.13.0/bayestestR/R/hdi.R | 9 bayestestR-0.13.0/bayestestR/R/map_estimate.R | 5 bayestestR-0.13.0/bayestestR/R/mediation.R | 1 bayestestR-0.13.0/bayestestR/R/overlap.R | 1 bayestestR-0.13.0/bayestestR/R/p_direction.R | 27 + bayestestR-0.13.0/bayestestR/R/p_map.R | 3 bayestestR-0.13.0/bayestestR/R/p_rope.R | 3 bayestestR-0.13.0/bayestestR/R/p_significance.R | 10 bayestestR-0.13.0/bayestestR/R/p_to_bf.R |only bayestestR-0.13.0/bayestestR/R/point_estimate.R | 5 bayestestR-0.13.0/bayestestR/R/print.R | 6 bayestestR-0.13.0/bayestestR/R/print.equivalence_test.R | 2 bayestestR-0.13.0/bayestestR/R/print.rope.R | 4 bayestestR-0.13.0/bayestestR/R/print_html.R | 2 bayestestR-0.13.0/bayestestR/R/print_md.R | 2 bayestestR-0.13.0/bayestestR/R/reshape_iterations.R | 20 - bayestestR-0.13.0/bayestestR/R/rope.R | 15 bayestestR-0.13.0/bayestestR/R/rope_range.R | 1 bayestestR-0.13.0/bayestestR/R/sexit.R | 4 bayestestR-0.13.0/bayestestR/R/si.R | 7 bayestestR-0.13.0/bayestestR/R/simulate_data.R | 21 - bayestestR-0.13.0/bayestestR/R/simulate_priors.R | 2 bayestestR-0.13.0/bayestestR/R/simulate_simpson.R | 2 bayestestR-0.13.0/bayestestR/R/spi.R | 58 +- bayestestR-0.13.0/bayestestR/R/unupdate.R | 4 bayestestR-0.13.0/bayestestR/R/utils.R | 12 bayestestR-0.13.0/bayestestR/R/utils_bayesfactor.R | 15 bayestestR-0.13.0/bayestestR/R/utils_check_collinearity.R | 1 bayestestR-0.13.0/bayestestR/R/utils_hdi_ci.R | 4 bayestestR-0.13.0/bayestestR/R/utils_posterior.R | 4 bayestestR-0.13.0/bayestestR/R/utils_print_data_frame.R | 2 bayestestR-0.13.0/bayestestR/R/weighted_posteriors.R | 2 bayestestR-0.13.0/bayestestR/README.md | 164 ++++---- bayestestR-0.13.0/bayestestR/build/partial.rdb |binary bayestestR-0.13.0/bayestestR/build/vignette.rds |binary bayestestR-0.13.0/bayestestR/inst/doc/overview_of_vignettes.html | 1 bayestestR-0.13.0/bayestestR/man/area_under_curve.Rd | 78 +-- bayestestR-0.13.0/bayestestR/man/as.numeric.p_direction.Rd | 52 +- bayestestR-0.13.0/bayestestR/man/bayesfactor_parameters.Rd | 4 bayestestR-0.13.0/bayestestR/man/bayesfactor_restricted.Rd | 2 bayestestR-0.13.0/bayestestR/man/contr.equalprior.Rd |only bayestestR-0.13.0/bayestestR/man/cwi.Rd | 1 bayestestR-0.13.0/bayestestR/man/density_at.Rd | 57 +- bayestestR-0.13.0/bayestestR/man/describe_posterior.Rd | 4 bayestestR-0.13.0/bayestestR/man/diagnostic_posterior.Rd | 2 bayestestR-0.13.0/bayestestR/man/distribution.Rd | 15 bayestestR-0.13.0/bayestestR/man/estimate_density.Rd | 2 bayestestR-0.13.0/bayestestR/man/figures/unnamed-chunk-10-1.png |only bayestestR-0.13.0/bayestestR/man/figures/unnamed-chunk-12-1.png |binary bayestestR-0.13.0/bayestestR/man/figures/unnamed-chunk-14-1.png |binary bayestestR-0.13.0/bayestestR/man/figures/unnamed-chunk-16-1.png |binary bayestestR-0.13.0/bayestestR/man/figures/unnamed-chunk-7-1.png |binary bayestestR-0.13.0/bayestestR/man/figures/unnamed-chunk-8-1.png |binary bayestestR-0.13.0/bayestestR/man/p_to_bf.Rd |only bayestestR-0.13.0/bayestestR/man/point_estimate.Rd | 2 bayestestR-0.13.0/bayestestR/man/reshape_iterations.Rd | 13 bayestestR-0.13.0/bayestestR/man/rope_range.Rd | 6 bayestestR-0.13.0/bayestestR/man/sensitivity_to_prior.Rd | 90 ++-- bayestestR-0.13.0/bayestestR/man/sexit.Rd | 2 bayestestR-0.13.0/bayestestR/man/si.Rd | 16 bayestestR-0.13.0/bayestestR/man/simulate_correlation.Rd | 13 bayestestR-0.13.0/bayestestR/man/weighted_posteriors.Rd | 2 bayestestR-0.13.0/bayestestR/tests/testthat/test-bayesfactor_models.R | 15 bayestestR-0.13.0/bayestestR/tests/testthat/test-bayesfactor_parameters.R | 1 bayestestR-0.13.0/bayestestR/tests/testthat/test-bayesfactor_restricted.R | 3 bayestestR-0.13.0/bayestestR/tests/testthat/test-brms.R | 23 - bayestestR-0.13.0/bayestestR/tests/testthat/test-check_prior.R | 20 - bayestestR-0.13.0/bayestestR/tests/testthat/test-contr.R |only bayestestR-0.13.0/bayestestR/tests/testthat/test-describe_posterior.R | 4 bayestestR-0.13.0/bayestestR/tests/testthat/test-describe_prior.R | 20 - bayestestR-0.13.0/bayestestR/tests/testthat/test-different_models.R | 6 bayestestR-0.13.0/bayestestR/tests/testthat/test-hdi.R | 1 bayestestR-0.13.0/bayestestR/tests/testthat/test-map_estimate.R | 1 bayestestR-0.13.0/bayestestR/tests/testthat/test-p_to_bf.R |only bayestestR-0.13.0/bayestestR/tests/testthat/test-posterior.R | 48 +- bayestestR-0.13.0/bayestestR/tests/testthat/test-rope.R | 9 bayestestR-0.13.0/bayestestR/tests/testthat/test-rstanarm.R | 8 bayestestR-0.13.0/bayestestR/tests/testthat/test-si.R | 11 bayestestR-0.13.0/bayestestR/tests/testthat/test-simulate_data.R | 13 bayestestR-0.13.0/bayestestR/tests/testthat/test-spi.R | 1 106 files changed, 944 insertions(+), 641 deletions(-)
Title: Running Operations for Vectors
Description: Lightweight library for rolling windows operations. Package enables
full control over the window length, window lag and a time indices. With a runner
one can apply any R function on a rolling windows. The package eases work with
equally and unequally spaced time series.
Author: Dawid Kalędkowski [aut, cre]
Maintainer: Dawid Kalędkowski <dawid.kaledkowski@gmail.com>
Diff between runner versions 0.4.1 dated 2021-10-03 and 0.4.2 dated 2022-09-17
runner-0.4.1/runner/man/k_by.Rd |only runner-0.4.1/runner/man/reformat_k.Rd |only runner-0.4.1/runner/man/seq_at.Rd |only runner-0.4.1/runner/man/this_group.Rd |only runner-0.4.2/runner/DESCRIPTION | 8 runner-0.4.2/runner/MD5 | 57 - runner-0.4.2/runner/NEWS.md | 13 runner-0.4.2/runner/R/run.R | 491 ------------- runner-0.4.2/runner/R/run_by.R | 85 -- runner-0.4.2/runner/R/utils.R |only runner-0.4.2/runner/README.md | 5 runner-0.4.2/runner/build/vignette.rds |binary runner-0.4.2/runner/inst/doc/apply_any_r_function.html | 342 ++++++++- runner-0.4.2/runner/inst/doc/built-in_functions.html | 303 +++++++- runner-0.4.2/runner/inst/doc/runner_examples.html | 228 +++++- runner-0.4.2/runner/inst/tinytest/test_check_unresolved.R |only runner-0.4.2/runner/inst/tinytest/test_run_by.R | 181 +--- runner-0.4.2/runner/inst/tinytest/test_runner-data.frame.R |only runner-0.4.2/runner/inst/tinytest/test_runner-parallel.R |only runner-0.4.2/runner/inst/tinytest/test_runner.R | 367 +-------- runner-0.4.2/runner/inst/tinytest/test_timeops.R | 62 - runner-0.4.2/runner/inst/tinytest/test_window_run.R | 22 runner-0.4.2/runner/man/dot-check_unresolved_at.Rd |only runner-0.4.2/runner/man/dot-check_unresolved_difftime.Rd |only runner-0.4.2/runner/man/dot-check_unresolved_index.Rd |only runner-0.4.2/runner/man/dot-is_datetime_valid.Rd |only runner-0.4.2/runner/man/dot-k_by.Rd |only runner-0.4.2/runner/man/dot-reformat_k.Rd |only runner-0.4.2/runner/man/dot-resolve_arg.Rd |only runner-0.4.2/runner/man/dot-seq_at.Rd |only runner-0.4.2/runner/man/dot-this_group.Rd |only runner-0.4.2/runner/man/length_run.Rd | 2 runner-0.4.2/runner/man/minmax_run.Rd | 2 runner-0.4.2/runner/man/runner.Rd | 20 runner-0.4.2/runner/man/streak_run.Rd | 2 runner-0.4.2/runner/man/window_run.Rd | 2 runner-0.4.2/runner/src/lag_run.cpp | 8 runner-0.4.2/runner/src/vector_funs.h | 16 38 files changed, 1070 insertions(+), 1146 deletions(-)
Title: Risk Regression Models and Prediction Scores for Survival
Analysis with Competing Risks
Description: Implementation of the following methods for event history analysis.
Risk regression models for survival endpoints also in the presence of competing
risks are fitted using binomial regression based on a time sequence of binary
event status variables. A formula interface for the Fine-Gray regression model
and an interface for the combination of cause-specific Cox regression models.
A toolbox for assessing and comparing performance of risk predictions (risk
markers and risk prediction models). Prediction performance is measured by the
Brier score and the area under the ROC curve for binary possibly time-dependent
outcome. Inverse probability of censoring weighting and pseudo values are used
to deal with right censored data. Lists of risk markers and lists of risk models
are assessed simultaneously. Cross-validation repeatedly splits the data, trains
the risk prediction models on one part of each split and then summarizes and
compares the performance across splits.
Author: Thomas Alexander Gerds [aut, cre],
Johan Sebastian Ohlendorff [aut],
Paul Blanche [ctb],
Rikke Mortensen [ctb],
Marvin Wright [ctb],
Nikolaj Tollenaar [ctb],
John Muschelli [ctb],
Ulla Brasch Mogensen [ctb],
Brice Ozenne [aut]
Maintainer: Thomas Alexander Gerds <tag@biostat.ku.dk>
Diff between riskRegression versions 2022.03.22 dated 2022-03-23 and 2022.09.13 dated 2022-09-17
riskRegression-2022.03.22/riskRegression/src/getInfluenceFunctionSurvival.cpp |only riskRegression-2022.03.22/riskRegression/tests/test-AUC.R |only riskRegression-2022.03.22/riskRegression/tests/test-BinomialRegression.R |only riskRegression-2022.03.22/riskRegression/tests/test-BrierScore.R |only riskRegression-2022.03.22/riskRegression/tests/test-CauseSpecificCoxRegression.R |only riskRegression-2022.03.22/riskRegression/tests/test-FineGrayRegression.R |only riskRegression-2022.03.22/riskRegression/tests/test-boxplotScore.R |only riskRegression-2022.03.22/riskRegression/tests/test-iidCox.R |only riskRegression-2022.03.22/riskRegression/tests/test-phreg.R |only riskRegression-2022.03.22/riskRegression/tests/test-predictCox.R |only riskRegression-2022.03.22/riskRegression/tests/test-predictCoxPL.R |only riskRegression-2022.03.22/riskRegression/tests/test-predictRisk-TD.R |only riskRegression-2022.03.22/riskRegression/tests/test-predictRisk.R |only riskRegression-2022.03.22/riskRegression/tests/test-score-bootstrap.R |only riskRegression-2022.03.22/riskRegression/tests/test-score.R |only riskRegression-2022.03.22/riskRegression/tests/test-summary-score.R |only riskRegression-2022.03.22/riskRegression/tests/test-wglm.R |only riskRegression-2022.09.13/riskRegression/DESCRIPTION | 15 riskRegression-2022.09.13/riskRegression/MD5 | 143 riskRegression-2022.09.13/riskRegression/NAMESPACE | 10 riskRegression-2022.09.13/riskRegression/R/AUC.competing.risks.R | 99 riskRegression-2022.09.13/riskRegression/R/AUC.survival.R | 47 riskRegression-2022.09.13/riskRegression/R/Brier.competing.risks.R | 70 riskRegression-2022.09.13/riskRegression/R/Brier.survival.R | 67 riskRegression-2022.09.13/riskRegression/R/CSC.R | 22 riskRegression-2022.09.13/riskRegression/R/RcppExports.R | 24 riskRegression-2022.09.13/riskRegression/R/Score.R | 2115 +++------- riskRegression-2022.09.13/riskRegression/R/ate.R | 13 riskRegression-2022.09.13/riskRegression/R/calcSeCSC.R | 6 riskRegression-2022.09.13/riskRegression/R/computePerformance.R | 29 riskRegression-2022.09.13/riskRegression/R/crossvalPerf.R |only riskRegression-2022.09.13/riskRegression/R/getCensoringWeights.R | 91 riskRegression-2022.09.13/riskRegression/R/getCoxInfo.R | 2 riskRegression-2022.09.13/riskRegression/R/getInfluenceCurve.R | 385 + riskRegression-2022.09.13/riskRegression/R/getInfluenceCurverHelper.R |only riskRegression-2022.09.13/riskRegression/R/getPerformanceData.R | 22 riskRegression-2022.09.13/riskRegression/R/getResponse.R | 3 riskRegression-2022.09.13/riskRegression/R/plotAUC.R | 78 riskRegression-2022.09.13/riskRegression/R/plotBrier.R | 85 riskRegression-2022.09.13/riskRegression/R/plotCalibration.R | 4 riskRegression-2022.09.13/riskRegression/R/plotRisk.R | 111 riskRegression-2022.09.13/riskRegression/R/predict.CauseSpecificCox.R | 67 riskRegression-2022.09.13/riskRegression/R/predictCox.R | 5 riskRegression-2022.09.13/riskRegression/R/predictRisk.R | 250 - riskRegression-2022.09.13/riskRegression/R/riskRegression-package.R | 4 riskRegression-2022.09.13/riskRegression/R/sim.synth.R |only riskRegression-2022.09.13/riskRegression/R/synthesize.R |only riskRegression-2022.09.13/riskRegression/man/CSC.Rd | 2 riskRegression-2022.09.13/riskRegression/man/Score.Rd | 9 riskRegression-2022.09.13/riskRegression/man/ate.Rd | 6 riskRegression-2022.09.13/riskRegression/man/plotAUC.Rd | 3 riskRegression-2022.09.13/riskRegression/man/plotBrier.Rd | 2 riskRegression-2022.09.13/riskRegression/man/plotRisk.Rd | 2 riskRegression-2022.09.13/riskRegression/man/predictRisk.Rd | 8 riskRegression-2022.09.13/riskRegression/man/simsynth.Rd |only riskRegression-2022.09.13/riskRegression/man/synthesize.Rd |only riskRegression-2022.09.13/riskRegression/src/AUCijFun.cpp | 2 riskRegression-2022.09.13/riskRegression/src/IC-Nelson-Aalen-cens-time.cpp | 2 riskRegression-2022.09.13/riskRegression/src/Makevars | 3 riskRegression-2022.09.13/riskRegression/src/RcppExports.cpp | 90 riskRegression-2022.09.13/riskRegression/src/arma-wrap.cpp |only riskRegression-2022.09.13/riskRegression/src/arma-wrap.h |only riskRegression-2022.09.13/riskRegression/src/baseHaz.cpp | 2 riskRegression-2022.09.13/riskRegression/src/calcSeCox.cpp | 2 riskRegression-2022.09.13/riskRegression/src/calculateDelongCovarianceMatrix.cpp | 30 riskRegression-2022.09.13/riskRegression/src/colCumSum.cpp | 2 riskRegression-2022.09.13/riskRegression/src/colSumsCrossprod.cpp | 2 riskRegression-2022.09.13/riskRegression/src/confBand.cpp | 2 riskRegression-2022.09.13/riskRegression/src/getInfluenceFunctionAUC.cpp |only riskRegression-2022.09.13/riskRegression/src/getInfluenceFunctionBrier.cpp |only riskRegression-2022.09.13/riskRegression/src/getInfluenceFunctionBrierCVCensoringKM.cpp |only riskRegression-2022.09.13/riskRegression/src/iidCox.cpp | 2 riskRegression-2022.09.13/riskRegression/src/influenceFunctionHelpers.cpp | 2 riskRegression-2022.09.13/riskRegression/src/predictCIF.cpp | 136 riskRegression-2022.09.13/riskRegression/src/rowCumSum.cpp | 2 riskRegression-2022.09.13/riskRegression/src/rowSumsCrossprod.cpp | 2 riskRegression-2022.09.13/riskRegression/src/sweepCenterScale.cpp | 2 riskRegression-2022.09.13/riskRegression/tests/testthat |only riskRegression-2022.09.13/riskRegression/tests/testthat.R |only riskRegression-2022.09.13/riskRegression/vignettes/IFAUC.Rmd |only riskRegression-2022.09.13/riskRegression/vignettes/IFBrier.Rmd |only 81 files changed, 2111 insertions(+), 1971 deletions(-)
More information about riskRegression at CRAN
Permanent link
Title: General Package for Meta-Analysis
Description: User-friendly general package providing standard methods for meta-analysis and supporting Schwarzer, Carpenter, and Rücker <DOI:10.1007/978-3-319-21416-0>, "Meta-Analysis with R" (2015):
- common effect and random effects meta-analysis;
- several plots (forest, funnel, Galbraith / radial, L'Abbe, Baujat, bubble);
- three-level meta-analysis model;
- generalised linear mixed model;
- Hartung-Knapp method for random effects model;
- Kenward-Roger method for random effects model;
- prediction interval;
- statistical tests for funnel plot asymmetry;
- trim-and-fill method to evaluate bias in meta-analysis;
- meta-regression;
- cumulative meta-analysis and leave-one-out meta-analysis;
- import data from 'RevMan 5';
- produce forest plot summarising several (subgroup) meta-analyses.
Author: Guido Schwarzer [cre, aut]
Maintainer: Guido Schwarzer <sc@imbi.uni-freiburg.de>
Diff between meta versions 5.5-0 dated 2022-07-11 and 6.0-0 dated 2022-09-17
DESCRIPTION | 26 MD5 | 169 +-- NAMESPACE | 1 NEWS.md | 69 + R/amlodipine.R | 4 R/baujat.R | 9 R/catmeth.R | 488 ++++++---- R/ci.R | 31 R/cisapride.R | 8 R/forest-internal.R | 160 ++- R/forest.R | 2196 +++++++++++++++++++++++++++------------------ R/forest.metabind.R | 4 R/gs.R | 5 R/hetcalc.R | 15 R/is.installed.package.R | 22 R/kenwardroger.R |only R/meta-aux.R | 25 R/meta-chk.R | 30 R/meta-format.R | 40 R/meta-internal.R | 370 +++++-- R/meta-object.R |only R/meta-package.R | 416 +++++++- R/meta-set.R | 36 R/metabias.rm5.R | 6 R/metabin.R | 640 ++++--------- R/metabind.R | 82 - R/metacont.R | 499 ++-------- R/metacor.R | 441 ++------- R/metacr.R | 357 +++++-- R/metacum.R | 243 +++- R/metagen.R | 1177 +++++++++++------------- R/metainc.R | 547 +++-------- R/metainf.R | 247 +++-- R/metamean.R | 468 ++------- R/metamerge-internal.R |only R/metamerge.R | 912 +++++++++--------- R/metaprop.R | 569 +++-------- R/metarate.R | 552 +++-------- R/metareg.R | 39 R/or2smd.R | 80 + R/print.meta.R | 905 ++++++++++-------- R/print.rm5.R | 6 R/print.summary.meta.R | 38 R/read.rm5.R | 2 R/settings.meta-internal.R | 89 + R/settings.meta.R | 1208 ++++++++++++------------ R/smd2or.R | 81 + R/subgroup-internal.R |only R/subgroup.R | 832 +++++++++-------- R/subset.longarm.R | 2 R/summary.meta.R | 65 - R/summary.rm5.R | 6 R/trimfill.R | 410 ++++---- R/update.meta.R | 144 ++ man/amlodipine.Rd | 4 man/baujat.meta.Rd | 7 man/cisapride.Rd | 8 man/forest.meta.Rd | 203 ++-- man/forest.metabind.Rd | 2 man/gs.Rd | 5 man/meta-object.Rd |only man/meta-package.Rd | 412 +++++++- man/metabias.rm5.Rd | 6 man/metabin.Rd | 425 +------- man/metabind.Rd | 12 man/metacont.Rd | 425 +------- man/metacor.Rd | 364 ------- man/metacr.Rd | 65 - man/metacum.Rd | 44 man/metagen.Rd | 483 +-------- man/metainc.Rd | 373 +------ man/metainf.Rd | 44 man/metamean.Rd | 380 +------ man/metamerge.Rd | 114 -- man/metaprop.Rd | 392 +------- man/metarate.Rd | 377 +------ man/metareg.Rd | 4 man/or2smd.Rd | 4 man/print.meta.Rd | 4 man/print.rm5.Rd | 6 man/read.rm5.Rd | 2 man/settings.meta.Rd | 34 man/smd2or.Rd | 4 man/subset.longarm.Rd | 2 man/summary.meta.Rd | 47 man/summary.rm5.Rd | 6 man/trimfill.Rd | 145 -- man/update.meta.Rd | 45 88 files changed, 8842 insertions(+), 10377 deletions(-)
Title: Variational Inference for Hierarchical Generalized Linear Models
Description: Estimates hierarchical models using mean-field variational Bayes.
At present, it can estimate logistic, linear, and negative binomial models.
It can accommodate models with an arbitrary number of random effects and
requires no integration to estimate. It also provides the ability to improve
the quality of the approximation using marginal augmentation.
Goplerud (2022) <doi:10.1214/21-BA1266> provides details on the variational
algorithms.
Author: Max Goplerud [aut, cre]
Maintainer: Max Goplerud <mgoplerud@pitt.edu>
Diff between vglmer versions 1.0.0 dated 2022-09-14 and 1.0.1 dated 2022-09-17
DESCRIPTION | 8 +++++--- MD5 | 8 ++++---- NEWS.md | 5 +++++ README.md | 10 +++++++--- src/eigen_helpers.cpp | 2 +- 5 files changed, 22 insertions(+), 11 deletions(-)
Title: Robust Linear Mixed Effects Models
Description: Implements the Robust Scoring Equations estimator to fit linear
mixed effects models robustly.
Robustness is achieved by modification of the scoring equations
combined with the Design Adaptive Scale approach.
Author: Manuel Koller
Maintainer: Manuel Koller <kollerma@proton.me>
Diff between robustlmm versions 3.0-2 dated 2022-08-26 and 3.0-4 dated 2022-09-17
DESCRIPTION | 16 +---- MD5 | 30 ++++----- R/emmeans.R | 1 R/fitDatasets.R | 15 ++-- R/generateAnovaDatasets.R | 2 R/processFile.R | 32 ---------- R/processFit.R | 4 - inst/doc/rlmer.pdf |binary inst/doc/simulationStudies.pdf |binary inst/simulationStudy/consistencyAndEfficiencyBlockDiagonal.R | 34 ----------- inst/simulationStudy/robustnessDiagonal.R | 4 - man/fitDatasets.Rd | 6 - man/generateAnovaDatasets.Rd | 2 man/mergeProcessedFits.Rd | 32 ---------- man/processFit.Rd | 4 - tests/fitDatasets.R | 16 +++-- 16 files changed, 52 insertions(+), 146 deletions(-)
Title: Power Under Multiplicity Project
Description: Estimates power, minimum detectable effect size (MDES) and sample size requirements. The context is multilevel randomized experiments with multiple outcomes. The estimation takes into account the use of multiple testing procedures. Development of this package was supported by a grant from the Institute of Education Sciences (R305D170030). For a full package description, including a detailed technical appendix, see <arXiv:2112.15273>.
Author: Kristin Porter [aut],
Luke Miratrix [aut, cre] ,
Kristen Hunter [aut] ,
Zarni Htet [aut],
MDRC [cph],
Institute of Education Sciences [fnd]
Maintainer: Luke Miratrix <luke_miratrix@gse.harvard.edu>
Diff between PUMP versions 1.0.0 dated 2022-02-09 and 1.0.1 dated 2022-09-17
PUMP-1.0.0/PUMP/man/gen_full_data.Rd |only PUMP-1.0.1/PUMP/DESCRIPTION | 20 PUMP-1.0.1/PUMP/MD5 | 156 +- PUMP-1.0.1/PUMP/NAMESPACE | 8 PUMP-1.0.1/PUMP/R/correlation.R |only PUMP-1.0.1/PUMP/R/designs_and_models.R | 71 - PUMP-1.0.1/PUMP/R/grid_functions.R | 78 - PUMP-1.0.1/PUMP/R/model_fitting.R |only PUMP-1.0.1/PUMP/R/optimize_power.R | 55 PUMP-1.0.1/PUMP/R/plots.R | 220 ++- PUMP-1.0.1/PUMP/R/pump_mdes.R | 507 ++++--- PUMP-1.0.1/PUMP/R/pump_power.R | 178 +- PUMP-1.0.1/PUMP/R/pump_sample.R | 1047 ++++++++-------- PUMP-1.0.1/PUMP/R/pumpgridresult.R | 12 PUMP-1.0.1/PUMP/R/pumpresult.R | 935 +++++++------- PUMP-1.0.1/PUMP/R/simulation.R | 348 +++-- PUMP-1.0.1/PUMP/build/vignette.rds |binary PUMP-1.0.1/PUMP/inst/doc/pump_demo.R | 10 PUMP-1.0.1/PUMP/inst/doc/pump_demo.Rmd | 45 PUMP-1.0.1/PUMP/inst/doc/pump_demo.html | 74 - PUMP-1.0.1/PUMP/inst/doc/pump_sample_demo.R | 13 PUMP-1.0.1/PUMP/inst/doc/pump_sample_demo.Rmd | 13 PUMP-1.0.1/PUMP/inst/doc/pump_sample_demo.html | 53 PUMP-1.0.1/PUMP/inst/doc/pump_simulate.R | 29 PUMP-1.0.1/PUMP/inst/doc/pump_simulate.Rmd | 61 PUMP-1.0.1/PUMP/inst/doc/pump_simulate.html | 67 - PUMP-1.0.1/PUMP/man/calc_J.Rd | 61 PUMP-1.0.1/PUMP/man/calc_df.Rd | 28 PUMP-1.0.1/PUMP/man/calc_nbar.Rd | 34 PUMP-1.0.1/PUMP/man/check_cor.Rd |only PUMP-1.0.1/PUMP/man/convert_params.Rd | 16 PUMP-1.0.1/PUMP/man/estimate_power_curve.Rd | 2 PUMP-1.0.1/PUMP/man/gen_T.x.Rd | 4 PUMP-1.0.1/PUMP/man/gen_Yobs.Rd | 12 PUMP-1.0.1/PUMP/man/gen_assignments.Rd | 20 PUMP-1.0.1/PUMP/man/gen_base_sim_data.Rd |only PUMP-1.0.1/PUMP/man/gen_sim_data.Rd |only PUMP-1.0.1/PUMP/man/get_pval_tstat.Rd |only PUMP-1.0.1/PUMP/man/get_rawpt.Rd |only PUMP-1.0.1/PUMP/man/interacted_linear_estimators.Rd |only PUMP-1.0.1/PUMP/man/make_model.Rd |only PUMP-1.0.1/PUMP/man/makelist_samp.Rd |only PUMP-1.0.1/PUMP/man/optimize_power.Rd | 102 - PUMP-1.0.1/PUMP/man/parse_d_m.Rd | 2 PUMP-1.0.1/PUMP/man/plot.pumpgridresult.Rd | 42 PUMP-1.0.1/PUMP/man/plot.pumpgridresult.mdes.Rd | 22 PUMP-1.0.1/PUMP/man/plot.pumpgridresult.power.Rd | 18 PUMP-1.0.1/PUMP/man/plot.pumpgridresult.sample.Rd | 22 PUMP-1.0.1/PUMP/man/plot.pumpresult.Rd | 73 - PUMP-1.0.1/PUMP/man/plot_power_curve.Rd | 22 PUMP-1.0.1/PUMP/man/plot_power_search.Rd | 12 PUMP-1.0.1/PUMP/man/power_curve.Rd | 22 PUMP-1.0.1/PUMP/man/print_context.Rd | 2 PUMP-1.0.1/PUMP/man/print_search.Rd | 1 PUMP-1.0.1/PUMP/man/pump_mdes.Rd | 115 - PUMP-1.0.1/PUMP/man/pump_mdes_grid.Rd | 102 - PUMP-1.0.1/PUMP/man/pump_power.Rd | 155 +- PUMP-1.0.1/PUMP/man/pump_power_grid.Rd | 136 +- PUMP-1.0.1/PUMP/man/pump_sample.Rd | 112 - PUMP-1.0.1/PUMP/man/pump_sample_grid.Rd | 103 - PUMP-1.0.1/PUMP/man/pump_sample_raw.Rd | 80 - PUMP-1.0.1/PUMP/man/pumpresult.Rd | 6 PUMP-1.0.1/PUMP/tests/testthat/Rplots.pdf |binary PUMP-1.0.1/PUMP/tests/testthat/test-M1-calls.R |only PUMP-1.0.1/PUMP/tests/testthat/test-cor.R |only PUMP-1.0.1/PUMP/tests/testthat/test-designs_two.R | 7 PUMP-1.0.1/PUMP/tests/testthat/test-grid_functions.R | 18 PUMP-1.0.1/PUMP/tests/testthat/test-numZero_parameter.R | 42 PUMP-1.0.1/PUMP/tests/testthat/test-plots.R | 5 PUMP-1.0.1/PUMP/tests/testthat/test-pump_mdes.R | 43 PUMP-1.0.1/PUMP/tests/testthat/test-pump_power.R | 63 PUMP-1.0.1/PUMP/tests/testthat/test-pump_sample.R | 12 PUMP-1.0.1/PUMP/tests/testthat/test-sim-gen.R |only PUMP-1.0.1/PUMP/tests/testthat/test-sim.R | 386 +---- PUMP-1.0.1/PUMP/vignettes/output/ICCgrid.RDS |binary PUMP-1.0.1/PUMP/vignettes/output/numzerogrid.RDS |binary PUMP-1.0.1/PUMP/vignettes/output/othercorrections.RDS |binary PUMP-1.0.1/PUMP/vignettes/output/powICC.RDS |binary PUMP-1.0.1/PUMP/vignettes/output/powR2.RDS |binary PUMP-1.0.1/PUMP/vignettes/output/powbase.RDS |binary PUMP-1.0.1/PUMP/vignettes/output/rhogrid.RDS |binary PUMP-1.0.1/PUMP/vignettes/output/samplesizeverify.RDS |binary PUMP-1.0.1/PUMP/vignettes/pump_demo.Rmd | 45 PUMP-1.0.1/PUMP/vignettes/pump_sample_demo.Rmd | 13 PUMP-1.0.1/PUMP/vignettes/pump_simulate.Rmd | 61 PUMP-1.0.1/PUMP/vignettes/refs.bib | 6 86 files changed, 3224 insertions(+), 2803 deletions(-)
Title: Multilevel Joint Modelling Multiple Imputation
Description: Similarly to Schafer's package 'pan', 'jomo' is a package for multilevel joint modelling multiple imputation (Carpenter and Kenward, 2013) <doi:10.1002/9781119942283>.
Novel aspects of 'jomo' are the possibility of handling binary and categorical data through latent normal variables, the option to use cluster-specific covariance matrices and to impute compatibly with the substantive model.
Author: Matteo Quartagno, James Carpenter
Maintainer: Matteo Quartagno <m.quartagno@ucl.ac.uk>
Diff between jomo versions 2.7-3 dated 2022-02-08 and 2.7-4 dated 2022-09-17
DESCRIPTION | 8 ++--- MD5 | 64 ++++++++++++++++++++++---------------------- R/jomo1cat.MCMCchain.R | 2 - R/jomo1cat.R | 2 - R/jomo1con.MCMCchain.R | 2 - R/jomo1con.R | 2 - R/jomo1mix.MCMCchain.R | 2 - R/jomo1mix.R | 2 - R/jomo1rancat.MCMCchain.R | 2 - R/jomo1rancat.R | 2 - R/jomo1rancathr.MCMCchain.R | 2 - R/jomo1rancathr.R | 2 - R/jomo1rancon.MCMCchain.R | 2 - R/jomo1rancon.R | 2 - R/jomo1ranconhr.MCMCchain.R | 2 - R/jomo1ranconhr.R | 2 - R/jomo1ranmix.MCMCchain.R | 2 - R/jomo1ranmix.R | 2 - R/jomo1ranmixhr.MCMCchain.R | 2 - R/jomo1ranmixhr.R | 2 - R/jomo2com.MCMCchain.R | 4 +- R/jomo2com.R | 4 +- R/jomo2hr.MCMCchain.R | 4 +- R/jomo2hr.R | 4 +- src/jomo1C.c | 4 +- src/jomo1ranC.c | 4 +- src/jomo1ranhrC.c | 8 ++--- src/jomo1ranhrsmcC.c | 4 ++ src/jomo1smcC.c | 4 ++ src/jomo2comC.c | 4 +- src/jomo2hrC.c | 8 ++--- src/jomo2hrsmcC.c | 4 ++ src/jomo2smcC.c | 4 ++ 33 files changed, 88 insertions(+), 80 deletions(-)
Title: Tools to Easily Download Data from INSEE BDM Database
Description: Using embedded sdmx queries, get the data of more than 150 000 insee series from 'bdm' macroeconomic database.
Author: Hadrien Leclerc [aut, cre],
INSEE [cph]
Maintainer: Hadrien Leclerc <leclerc.hadrien@gmail.com>
Diff between insee versions 1.1.4 dated 2022-03-10 and 1.1.5 dated 2022-09-17
insee-1.1.4/insee/R/read_sdmx_fast.R |only insee-1.1.5/insee/DESCRIPTION | 12 insee-1.1.5/insee/MD5 | 55 - insee-1.1.5/insee/NEWS.md | 127 ++- insee-1.1.5/insee/R/create_insee_folder.R | 2 insee-1.1.5/insee/R/dwn_idbank_files.R | 65 +- insee-1.1.5/insee/R/get_dataset_dimension.R | 10 insee-1.1.5/insee/R/get_dataset_list.R | 72 +- insee-1.1.5/insee/R/get_idbank_list.R | 7 insee-1.1.5/insee/R/get_insee.R | 189 ++--- insee-1.1.5/insee/R/read_sdmx_slow.R | 3 insee-1.1.5/insee/R/sysdata.rda |binary insee-1.1.5/insee/R/zzz.R | 6 insee-1.1.5/insee/README.md | 482 +++++++-------- insee-1.1.5/insee/build/vignette.rds |binary insee-1.1.5/insee/inst/doc/insee.Rmd | 8 insee-1.1.5/insee/inst/doc/insee.html | 143 +++- insee-1.1.5/insee/inst/doc/v2_gdp-vignettes.html | 25 insee-1.1.5/insee/inst/doc/v3_inflation-vignettes.html | 25 insee-1.1.5/insee/inst/doc/v4_unem-vignettes.html | 25 insee-1.1.5/insee/inst/doc/v5_pop-vignettes.html | 25 insee-1.1.5/insee/inst/doc/v6_pop_map-vignettes.R | 15 insee-1.1.5/insee/inst/doc/v6_pop_map-vignettes.Rmd | 299 ++++----- insee-1.1.5/insee/inst/doc/v6_pop_map-vignettes.html | 68 +- insee-1.1.5/insee/inst/doc/v7_death_birth-vignettes.html | 25 insee-1.1.5/insee/man/get_insee.Rd | 2 insee-1.1.5/insee/tests/testthat/test_all.R | 374 +++++------ insee-1.1.5/insee/vignettes/insee.Rmd | 8 insee-1.1.5/insee/vignettes/v6_pop_map-vignettes.Rmd | 299 ++++----- 29 files changed, 1303 insertions(+), 1068 deletions(-)
Title: S3 Infrastructure for Regular and Irregular Time Series (Z's
Ordered Observations)
Description: An S3 class with methods for totally ordered indexed
observations. It is particularly aimed at irregular time series
of numeric vectors/matrices and factors. zoo's key design goals
are independence of a particular index/date/time class and
consistency with ts and base R by providing methods to extend
standard generics.
Author: Achim Zeileis [aut, cre] ,
Gabor Grothendieck [aut],
Jeffrey A. Ryan [aut],
Joshua M. Ulrich [ctb],
Felix Andrews [ctb]
Maintainer: Achim Zeileis <Achim.Zeileis@R-project.org>
Diff between zoo versions 1.8-10 dated 2022-04-15 and 1.8-11 dated 2022-09-17
DESCRIPTION | 10 +++++----- MD5 | 34 +++++++++++++++++----------------- NAMESPACE | 1 + NEWS | 27 +++++++++++++++++++++++++++ R/MATCH.R | 18 ++++++++++++++---- R/as.zoo.R | 6 ++++-- R/merge.zoo.R | 16 ++++++++-------- build/vignette.rds |binary inst/doc/zoo-design.pdf |binary inst/doc/zoo-faq.pdf |binary inst/doc/zoo-quickref.pdf |binary inst/doc/zoo-read.pdf |binary inst/doc/zoo.pdf |binary man/MATCH.Rd | 18 ++++++++++++++++-- man/as.zoo.Rd | 4 ++-- man/merge.zoo.Rd | 4 +++- man/yearmon.Rd | 8 +++++++- tests/Examples/zoo-Ex.Rout.save | 27 +++++++++++++++++---------- 18 files changed, 121 insertions(+), 52 deletions(-)
Title: Modeling Spatially Varying Coefficients
Description: Implements a maximum likelihood estimation (MLE) method for
estimation and prediction of Gaussian process-based spatially varying
coefficient (SVC) models (Dambon et al. (2021a)
<doi:10.1016/j.spasta.2020.100470>). Covariance tapering (Furrer et
al. (2006) <doi:10.1198/106186006X132178>) can be applied such that
the method scales to large data. Further, it implements a joint
variable selection of the fixed and random effects (Dambon et al.
(2021b) <doi:10.1080/13658816.2022.2097684>). The package and its
capabilities are described in (Dambon et al. (2021c) <arXiv:2106.02364>).
Author: Jakob A. Dambon [aut, cre] ,
Fabio Sigrist [ctb] ,
Reinhard Furrer [ctb]
Maintainer: Jakob A. Dambon <jakob.dambon@math.uzh.ch>
Diff between varycoef versions 0.3.3 dated 2022-05-31 and 0.3.4 dated 2022-09-17
varycoef-0.3.3/varycoef/R/help_functions.R |only varycoef-0.3.3/varycoef/man/Sigma_y.Rd |only varycoef-0.3.3/varycoef/man/own_dist.Rd |only varycoef-0.3.3/varycoef/man/prep_par_output.Rd |only varycoef-0.3.4/varycoef/DESCRIPTION | 57 +-- varycoef-0.3.4/varycoef/MD5 | 72 ++-- varycoef-0.3.4/varycoef/NAMESPACE | 14 varycoef-0.3.4/varycoef/R/SVC_mle.R | 295 +++++++++---------- varycoef-0.3.4/varycoef/R/SVC_selection.R | 42 +- varycoef-0.3.4/varycoef/R/cov_par.R | 4 varycoef-0.3.4/varycoef/R/data.R | 28 + varycoef-0.3.4/varycoef/R/example.R |only varycoef-0.3.4/varycoef/R/nlocs.R | 5 varycoef-0.3.4/varycoef/R/nobs-SVC_mle.R | 3 varycoef-0.3.4/varycoef/R/objective_functions.R | 1 varycoef-0.3.4/varycoef/R/predict-SVC_mle.R | 121 +++---- varycoef-0.3.4/varycoef/R/print-SVC_mle.R | 10 varycoef-0.3.4/varycoef/R/utils.R |only varycoef-0.3.4/varycoef/R/varycoef.R | 11 varycoef-0.3.4/varycoef/build/partial.rdb |binary varycoef-0.3.4/varycoef/build/vignette.rds |only varycoef-0.3.4/varycoef/data/SVCdata.rda |only varycoef-0.3.4/varycoef/data/house.rda |binary varycoef-0.3.4/varycoef/inst/CITATION | 6 varycoef-0.3.4/varycoef/inst/doc |only varycoef-0.3.4/varycoef/man/GLS_chol.Rd | 4 varycoef-0.3.4/varycoef/man/SVC_mle.Rd | 118 +++---- varycoef-0.3.4/varycoef/man/SVC_selection.Rd | 7 varycoef-0.3.4/varycoef/man/SVC_selection_control.Rd | 7 varycoef-0.3.4/varycoef/man/SVCdata.Rd |only varycoef-0.3.4/varycoef/man/check_cov_lower.Rd | 2 varycoef-0.3.4/varycoef/man/cov_par.Rd | 11 varycoef-0.3.4/varycoef/man/init_bounds_optim.Rd | 2 varycoef-0.3.4/varycoef/man/nlocs.Rd | 11 varycoef-0.3.4/varycoef/man/nobs.SVC_mle.Rd | 2 varycoef-0.3.4/varycoef/man/predict.SVC_mle.Rd | 81 +---- varycoef-0.3.4/varycoef/man/sample_SVCdata.Rd |only varycoef-0.3.4/varycoef/man/varycoef.Rd | 11 varycoef-0.3.4/varycoef/tests |only varycoef-0.3.4/varycoef/vignettes |only 40 files changed, 475 insertions(+), 450 deletions(-)
Title: Survey Value of Information
Description: Decision support tool for prioritizing sites for ecological
surveys based on their potential to improve plans for conserving
biodiversity (e.g. plans for establishing protected areas). Given a set of
sites that could potentially be acquired for conservation management,
it can be used to generate and evaluate plans for surveying additional
sites. Specifically, plans for ecological surveys can be
generated using various conventional approaches (e.g. maximizing expected
species richness, geographic coverage, diversity of sampled environmental
algorithms. After generating such survey plans, they can be evaluated using
conditions) and maximizing value of information. Please note that several
functions depend on the 'Gurobi' optimization software (available from
<https://www.gurobi.com>). Additionally, the 'JAGS' software (available from
<https://mcmc-jags.sourceforge.io/>) is required to fit hierarchical
generalized linear models.
Author: Jeffrey O Hanson [aut, cre] ,
Iadine Chades [aut] ,
Emma J Hudgins [aut] ,
Joseph R Bennett [aut]
Maintainer: Jeffrey O Hanson <jeffrey.hanson@uqconnect.edu.au>
Diff between surveyvoi versions 1.0.4 dated 2022-08-26 and 1.0.5 dated 2022-09-17
DESCRIPTION | 9 +- MD5 | 34 +++++---- NEWS.md | 29 +++++-- R/feasible_survey_schemes.R | 2 R/ilp.R | 2 R/internal.R | 60 ++++++++++++++++ R/zzz.R |only README.md | 41 +++++++--- inst/doc/surveyvoi.html | 4 - man/figures/README-unnamed-chunk-10-1.png |binary man/figures/README-unnamed-chunk-10-2.png |only man/figures/README-unnamed-chunk-13-1.png |only man/figures/README-unnamed-chunk-14-1.png |only src/functions.cpp | 4 - tests/testthat.R | 37 ++++++++- tests/testthat/helper_skip_functions.R | 13 +++ tests/testthat/test_approx_near_optimal_survey_scheme.R | 1 tests/testthat/test_cluster.R | 2 tests/testthat/test_fit_hglm_occupancy_models.R | 1 tests/testthat/test_optimal_survey_scheme.R | 1 20 files changed, 186 insertions(+), 54 deletions(-)
Title: Analyze Shot Group Data
Description: Analyzes shooting data with respect to group shape,
precision, and accuracy. This includes graphical methods,
descriptive statistics, and inference tests using standard,
but also non-parametric and robust statistical methods.
Implements distributions for radial error in bivariate normal
variables. Works with files exported by 'OnTarget PC/TDS',
'Silver Mountain' e-target, 'ShotMarker' e-target, or 'Taran',
as well as with custom data files in text format.
Supports inference from range statistics such as extreme
spread. Includes a set of web-based graphical user interfaces.
Author: Daniel Wollschlaeger
Maintainer: Daniel Wollschlaeger <dwoll@kuci.org>
Diff between shotGroups versions 0.8.1 dated 2021-04-10 and 0.8.2 dated 2022-09-17
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Title: Benchmark Suite for Indirect Methods for RI Estimation
Description: The provided benchmark suite enables the automated evaluation and comparison of any existing and novel indirect method for reference interval ('RI') estimation in a systematic way.
Indirect methods take routine measurements of diagnostic tests, containing pathological and non-pathological samples as input and use sophisticated
statistical methods to derive a model describing the distribution of the non-pathological samples, which can then be
used to derive reference intervals. The benchmark suite contains 5,760 simulated test sets with varying difficulty.
To include any indirect method, a custom wrapper function needs to be provided.
The package offers functions for generating the test sets, executing the indirect method and evaluating the results.
See ?RIbench or vignette("RIbench_package") for a more comprehensive description of the features.
A detailed description and application is described in Ammer T., Schuetzenmeister A., Prokosch H.-U., Zierk J., Rank C.M., Rauh M. "RIbench: A [...truncated...]
Author: Tatjana Ammer [aut, cre],
Christopher Rank [aut],
Andre Schuetzenmeister [aut]
Maintainer: Tatjana Ammer <tatjana.ammer@roche.com>
Diff between RIbench versions 1.0.0 dated 2022-08-29 and 1.0.1 dated 2022-09-17
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Title: Systematic Conservation Prioritization in R
Description: Systematic conservation prioritization using mixed integer linear
programming (MILP). It provides a flexible interface for building and
solving conservation planning problems. Once built, conservation planning
problems can be solved using a variety of commercial and open-source exact
algorithm solvers. By using exact algorithm solvers, solutions can be
generated that are guaranteed to be optimal (or within a pre-specified
optimality gap). Furthermore, conservation problems can be constructed to
optimize the spatial allocation of different management actions or zones,
meaning that conservation practitioners can identify solutions that benefit
multiple stakeholders. To solve large-scale or complex conservation
planning problems, users should install the Gurobi optimization software
(available from <https://www.gurobi.com/>) and the 'gurobi' R package (see
Gurobi Installation Guide vignette for details). Users can also install the
IBM CPLEX software (<https://www.ibm.com/analytic [...truncated...]
Author: Jeffrey O Hanson [aut] ,
Richard Schuster [aut, cre] ,
Nina Morrell [aut],
Matthew Strimas-Mackey [aut] ,
Brandon P M Edwards [aut] ,
Matthew E Watts [aut],
Peter Arcese [aut] ,
Joseph Bennett [aut] ,
Hugh P Possingham [aut]
Maintainer: Richard Schuster <richard.schuster@glel.carleton.ca>
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prioritizr-7.2.2/prioritizr/tests/testthat/test_sp_to_polyset.R | 26 prioritizr-7.2.2/prioritizr/vignettes/calibrating_trade-offs_tutorial.Rmd |only prioritizr-7.2.2/prioritizr/vignettes/connectivity_tutorial.Rmd |only prioritizr-7.2.2/prioritizr/vignettes/gurobi_installation_guide.Rmd |only prioritizr-7.2.2/prioritizr/vignettes/management_zones_tutorial.Rmd |only prioritizr-7.2.2/prioritizr/vignettes/package_overview.Rmd |only prioritizr-7.2.2/prioritizr/vignettes/prioritizr.Rmd | 1200 - prioritizr-7.2.2/prioritizr/vignettes/publication_record.Rmd | 168 prioritizr-7.2.2/prioritizr/vignettes/references.bib | 326 prioritizr-7.2.2/prioritizr/vignettes/solver_benchmarks.Rmd |only 320 files changed, 31532 insertions(+), 32593 deletions(-)
Title: Non-Local Prior Based Iterative Variable Selection Tool for
Genome-Wide Association Studies
Description: Performs variable selection with data from Genome-wide association studies (GWAS), or other high-dimensional data, combining in an iterative framework, the computational efficiency of the screen-and-select variable selection approach based on some association learning and the parsimonious uncertainty quantification provided by the use of non-local priors as described in Sanyal et al. (2019) <DOI:10.1093/bioinformatics/bty472>.
Author: Nilotpal Sanyal [aut, cre]
Maintainer: Nilotpal Sanyal <nilotpal.sanyal@gmail.com>
Diff between GWASinlps versions 2.0 dated 2022-09-14 and 2.1 dated 2022-09-17
DESCRIPTION | 6 +++--- MD5 | 10 +++++----- NEWS | 4 ++++ NEWS.md | 4 ++++ man/GWASinlps-package.Rd | 2 +- src/GWASinlps.cpp | 2 +- 6 files changed, 18 insertions(+), 10 deletions(-)
Title: Predict Peptide-MHC Binding
Description: A suite of tools to predict peptide MHC (major histocompatibility complex) presentation in the context of both human and mouse. Polymorphic peptides between self and foreign proteins are identified. The ability of peptides to bind self MHC is assessed and scored. Based on half maximal inhibitory concentration as queried through the immune epitope database API <http://tools.iedb.org/mhcii/> using user defined methods, the foreign peptides most likely to be presented are output along with their predicted binding strength, amino acid position, the protein from which each peptide was derived, and the presenting allele. "References:" Vita R, Mahajan S, Overton JA, Dhanda SK, Martini S, Cantrell JR, Wheeler DK, Sette A, Peters B. <doi:10.1093/nar/gky1006>.
Author: Joan Zhang [aut, cre],
Aileen Johnson [aut],
Christian P Larsen [cph, aut]
Maintainer: Joan Zhang <joan.zhang@emory.edu>
Diff between epitopR versions 0.1.1 dated 2022-08-19 and 0.1.2 dated 2022-09-17
.aspell |only DESCRIPTION | 11 +-- MD5 | 12 +-- R/utils.R | 34 +++++---- inst/doc/mhcII-hu.R | 19 ++--- inst/doc/mhcII-hu.Rmd | 19 ++--- inst/doc/mhcII-hu.html | 168 +++++++++++++++++++++++++------------------------ vignettes/mhcII-hu.Rmd | 19 ++--- 8 files changed, 146 insertions(+), 136 deletions(-)
Title: Statistical Functions for the Design of Studies with Composite
Endpoints
Description: It has been designed to calculate the required sample size in randomized clinical trials with composite endpoints. This package also includes functions to calculate the probability of observing the composite endpoint and the expected effect on the composite endpoint, among others. The methods implemented can be found in Bofill & Gómez (2019) <doi:10.1002/sim.8092> and Gómez & Lagakos (2013) <doi:10.1002/sim.5547>.
Author: Marta Bofill Roig [aut, cre], Jordi Cortes Martinez [aut], Guadalupe Gomez Melis [ctb]
Maintainer: Marta Bofill Roig <marta.bofillroig@meduniwien.ac.at>
Diff between CompAREdesign versions 1.9 dated 2021-06-15 and 2.0 dated 2022-09-17
CompAREdesign-1.9/CompAREdesign/R/schoendfeld_formula.R |only CompAREdesign-1.9/CompAREdesign/man/figures |only CompAREdesign-1.9/CompAREdesign/man/schoendfeld_formula.Rd |only CompAREdesign-2.0/CompAREdesign/DESCRIPTION | 12 CompAREdesign-2.0/CompAREdesign/MD5 | 70 ++- CompAREdesign-2.0/CompAREdesign/NAMESPACE | 12 CompAREdesign-2.0/CompAREdesign/R/ARE_tte.R | 196 +++++++--- CompAREdesign-2.0/CompAREdesign/R/CopulaSelection.R | 6 CompAREdesign-2.0/CompAREdesign/R/MarginalsSelection.R | 36 +- CompAREdesign-2.0/CompAREdesign/R/effectsize_tte.R | 93 +++-- CompAREdesign-2.0/CompAREdesign/R/f_sim.R |only CompAREdesign-2.0/CompAREdesign/R/get_prob1.R |only CompAREdesign-2.0/CompAREdesign/R/plot_tte.R |only CompAREdesign-2.0/CompAREdesign/R/sample_size_tte.R | 131 +++++-- CompAREdesign-2.0/CompAREdesign/R/schoenfeld_formula.R |only CompAREdesign-2.0/CompAREdesign/R/simula_cbe.R |only CompAREdesign-2.0/CompAREdesign/R/simula_tte.R |only CompAREdesign-2.0/CompAREdesign/R/surv_tte.R |only CompAREdesign-2.0/CompAREdesign/man/ARE_cbe.Rd | 98 ++--- CompAREdesign-2.0/CompAREdesign/man/ARE_tte.Rd | 143 ++++--- CompAREdesign-2.0/CompAREdesign/man/CompAREdesign-package.Rd | 38 -- CompAREdesign-2.0/CompAREdesign/man/CopulaSelection.Rd | 40 +- CompAREdesign-2.0/CompAREdesign/man/MarginalsSelection.Rd | 83 ++-- CompAREdesign-2.0/CompAREdesign/man/Sstar.Rd | 52 +- CompAREdesign-2.0/CompAREdesign/man/Sstar_func_perc.Rd | 26 - CompAREdesign-2.0/CompAREdesign/man/dClayton.Rd | 24 - CompAREdesign-2.0/CompAREdesign/man/dFGM.Rd | 24 - CompAREdesign-2.0/CompAREdesign/man/dFrank.Rd | 24 - CompAREdesign-2.0/CompAREdesign/man/dGumbel.Rd | 24 - CompAREdesign-2.0/CompAREdesign/man/dNormal.Rd | 24 - CompAREdesign-2.0/CompAREdesign/man/effectsize_cbe.Rd | 100 ++--- CompAREdesign-2.0/CompAREdesign/man/effectsize_tte.Rd | 197 +++++------ CompAREdesign-2.0/CompAREdesign/man/f_sim.Rd |only CompAREdesign-2.0/CompAREdesign/man/freedman_formula.Rd | 24 - CompAREdesign-2.0/CompAREdesign/man/lower_corr.Rd | 54 +-- CompAREdesign-2.0/CompAREdesign/man/plot_tte.Rd |only CompAREdesign-2.0/CompAREdesign/man/prob_cbe.Rd | 68 +-- CompAREdesign-2.0/CompAREdesign/man/samplesize_cbe.Rd | 122 +++--- CompAREdesign-2.0/CompAREdesign/man/samplesize_tte.Rd | 177 +++++---- CompAREdesign-2.0/CompAREdesign/man/schoenfeld_formula.Rd |only CompAREdesign-2.0/CompAREdesign/man/simula_cbe.Rd |only CompAREdesign-2.0/CompAREdesign/man/simula_tte.Rd |only CompAREdesign-2.0/CompAREdesign/man/surv_tte.Rd |only CompAREdesign-2.0/CompAREdesign/man/upper_corr.Rd | 54 +-- 44 files changed, 1087 insertions(+), 865 deletions(-)
Title: Optimal Weight Exchange Algorithm for Optimal Designs for Three
Models
Description: An implementation of optimal weight exchange algorithm Yang(2013) <doi:10.1080/01621459.2013.806268> for three models.
They are Crossover model with subject dropout, crossover model with proportional
first order residual effects and interference model. You can use it to find either
A-opt or D-opt approximate designs. Exact designs can be automatically rounded
from approximate designs and relative efficiency is provided as well.
Author: Shuai Hao [aut, cre],
Min Yang [aut],
Wei Zheng [aut]
Maintainer: Shuai Hao <shuaih0303@gmail.com>
Diff between OWEA versions 0.1.1 dated 2018-11-03 and 0.1.2 dated 2022-09-17
DESCRIPTION | 11 MD5 | 30 - R/app.R | 22 - R/design.R | 834 ++++++++++++++++++++++---------------------- R/efficiency.R | 486 +++++++++++++------------- R/informatrix.R | 470 ++++++++++++------------- R/owea.R | 26 - R/summary.R | 178 ++++----- README.md | 4 inst/shiny/server.R | 424 +++++++++++----------- inst/shiny/ui.R | 626 ++++++++++++++++----------------- inst/test/example.R | 420 +++++++++++----------- inst/test/example.html | 914 ++++++++++++++++++++++++------------------------- man/OWEA.Rd | 1 man/design.Rd | 11 man/eff.Rd | 10 16 files changed, 2236 insertions(+), 2231 deletions(-)
Title: Likelihood Ratio Tests and Confidence Intervals
Description: A collection of hypothesis tests and confidence intervals based on the likelihood ratio
<https://en.wikipedia.org/wiki/Likelihood-ratio_test>.
Author: Greg McMahan
Maintainer: Greg McMahan <gmcmacran@gmail.com>
Diff between LRTesteR versions 1.0.0 dated 2022-08-24 and 1.0.1 dated 2022-09-17
LRTesteR-1.0.0/LRTesteR/inst/doc/Generalized_One_Way.R |only LRTesteR-1.0.0/LRTesteR/inst/doc/Generalized_One_Way.Rmd |only LRTesteR-1.0.0/LRTesteR/inst/doc/Generalized_One_Way.html |only LRTesteR-1.0.0/LRTesteR/vignettes/Generalized_One_Way.Rmd |only LRTesteR-1.0.1/LRTesteR/DESCRIPTION | 10 - LRTesteR-1.0.1/LRTesteR/MD5 | 96 +++++----- LRTesteR-1.0.1/LRTesteR/NAMESPACE | 6 LRTesteR-1.0.1/LRTesteR/NEWS.md | 5 LRTesteR-1.0.1/LRTesteR/R/a_function_factories.R | 36 +++ LRTesteR-1.0.1/LRTesteR/R/beta_tests.R | 4 LRTesteR-1.0.1/LRTesteR/R/binomial_tests.R | 4 LRTesteR-1.0.1/LRTesteR/R/cauchy_tests.R | 4 LRTesteR-1.0.1/LRTesteR/R/exponential_tests.R | 4 LRTesteR-1.0.1/LRTesteR/R/gamma_tests.R | 6 LRTesteR-1.0.1/LRTesteR/R/gaussian_tests.R | 4 LRTesteR-1.0.1/LRTesteR/R/inverse_gaussian_tests.R |only LRTesteR-1.0.1/LRTesteR/R/negative_binomial_tests.R | 4 LRTesteR-1.0.1/LRTesteR/R/poisson_tests.R | 4 LRTesteR-1.0.1/LRTesteR/R/print.R | 2 LRTesteR-1.0.1/LRTesteR/README.md | 15 - LRTesteR-1.0.1/LRTesteR/build/vignette.rds |binary LRTesteR-1.0.1/LRTesteR/inst/doc/Analysis_of_Deviance.R |only LRTesteR-1.0.1/LRTesteR/inst/doc/Analysis_of_Deviance.Rmd |only LRTesteR-1.0.1/LRTesteR/inst/doc/Analysis_of_Deviance.html |only LRTesteR-1.0.1/LRTesteR/man/beta_shape1_one_way.Rd | 4 LRTesteR-1.0.1/LRTesteR/man/beta_shape2_one_way.Rd | 4 LRTesteR-1.0.1/LRTesteR/man/binomial_p_one_sample.Rd | 4 LRTesteR-1.0.1/LRTesteR/man/binomial_p_one_way.Rd | 4 LRTesteR-1.0.1/LRTesteR/man/cauchy_location_one_way.Rd | 4 LRTesteR-1.0.1/LRTesteR/man/cauchy_scale_one_way.Rd | 4 LRTesteR-1.0.1/LRTesteR/man/exponential_rate_one_sample.Rd | 4 LRTesteR-1.0.1/LRTesteR/man/exponential_rate_one_way.Rd | 4 LRTesteR-1.0.1/LRTesteR/man/gamma_rate_one_way.Rd | 4 LRTesteR-1.0.1/LRTesteR/man/gamma_scale_one_way.Rd | 4 LRTesteR-1.0.1/LRTesteR/man/gamma_shape_one_way.Rd | 4 LRTesteR-1.0.1/LRTesteR/man/gaussian_mu_one_way.Rd | 4 LRTesteR-1.0.1/LRTesteR/man/gaussian_variance_one_way.Rd | 4 LRTesteR-1.0.1/LRTesteR/man/inverse_gaussian_dispersion_one_sample.Rd |only LRTesteR-1.0.1/LRTesteR/man/inverse_gaussian_dispersion_one_way.Rd |only LRTesteR-1.0.1/LRTesteR/man/inverse_gaussian_mu_one_sample.Rd |only LRTesteR-1.0.1/LRTesteR/man/inverse_gaussian_mu_one_way.Rd |only LRTesteR-1.0.1/LRTesteR/man/inverse_gaussian_shape_one_sample.Rd |only LRTesteR-1.0.1/LRTesteR/man/inverse_gaussian_shape_one_way.Rd |only LRTesteR-1.0.1/LRTesteR/man/negative_binomial_p_one_sample.Rd | 4 LRTesteR-1.0.1/LRTesteR/man/negative_binomial_p_one_way.Rd | 4 LRTesteR-1.0.1/LRTesteR/man/poisson_lambda_one_sample.Rd | 4 LRTesteR-1.0.1/LRTesteR/man/poisson_lambda_one_way.Rd | 4 LRTesteR-1.0.1/LRTesteR/tests/testthat/test_beta_tests.R | 43 ++++ LRTesteR-1.0.1/LRTesteR/tests/testthat/test_binomial_tests.R | 22 ++ LRTesteR-1.0.1/LRTesteR/tests/testthat/test_cauchy_tests.R | 44 ++++ LRTesteR-1.0.1/LRTesteR/tests/testthat/test_exponential_tests.R | 22 ++ LRTesteR-1.0.1/LRTesteR/tests/testthat/test_gamma_tests.R | 78 +++++++- LRTesteR-1.0.1/LRTesteR/tests/testthat/test_gaussian_tests.R | 40 ++++ LRTesteR-1.0.1/LRTesteR/tests/testthat/test_inverse_gaussian.R |only LRTesteR-1.0.1/LRTesteR/tests/testthat/test_negative_binomial_tests.R | 22 ++ LRTesteR-1.0.1/LRTesteR/tests/testthat/test_poisson_tests.R | 22 ++ LRTesteR-1.0.1/LRTesteR/vignettes/Analysis_of_Deviance.Rmd |only 57 files changed, 443 insertions(+), 122 deletions(-)
Title: Providing Data from the US Department of Housing and Urban
Development
Description: Provides functions to access data from the US Department of Housing and Urban Development <https://www.huduser.gov/portal/dataset/fmr-api.html>.
Author: Paul Richardson
Maintainer: Paul Richardson <p.richardson.54391@gmail.com>
Diff between hudr versions 1.1.0 dated 2022-05-16 and 1.2.0 dated 2022-09-17
DESCRIPTION | 10 ++-- MD5 | 27 ++++++---- NAMESPACE | 2 R/chas.R |only R/hudr.R | 94 +++++++++++++++++++------------------- man/check_args.Rd | 2 man/get_hud_chas_data.Rd |only man/get_hud_chas_entityid_list.Rd |only man/get_hud_fmr_data.Rd | 4 - man/get_hud_fmr_listcounties.Rd | 2 man/get_hud_fmr_listmetros.Rd | 2 man/get_hud_fmr_liststates.Rd | 2 man/get_hud_fmr_statedata.Rd | 4 - man/get_hud_il_data.Rd | 4 - man/get_hud_il_statedata.Rd | 4 - man/hudr-package.Rd | 2 16 files changed, 83 insertions(+), 76 deletions(-)
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2022-08-30 0.1-2
Title: Strength Training Manual R-Language Functions
Description: Strength training prescription using percent-based approach requires
numerous computations and assumptions. 'STMr' package allow users to estimate
individual reps-max relationships, implement various progression tables, and
create numerous set and rep schemes. The 'STMr' package is originally created as
a tool to help writing Jovanović M. (2020) Strength Training Manual
<ISBN:979-8604459898>.
Author: Mladen Jovanović [aut, cre]
Maintainer: Mladen Jovanović <coach.mladen.jovanovic@gmail.com>
Diff between STMr versions 0.1.4 dated 2022-08-31 and 0.1.5 dated 2022-09-17
DESCRIPTION | 6 MD5 | 41 +++-- NAMESPACE | 1 NEWS.md | 7 + R/dataset-strength-training-log.R | 5 R/estimate-rolling.R |only README.md | 207 +++++++++++++++++++----------- data/strength_training_log.rda |binary inst/CITATION | 4 man/estimate_rolling_1RM.Rd |only man/figures/README-unnamed-chunk-59-1.png |binary man/figures/README-unnamed-chunk-61-1.png |binary man/figures/README-unnamed-chunk-63-1.png |binary man/figures/README-unnamed-chunk-64-1.png |binary man/figures/README-unnamed-chunk-65-1.png |binary man/figures/README-unnamed-chunk-66-1.png |binary man/figures/README-unnamed-chunk-67-1.png |binary man/figures/README-unnamed-chunk-68-1.png |binary man/figures/README-unnamed-chunk-69-1.png |binary man/figures/README-unnamed-chunk-70-1.png |binary man/figures/README-unnamed-chunk-71-1.png |binary man/figures/README-unnamed-chunk-72-1.png |only man/strength_training_log.Rd | 5 23 files changed, 173 insertions(+), 103 deletions(-)
Title: A Tool for Calculation and Optimization of the Expected Gain
from Multi-Stage Selection
Description: Multi-stage selection is practiced in numerous fields of life
and social sciences and particularly in breeding. A special characteristic of
multi-stage selection is that candidates are evaluated in successive stages
with increasing intensity and effort, and only a fraction of the superior
candidates is selected and promoted to the next stage. For the optimum design
of such selection programs, the selection gain plays a crucial role. It can be
calculated by integration of a truncated multivariate normal (MVN) distribution.
While mathematical formulas for calculating the selection gain and the variance
among selected candidates were developed long time ago, solutions for numerical
calculation were not available. This package can also be used for optimizing
multi-stage selection programs for a given total budget and different costs of
evaluating the candidates in each stage.
Author: Xuefei Mi, Jose Marulanda, H. Friedrich Utz, Albrecht E. Melchinger
Maintainer: Xuefei Mi <mi_xue_fei@hotmail.com>
Diff between selectiongain versions 2.0.707 dated 2022-02-12 and 2.0.710 dated 2022-09-17
DESCRIPTION | 8 ++++---- MD5 | 4 ++-- man/multistagegain.each.Rd | 2 +- 3 files changed, 7 insertions(+), 7 deletions(-)
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2017-11-23 1.0.0
2017-10-11 0.0.6
2017-10-11 0.0.7
2017-02-23 0.0.5
2016-08-08 0.0.4
2016-06-01 0.0.3
2016-01-18 0.0.2
2015-12-03 0.0.1
Title: Retrieve and Plot Google n-Gram Data
Description: Retrieve and plot word frequencies through time from the "Google
Ngram Viewer" <https://books.google.com/ngrams>.
Author: Sean Carmody [aut, cre, cph]
Maintainer: Sean Carmody <seancarmody@gmail.com>
Diff between ngramr versions 1.7.7 dated 2022-09-10 and 1.8.0 dated 2022-09-17
DESCRIPTION | 8 ++++---- MD5 | 10 +++++----- NEWS.md | 5 +++++ R/ggram.R | 6 +++--- R/ngram.R | 14 +++++++------- man/ggram.Rd | 6 +++--- 6 files changed, 27 insertions(+), 22 deletions(-)