Title: Maximum Likelihood Estimates of Gaussian Processes
Description: Maximum likelihood Gaussian process modeling for
univariate and multi-dimensional outputs with diagnostic plots
following Santner et al (2003) <doi:10.1007/978-1-4757-3799-8>.
Contact the maintainer for a package version that includes
sensitivity analysis.
Author: Garrett M. Dancik
Maintainer: Garrett M. Dancik <dancikg@easternct.edu>
Diff between mlegp versions 3.1.5 dated 2018-01-30 and 3.1.7 dated 2018-04-14
DESCRIPTION | 13 +++++++------ MD5 | 11 ++++++----- inst/CITATION |only inst/doc/mlegp.pdf |binary src/fit_gp.h | 6 +++--- src/mlegp.c | 5 ++--- src/nelder_mead_min.c | 2 +- 7 files changed, 19 insertions(+), 18 deletions(-)
Title: Dot-and-Whisker Plots of Regression Results
Description: Quick and easy dot-and-whisker plots of regression results.
Author: Frederick Solt [aut],
Yue Hu [aut, cre],
Oliver Keyes [ctb],
Ben Bolker [ctb],
Stefan Müller [ctb]
Maintainer: Yue Hu <yue-hu-1@uiowa.edu>
Diff between dotwhisker versions 0.3.0 dated 2017-06-27 and 0.4.0 dated 2018-04-14
dotwhisker-0.3.0/dotwhisker/vignettes/vignette_dwplot.bib |only dotwhisker-0.4.0/dotwhisker/DESCRIPTION | 15 dotwhisker-0.4.0/dotwhisker/MD5 | 55 dotwhisker-0.4.0/dotwhisker/NAMESPACE | 81 dotwhisker-0.4.0/dotwhisker/NEWS.md | 132 dotwhisker-0.4.0/dotwhisker/R/add_brackets.R | 263 - dotwhisker-0.4.0/dotwhisker/R/by_2sd.R | 112 dotwhisker-0.4.0/dotwhisker/R/dwplot.R | 573 +-- dotwhisker-0.4.0/dotwhisker/R/relabel_predictors.R | 118 dotwhisker-0.4.0/dotwhisker/R/relabel_y_axis.R | 28 dotwhisker-0.4.0/dotwhisker/R/secret_weapon.R | 137 dotwhisker-0.4.0/dotwhisker/R/small_multiple.R | 332 +- dotwhisker-0.4.0/dotwhisker/build/vignette.rds |binary dotwhisker-0.4.0/dotwhisker/inst/doc/dotwhisker-vignette.R | 560 +-- dotwhisker-0.4.0/dotwhisker/inst/doc/dotwhisker-vignette.Rmd | 815 ++--- dotwhisker-0.4.0/dotwhisker/inst/doc/dotwhisker-vignette.html | 956 +++--- dotwhisker-0.4.0/dotwhisker/inst/doc/kl2007_examples.R | 1348 ++++---- dotwhisker-0.4.0/dotwhisker/inst/doc/kl2007_examples.Rmd | 1475 ++++----- dotwhisker-0.4.0/dotwhisker/inst/doc/kl2007_examples.html | 1585 +++++----- dotwhisker-0.4.0/dotwhisker/man/add_brackets.Rd | 87 dotwhisker-0.4.0/dotwhisker/man/by_2sd.Rd | 75 dotwhisker-0.4.0/dotwhisker/man/dwplot.Rd | 181 - dotwhisker-0.4.0/dotwhisker/man/relabel_predictors.Rd | 80 dotwhisker-0.4.0/dotwhisker/man/relabel_y_axis.Rd | 34 dotwhisker-0.4.0/dotwhisker/man/secret_weapon.Rd | 93 dotwhisker-0.4.0/dotwhisker/man/small_multiple.Rd | 188 - dotwhisker-0.4.0/dotwhisker/vignettes/dotwhisker-vignette.Rmd | 815 ++--- dotwhisker-0.4.0/dotwhisker/vignettes/kl2007_examples.Rmd | 1475 ++++----- dotwhisker-0.4.0/dotwhisker/vignettes/vignette.bib | 107 29 files changed, 5950 insertions(+), 5770 deletions(-)
Title: Load Census TIGER/Line Shapefiles
Description: Download TIGER/Line shapefiles from the United States Census Bureau
(<https://www.census.gov/geo/maps-data/data/tiger-line.html>) and load into R as 'SpatialDataFrame' or 'sf' objects.
Author: Kyle Walker [aut, cre],
Bob Rudis [ctb]
Maintainer: Kyle Walker <kyle.walker@tcu.edu>
Diff between tigris versions 0.6.2 dated 2018-01-04 and 0.7 dated 2018-04-14
DESCRIPTION | 8 ++++---- MD5 | 8 ++++---- R/enumeration_units.R | 2 +- R/helpers.R | 1 + R/zzz.R | 8 ++++---- 5 files changed, 14 insertions(+), 13 deletions(-)
Title: Historical Tree Ensembles for Longitudinal Data
Description: Historical regression trees are an extension of standard trees,
producing a non-parametric estimate of how the response depends on
all of its prior realizations as well as that of any time-varying predictor
variables. The method applies equally to regularly as well as irregularly
sampled data. The package implements random forest and boosting ensembles
based on historical regression trees, suitable for longitudinal data.
Standard error estimation and Z-score variable importance is also implemented.
Author: Joe Sexton <joesexton0@gmail.com>
Maintainer: Joe Sexton <joesexton0@gmail.com>
Diff between htree versions 0.1.1 dated 2017-04-26 and 1.0.0 dated 2018-04-14
DESCRIPTION | 9 MD5 | 30 NAMESPACE | 6 R/aux_dev.R | 227 +- R/aux_start.R | 27 R/hrf.R | 588 ++++-- R/htb.R | 243 ++ man/hrf.Rd | 229 +- man/htb.Rd | 160 + man/partdep_hrf.Rd | 3 man/predict_hrf.Rd | 113 + man/quantile_hrf.Rd | 28 man/varimp_hrf.Rd | 50 src/helper.c | 1 src/htree.c | 5094 +++++++++++++++++++++++++++++++++++++++++++++++----- src/init.c | 26 16 files changed, 6046 insertions(+), 788 deletions(-)
Title: Ask Yes-No Questions
Description: Asks Yes-No questions with variable or custom responses.
Author: Joe Thorley [aut, cre],
Hadley Wickham [aut]
Maintainer: Joe Thorley <joe@poissonconsulting.ca>
Diff between yesno versions 0.0.2 dated 2017-02-15 and 0.1.0 dated 2018-04-14
DESCRIPTION | 26 +++++----- MD5 | 15 +++--- NAMESPACE | 1 NEWS.md | 8 ++- R/yesno.R | 7 ++ R/yesno2.R |only README.md | 106 ++++++++++++++++++++++++++++++++----------- man/yesno.Rd | 9 ++- man/yesno2.Rd |only tests/testthat/test-yesno2.R |only 10 files changed, 121 insertions(+), 51 deletions(-)
Title: Two One-Sided Tests (TOST) Equivalence Testing
Description: Two one-sided tests (TOST) procedure to test equivalence for t-tests, correlations, differences between proportions, and meta-analyses, including power analysis for t-tests and correlations. Allows you to specify equivalence bounds in raw scale units or in terms of effect sizes. See: Lakens (2017) <doi:10.1177/1948550617697177>.
Author: Daniel Lakens <D.Lakens@tue.nl>
Maintainer: Daniel Lakens <D.Lakens@tue.nl>
Diff between TOSTER versions 0.3.1 dated 2018-04-06 and 0.3.2 dated 2018-04-14
DESCRIPTION | 8 ++++---- MD5 | 16 ++++++++-------- NEWS | 12 +++++++++++- R/powerTOSTone.raw.R | 10 +++++----- R/powerTOSTpaired.raw.R | 8 ++++---- R/powerTOSTtwo.raw.R | 12 ++++++------ inst/doc/IntroductionToTOSTER.html | 4 ++-- man/powerTOSTone.raw.Rd | 2 +- man/powerTOSTtwo.raw.Rd | 4 ++-- 9 files changed, 43 insertions(+), 33 deletions(-)
Title: Serializable Representations
Description: String and binary representations of objects for several formats /
mime types.
Author: Philipp Angerer [aut, cre],
Thomas Kluyver [aut],
Jan Schulz [aut],
abielr [ctb],
Denilson Figueiredo de Sa [ctb],
Jim Hester [ctb],
karldw [ctb],
Carson Sievert [ctb]
Maintainer: Philipp Angerer <phil.angerer@gmail.com>
Diff between repr versions 0.12.0 dated 2017-04-07 and 0.13 dated 2018-04-14
DESCRIPTION | 21 ++-- MD5 | 23 ++--- NAMESPACE | 5 + R/options.r | 6 + R/repr_factor.r |only R/repr_htmlwidget.r | 149 ++++++++++++++++++++++++++++------ R/repr_vector.r | 18 ---- R/utils.r | 5 + man/repr-options.Rd | 5 - man/repr_-times-.factor.Rd |only man/repr_-times-.htmlwidget.Rd | 28 +++++- man/repr_-times-.vector.Rd | 9 -- tests/testthat/test_repr_htmlwidget.r |only tests/testthat/test_vector.r | 13 ++ 14 files changed, 211 insertions(+), 71 deletions(-)
Title: Community Ecology Package
Description: Ordination methods, diversity analysis and other
functions for community and vegetation ecologists.
Author: Jari Oksanen, F. Guillaume Blanchet, Michael Friendly, Roeland Kindt,
Pierre Legendre, Dan McGlinn, Peter R. Minchin, R. B. O'Hara,
Gavin L. Simpson, Peter Solymos, M. Henry H. Stevens, Eduard Szoecs,
Helene Wagner
Maintainer: Jari Oksanen <jari.oksanen@oulu.fi>
Diff between vegan versions 2.4-6 dated 2018-01-24 and 2.5-1 dated 2018-04-14
vegan-2.4-6/vegan/R/ade2vegancca.R |only vegan-2.4-6/vegan/R/as.mlm.R |only vegan-2.4-6/vegan/R/as.mlm.cca.R |only vegan-2.4-6/vegan/R/as.mlm.rda.R |only vegan-2.4-6/vegan/R/oldCapscale.R |only vegan-2.4-6/vegan/man/as.mlm.Rd |only vegan-2.4-6/vegan/man/model.matrix.cca.Rd |only vegan-2.5-1/vegan/DESCRIPTION | 10 vegan-2.5-1/vegan/MD5 | 525 +++++----- vegan-2.5-1/vegan/NAMESPACE | 66 - vegan-2.5-1/vegan/R/CCorA.R | 13 vegan-2.5-1/vegan/R/MDSrotate.R | 12 vegan-2.5-1/vegan/R/RsquareAdj.R | 30 vegan-2.5-1/vegan/R/adipart.default.R | 12 vegan-2.5-1/vegan/R/adonis2.R | 29 vegan-2.5-1/vegan/R/anosim.R | 22 vegan-2.5-1/vegan/R/anova.betadisper.R | 2 vegan-2.5-1/vegan/R/anova.cca.R | 3 vegan-2.5-1/vegan/R/anova.ccabyterm.R | 207 ++-- vegan-2.5-1/vegan/R/anova.ccalist.R | 16 vegan-2.5-1/vegan/R/anova.ccanull.R | 3 vegan-2.5-1/vegan/R/as.hclust.spantree.R | 23 vegan-2.5-1/vegan/R/as.rad.R | 8 vegan-2.5-1/vegan/R/as.ts.permat.R | 8 vegan-2.5-1/vegan/R/avgdist.R |only vegan-2.5-1/vegan/R/betadisper.R | 8 vegan-2.5-1/vegan/R/betadiver.R | 10 vegan-2.5-1/vegan/R/bgdispersal.R | 10 vegan-2.5-1/vegan/R/bioenv.default.R | 26 vegan-2.5-1/vegan/R/biplot.CCorA.R | 35 vegan-2.5-1/vegan/R/capscale.R | 75 - vegan-2.5-1/vegan/R/cca.default.R | 150 --- vegan-2.5-1/vegan/R/cca.formula.R | 51 - vegan-2.5-1/vegan/R/centroids.cca.R | 2 vegan-2.5-1/vegan/R/checkSelect.R | 2 vegan-2.5-1/vegan/R/clamtest.R | 22 vegan-2.5-1/vegan/R/coef.cca.R | 14 vegan-2.5-1/vegan/R/coef.rda.R | 9 vegan-2.5-1/vegan/R/coverscale.R | 14 vegan-2.5-1/vegan/R/dbrda.R | 151 --- vegan-2.5-1/vegan/R/decorana.R | 176 --- vegan-2.5-1/vegan/R/decostand.R | 45 vegan-2.5-1/vegan/R/designdist.R | 48 vegan-2.5-1/vegan/R/distconnected.R | 6 vegan-2.5-1/vegan/R/diversity.R | 12 vegan-2.5-1/vegan/R/downweight.R | 10 vegan-2.5-1/vegan/R/eigenvals.R | 63 - vegan-2.5-1/vegan/R/extractAIC.cca.R | 2 vegan-2.5-1/vegan/R/factorfit.R | 17 vegan-2.5-1/vegan/R/fisherfit.R | 31 vegan-2.5-1/vegan/R/fitted.capscale.R | 21 vegan-2.5-1/vegan/R/fitted.cca.R | 22 vegan-2.5-1/vegan/R/fitted.dbrda.R | 62 - vegan-2.5-1/vegan/R/fitted.rda.R | 15 vegan-2.5-1/vegan/R/goodness.cca.R | 113 +- vegan-2.5-1/vegan/R/goodness.metaMDS.R | 4 vegan-2.5-1/vegan/R/hierParseFormula.R | 2 vegan-2.5-1/vegan/R/hiersimu.default.R | 2 vegan-2.5-1/vegan/R/indpower.R | 4 vegan-2.5-1/vegan/R/inertcomp.R | 71 - 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vegan-2.5-1/vegan/inst/doc/decision-vegan.pdf |binary vegan-2.5-1/vegan/inst/doc/diversity-vegan.R | 10 vegan-2.5-1/vegan/inst/doc/diversity-vegan.Rnw | 28 vegan-2.5-1/vegan/inst/doc/diversity-vegan.pdf |binary vegan-2.5-1/vegan/inst/doc/intro-vegan.Rnw | 6 vegan-2.5-1/vegan/inst/doc/intro-vegan.pdf |binary vegan-2.5-1/vegan/inst/doc/partitioning.pdf |binary vegan-2.5-1/vegan/man/BCI.Rd | 17 vegan-2.5-1/vegan/man/RsquareAdj.Rd | 43 vegan-2.5-1/vegan/man/SSarrhenius.Rd | 34 vegan-2.5-1/vegan/man/add1.cca.Rd | 8 vegan-2.5-1/vegan/man/adonis.Rd | 11 vegan-2.5-1/vegan/man/anosim.Rd | 6 vegan-2.5-1/vegan/man/anova.cca.Rd | 115 +- vegan-2.5-1/vegan/man/avgdist.Rd |only vegan-2.5-1/vegan/man/beals.Rd | 2 vegan-2.5-1/vegan/man/biplot.rda.Rd | 1 vegan-2.5-1/vegan/man/capscale.Rd | 107 +- vegan-2.5-1/vegan/man/cca.Rd | 34 vegan-2.5-1/vegan/man/cca.object.Rd | 469 +++------ vegan-2.5-1/vegan/man/commsim.Rd | 87 - vegan-2.5-1/vegan/man/contribdiv.Rd | 50 - vegan-2.5-1/vegan/man/decorana.Rd | 32 vegan-2.5-1/vegan/man/decostand.Rd | 6 vegan-2.5-1/vegan/man/designdist.Rd | 61 - vegan-2.5-1/vegan/man/deviance.cca.Rd | 4 vegan-2.5-1/vegan/man/dispindmorisita.Rd | 30 vegan-2.5-1/vegan/man/dune.taxon.Rd | 11 vegan-2.5-1/vegan/man/eigenvals.Rd | 31 vegan-2.5-1/vegan/man/envfit.Rd | 4 vegan-2.5-1/vegan/man/fisherfit.Rd | 4 vegan-2.5-1/vegan/man/goodness.cca.Rd | 62 - vegan-2.5-1/vegan/man/humpfit.Rd | 3 vegan-2.5-1/vegan/man/influence.cca.Rd |only vegan-2.5-1/vegan/man/mantel.Rd | 2 vegan-2.5-1/vegan/man/metaMDS.Rd | 2 vegan-2.5-1/vegan/man/mite.Rd | 2 vegan-2.5-1/vegan/man/monoMDS.Rd | 34 vegan-2.5-1/vegan/man/mso.Rd | 2 vegan-2.5-1/vegan/man/multipart.Rd | 3 vegan-2.5-1/vegan/man/nestedtemp.Rd | 22 vegan-2.5-1/vegan/man/ordiArrowTextXY.Rd | 14 vegan-2.5-1/vegan/man/ordihull.Rd | 34 vegan-2.5-1/vegan/man/ordilabel.Rd | 2 vegan-2.5-1/vegan/man/ordiplot.Rd | 54 - vegan-2.5-1/vegan/man/ordiresids.Rd | 33 vegan-2.5-1/vegan/man/ordistep.Rd | 47 vegan-2.5-1/vegan/man/ordisurf.Rd | 22 vegan-2.5-1/vegan/man/ordixyplot.Rd | 27 vegan-2.5-1/vegan/man/pcnm.Rd | 14 vegan-2.5-1/vegan/man/permatfull.Rd | 2 vegan-2.5-1/vegan/man/permustats.Rd | 21 vegan-2.5-1/vegan/man/permutations.Rd | 18 vegan-2.5-1/vegan/man/plot.cca.Rd | 83 + vegan-2.5-1/vegan/man/prc.Rd | 8 vegan-2.5-1/vegan/man/predict.cca.Rd | 90 + vegan-2.5-1/vegan/man/procrustes.Rd | 8 vegan-2.5-1/vegan/man/radfit.Rd | 36 vegan-2.5-1/vegan/man/rarefy.Rd | 12 vegan-2.5-1/vegan/man/raupcrick.Rd | 2 vegan-2.5-1/vegan/man/read.cep.Rd | 12 vegan-2.5-1/vegan/man/renyi.Rd | 28 vegan-2.5-1/vegan/man/reorder.hclust.Rd | 13 vegan-2.5-1/vegan/man/simper.Rd | 5 vegan-2.5-1/vegan/man/sipoo.Rd | 42 vegan-2.5-1/vegan/man/spantree.Rd | 24 vegan-2.5-1/vegan/man/specaccum.Rd | 6 vegan-2.5-1/vegan/man/sppscores.Rd |only vegan-2.5-1/vegan/man/varpart.Rd | 161 +-- vegan-2.5-1/vegan/man/vegan-defunct.Rd | 39 vegan-2.5-1/vegan/man/vegan-deprecated.Rd | 141 -- vegan-2.5-1/vegan/man/vegan-internal.Rd | 18 vegan-2.5-1/vegan/man/vegdist.Rd | 90 + vegan-2.5-1/vegan/man/vegemite.Rd | 92 - vegan-2.5-1/vegan/man/wascores.Rd | 24 vegan-2.5-1/vegan/man/wcmdscale.Rd | 16 vegan-2.5-1/vegan/src/Makevars |only vegan-2.5-1/vegan/src/data2hill.c | 117 ++ vegan-2.5-1/vegan/src/decorana.f | 718 +++++++------- vegan-2.5-1/vegan/src/getF.c |only vegan-2.5-1/vegan/src/goffactor.c | 59 + vegan-2.5-1/vegan/src/init.c | 85 - vegan-2.5-1/vegan/src/monoMDS.f | 109 -- vegan-2.5-1/vegan/src/nestedness.c | 1179 +++++++++++++++++++++--- vegan-2.5-1/vegan/src/stepacross.c | 4 vegan-2.5-1/vegan/src/vegdist.c | 248 ++++- vegan-2.5-1/vegan/tests |only vegan-2.5-1/vegan/vignettes/FAQ-vegan.Rmd | 8 vegan-2.5-1/vegan/vignettes/decision-vegan.Rnw | 85 - vegan-2.5-1/vegan/vignettes/diversity-vegan.Rnw | 28 vegan-2.5-1/vegan/vignettes/intro-vegan.Rnw | 6 270 files changed, 5904 insertions(+), 4785 deletions(-)
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2018-04-13 4.0.1
Title: Estimate Univariate Gaussian or Student's t Mixture
Autoregressive Model
Description: Maximum likelihood estimation of univariate Gaussian Mixture Autoregressive (GMAR),
Student's t Mixture Autoregressive (StMAR) and Gaussian and Student's t Mixture Autoregressive (G-StMAR) models,
quantile residual tests, graphical diagnostics, forecast and simulate from GMAR, StMAR and G-StMAR processes.
Also general linear constraints and restricting autoregressive parameters to be the same for all regimes are supported.
Leena Kalliovirta, Mika Meitz, Pentti Saikkonen (2015) <doi:10.1111/jtsa.12108>,
Leena Kalliovirta (2012) <doi:10.1111/j.1368-423X.2011.00364.x>.
Author: Savi Virolainen [aut, cre]
Maintainer: Savi Virolainen <savi.virolainen@helsinki.fi>
Diff between uGMAR versions 2.0.0 dated 2018-02-26 and 2.0.1 dated 2018-04-14
DESCRIPTION | 6 ++--- MD5 | 14 ++++++------- R/MAINest.R | 46 ++++++++++++++++++++++--------------------- R/forecastGMAR.R | 4 +-- R/quantileResidualTests.R | 6 ++--- build/vignette.rds |binary inst/doc/intro-to-uGMAR.html | 4 +-- man/fitGMAR.Rd | 2 - 8 files changed, 42 insertions(+), 40 deletions(-)
Title: WOE Transformation and Scorecard Builder
Description: Performs all steps in the credit scoring process. This package allows the user to follow all the necessary steps for building an effective scorecard. It provides the user functions for coarse binning of variables, Weights of Evidence (WOE) transformation, variable clustering, custom binning, visualization, and scaling of logistic regression coefficients. The results will generate a scorecard that can be used as an effective credit scoring tool to evaluate risk. For complete details on the credit scoring process, see Siddiqi (2005, ISBN:047175451X).
Author: Thomas Brandenburger [cre],
Eric Stratman [aut],
Riaz Khan [aut],
Allison Lempola [aut]
Maintainer: Thomas Brandenburger <thomas.brandenburger@sdstate.edu>
Diff between Rprofet versions 2.1.0 dated 2018-04-09 and 2.2.0 dated 2018-04-14
DESCRIPTION | 6 +++--- MD5 | 4 ++-- R/Rprofet.R | 25 +++++++++++++++++++++++-- 3 files changed, 28 insertions(+), 7 deletions(-)
Title: Non Metric Space (Approximate) Library
Description: A Non-Metric Space Library ('NMSLIB' <https://github.com/searchivarius/nmslib>) wrapper, which according to the authors "is an efficient cross-platform similarity search library and a toolkit for evaluation of similarity search methods. The goal of the 'NMSLIB' <https://github.com/searchivarius/nmslib> Library is to create an effective and comprehensive toolkit for searching in generic non-metric spaces. Being comprehensive is important, because no single method is likely to be sufficient in all cases. Also note that exact solutions are hardly efficient in high dimensions and/or non-metric spaces. Hence, the main focus is on approximate methods". The wrapper also includes Approximate Kernel k-Nearest-Neighbor functions based on the 'NMSLIB' <https://github.com/searchivarius/nmslib> 'Python' Library.
Author: Lampros Mouselimis [aut, cre],
B. Naidan [cph] (Author of the Non-Metric Space Library (NMSLIB)),
L. Boytsov [cph] (Author of the Non-Metric Space Library (NMSLIB)),
Yu. Malkov [cph] (Author of the Non-Metric Space Library (NMSLIB)),
B. Frederickson [cph] (Author of the Non-Metric Space Library (NMSLIB)),
D. Novak [cph] (Author of the Non-Metric Space Library (NMSLIB))
Maintainer: Lampros Mouselimis <mouselimislampros@gmail.com>
Diff between nmslibR versions 1.0.0 dated 2018-02-27 and 1.0.1 dated 2018-04-14
DESCRIPTION | 10 +++-- MD5 | 16 ++++---- NEWS.md | 5 ++ R/nmslib.R | 37 +++++++++++--------- README.md | 18 +++++++++ inst/doc/the_nmslibR_package.html | 4 +- man/dgCMatrix_2scipy_sparse.Rd | 33 +++++++++--------- src/init.c | 2 - tests/testthat/test-nmslibR_pkg.R | 69 ++++++++++++++++++++------------------ 9 files changed, 116 insertions(+), 78 deletions(-)
Title: Generalized Random Forests (Beta)
Description: A pluggable package for forest-based statistical estimation and inference.
GRF currently provides methods for non-parametric least-squares regression,
quantile regression, and treatment effect estimation (optionally using instrumental
variables). This package is currently in beta, and we expect to make continual
improvements to its performance and usability.
Author: Julie Tibshirani [aut, cre],
Susan Athey [aut],
Stefan Wager [aut],
Rina Friedberg [ctb],
Luke Miner [ctb],
Marvin Wright [ctb]
Maintainer: Julie Tibshirani <jtibs@cs.stanford.edu>
Diff between grf versions 0.9.5 dated 2018-01-09 and 0.9.6 dated 2018-04-14
grf-0.9.5/grf/R/average_effect.R |only grf-0.9.5/grf/man/estimate_average_effect.Rd |only grf-0.9.5/grf/src/AnalysisBindings.cpp |only grf-0.9.5/grf/src/src/splitting/RegularizedRegressionSplittingRule.cpp |only grf-0.9.5/grf/src/src/splitting/RegularizedRegressionSplittingRule.h |only grf-0.9.5/grf/src/src/splitting/factory/RegularizedRegressionSplittingRuleFactory.cpp |only grf-0.9.5/grf/src/src/splitting/factory/RegularizedRegressionSplittingRuleFactory.h |only grf-0.9.5/grf/tests |only grf-0.9.6/grf/DESCRIPTION | 13 grf-0.9.6/grf/MD5 | 203 ++++---- grf-0.9.6/grf/NAMESPACE | 11 grf-0.9.6/grf/R/RcppExports.R | 64 +- grf-0.9.6/grf/R/analysis_tools.R | 43 + grf-0.9.6/grf/R/average_partial_effect.R |only grf-0.9.6/grf/R/average_treatment_effect.R |only grf-0.9.6/grf/R/causal_forest.R | 162 ++++-- grf-0.9.6/grf/R/causal_tuning.R |only grf-0.9.6/grf/R/custom_forest.R | 38 - grf-0.9.6/grf/R/input_utilities.R | 61 ++ grf-0.9.6/grf/R/instrumental_forest.R | 72 +-- grf-0.9.6/grf/R/quantile_forest.R | 42 - grf-0.9.6/grf/R/regression_forest.R | 148 ++++-- grf-0.9.6/grf/R/regression_tuning.R |only grf-0.9.6/grf/R/tuning_utilities.R |only grf-0.9.6/grf/man/average_partial_effect.Rd |only grf-0.9.6/grf/man/average_treatment_effect.Rd |only grf-0.9.6/grf/man/causal_forest.Rd | 30 + grf-0.9.6/grf/man/custom_forest.Rd | 13 grf-0.9.6/grf/man/get_sample_weights.Rd |only grf-0.9.6/grf/man/grf.Rd |only grf-0.9.6/grf/man/instrumental_forest.Rd | 20 grf-0.9.6/grf/man/predict.regression_forest.Rd | 11 grf-0.9.6/grf/man/quantile_forest.Rd | 15 grf-0.9.6/grf/man/regression_forest.Rd | 28 - grf-0.9.6/grf/man/tune_causal_forest.Rd |only grf-0.9.6/grf/man/tune_regression_forest.Rd |only grf-0.9.6/grf/src/AnalysisToolsBindings.cpp |only grf-0.9.6/grf/src/CustomForestBindings.cpp | 28 - grf-0.9.6/grf/src/InstrumentalForestBindings.cpp | 50 -- grf-0.9.6/grf/src/QuantileForestBindings.cpp | 31 - grf-0.9.6/grf/src/RcppExports.cpp | 209 +++++--- grf-0.9.6/grf/src/RcppUtilities.cpp | 55 +- grf-0.9.6/grf/src/RcppUtilities.h | 16 grf-0.9.6/grf/src/RegressionForestBindings.cpp | 83 ++- grf-0.9.6/grf/src/src/commons/Data.cpp | 61 +- grf-0.9.6/grf/src/src/commons/Data.h | 8 grf-0.9.6/grf/src/src/commons/DefaultData.cpp | 8 grf-0.9.6/grf/src/src/commons/DefaultData.h | 1 grf-0.9.6/grf/src/src/commons/Observations.cpp | 11 grf-0.9.6/grf/src/src/commons/Observations.h | 10 grf-0.9.6/grf/src/src/commons/SparseData.cpp | 6 grf-0.9.6/grf/src/src/commons/SparseData.h | 1 grf-0.9.6/grf/src/src/commons/globals.h | 30 - grf-0.9.6/grf/src/src/forest/Forest.cpp | 19 grf-0.9.6/grf/src/src/forest/Forest.h | 16 grf-0.9.6/grf/src/src/forest/ForestOptions.cpp | 73 ++- grf-0.9.6/grf/src/src/forest/ForestOptions.h | 36 + grf-0.9.6/grf/src/src/forest/ForestPredictor.cpp | 98 ---- grf-0.9.6/grf/src/src/forest/ForestPredictor.h | 28 - grf-0.9.6/grf/src/src/forest/ForestPredictors.cpp | 19 grf-0.9.6/grf/src/src/forest/ForestPredictors.h | 9 grf-0.9.6/grf/src/src/forest/ForestTrainer.cpp | 223 ++------- grf-0.9.6/grf/src/src/forest/ForestTrainer.h | 67 -- grf-0.9.6/grf/src/src/forest/ForestTrainers.cpp | 73 --- grf-0.9.6/grf/src/src/forest/ForestTrainers.h | 38 - grf-0.9.6/grf/src/src/prediction/InstrumentalPredictionStrategy.cpp | 111 +++- grf-0.9.6/grf/src/src/prediction/InstrumentalPredictionStrategy.h | 6 grf-0.9.6/grf/src/src/prediction/LocalLinearPredictionStrategy.cpp |only grf-0.9.6/grf/src/src/prediction/LocalLinearPredictionStrategy.h |only grf-0.9.6/grf/src/src/prediction/OptimizedPredictionStrategy.h | 6 grf-0.9.6/grf/src/src/prediction/Prediction.cpp | 35 + grf-0.9.6/grf/src/src/prediction/Prediction.h | 25 - grf-0.9.6/grf/src/src/prediction/PredictionValues.cpp | 16 grf-0.9.6/grf/src/src/prediction/PredictionValues.h | 13 grf-0.9.6/grf/src/src/prediction/QuantilePredictionStrategy.cpp | 5 grf-0.9.6/grf/src/src/prediction/RegressionPredictionStrategy.cpp | 29 + grf-0.9.6/grf/src/src/prediction/RegressionPredictionStrategy.h | 6 grf-0.9.6/grf/src/src/prediction/collector/DefaultPredictionCollector.cpp | 60 -- grf-0.9.6/grf/src/src/prediction/collector/DefaultPredictionCollector.h | 16 grf-0.9.6/grf/src/src/prediction/collector/OptimizedPredictionCollector.cpp | 31 - grf-0.9.6/grf/src/src/prediction/collector/OptimizedPredictionCollector.h | 7 grf-0.9.6/grf/src/src/prediction/collector/PredictionCollector.h | 3 grf-0.9.6/grf/src/src/prediction/collector/SampleWeightComputer.cpp |only grf-0.9.6/grf/src/src/prediction/collector/SampleWeightComputer.h |only grf-0.9.6/grf/src/src/prediction/collector/TreeTraverser.cpp |only grf-0.9.6/grf/src/src/prediction/collector/TreeTraverser.h |only grf-0.9.6/grf/src/src/relabeling/InstrumentalRelabelingStrategy.cpp | 15 grf-0.9.6/grf/src/src/relabeling/InstrumentalRelabelingStrategy.h | 4 grf-0.9.6/grf/src/src/sampling/RandomSampler.cpp | 239 +++------- grf-0.9.6/grf/src/src/sampling/RandomSampler.h | 156 +++--- grf-0.9.6/grf/src/src/sampling/SamplingOptions.cpp | 47 + grf-0.9.6/grf/src/src/sampling/SamplingOptions.h | 34 - grf-0.9.6/grf/src/src/serialization/TreeSerializer.cpp | 8 grf-0.9.6/grf/src/src/splitting/InstrumentalSplittingRule.cpp |only grf-0.9.6/grf/src/src/splitting/InstrumentalSplittingRule.h |only grf-0.9.6/grf/src/src/splitting/ProbabilitySplittingRule.cpp | 79 ++- grf-0.9.6/grf/src/src/splitting/ProbabilitySplittingRule.h | 23 grf-0.9.6/grf/src/src/splitting/RegressionSplittingRule.cpp | 81 ++- grf-0.9.6/grf/src/src/splitting/RegressionSplittingRule.h | 46 + grf-0.9.6/grf/src/src/splitting/SplittingRule.h | 2 grf-0.9.6/grf/src/src/splitting/factory/InstrumentalSplittingRuleFactory.cpp |only grf-0.9.6/grf/src/src/splitting/factory/InstrumentalSplittingRuleFactory.h |only grf-0.9.6/grf/src/src/splitting/factory/ProbabilitySplittingRuleFactory.cpp | 14 grf-0.9.6/grf/src/src/splitting/factory/ProbabilitySplittingRuleFactory.h | 24 - grf-0.9.6/grf/src/src/splitting/factory/RegressionSplittingRuleFactory.cpp | 11 grf-0.9.6/grf/src/src/splitting/factory/RegressionSplittingRuleFactory.h | 24 - grf-0.9.6/grf/src/src/splitting/factory/SplittingRuleFactory.h | 8 grf-0.9.6/grf/src/src/tree/Tree.cpp | 103 +++- grf-0.9.6/grf/src/src/tree/Tree.h | 80 +-- grf-0.9.6/grf/src/src/tree/TreeOptions.cpp | 40 - grf-0.9.6/grf/src/src/tree/TreeOptions.h | 42 - grf-0.9.6/grf/src/src/tree/TreeTrainer.cpp | 85 +-- grf-0.9.6/grf/src/src/tree/TreeTrainer.h | 26 - 113 files changed, 2113 insertions(+), 1728 deletions(-)
Title: Binary Classification via GMDH-Type Neural Network Algorithm
Description: Performs binary classification via Group Method of Data Handling (GMDH) - type neural network algorithm. There exist two main algorithms available in GMDH() and dceGMDH() functions. GMDH() performs classification via GMDH algorithm for a binary response and returns important variables. dceGMDH() performs classification via diverse classifiers ensemble based on GMDH (dce-GMDH) algorithm. Also, the package produces a well-formatted table of descriptives for a binary response. Moreover, it produces confusion matrix and related statistics and scatter plot (2D and 3D) with classification labels of binary classes to assess the prediction performance. All 'GMDH2' functions are designed for a binary response. See Dag O. and Yozgatligil C. (2016, ISSN:2073-4859) and Kondo T. and Ueno J. (2016, ISSN:1349-4198) for the details of GMDH algorithms.
Author: Osman Dag [aut, cre], Erdem Karabulut [aut], Reha Alpar [aut]
Maintainer: Osman Dag <osman.dag@hacettepe.edu.tr>
Diff between GMDH2 versions 1.0 dated 2018-04-06 and 1.1 dated 2018-04-14
DESCRIPTION | 10 +++++----- MD5 | 20 ++++++++++++-------- NAMESPACE | 3 ++- R/GMDH.R |only R/Table.R | 2 +- R/confMat.R | 13 +++++++++++-- R/dceGMDH.R | 14 +++++++------- R/predict.GMDH.R |only man/GMDH.Rd |only man/GMDH2.Rd | 2 +- man/Table.Rd | 6 +++--- man/dceGMDH.Rd | 12 ++++++------ man/predict.GMDH.Rd |only 13 files changed, 48 insertions(+), 34 deletions(-)
Title: Summarize CRAN Check Results in the Terminal
Description: The CRAN check results in your R terminal.
Author: Francois Michonneau [aut, cre],
Ben Bolker [ctb]
Maintainer: Francois Michonneau <francois.michonneau@gmail.com>
Diff between foghorn versions 1.0.1 dated 2018-02-28 and 1.0.2 dated 2018-04-14
DESCRIPTION | 6 +-- LICENSE | 2 - MD5 | 23 ++++++----- NEWS.md | 32 ++++++++++++---- R/cran_files.R | 2 - R/cran_queue.R | 20 ++++++---- README.md | 80 ++++++++++++++++++++++------------------- build/vignette.rds |binary inst/doc/quick_start.html | 63 ++++++++++++++------------------ man/cran_incoming.Rd | 8 +++- man/figures |only tests/testthat.R | 3 - tests/testthat/test-incoming.R | 8 ++++ 13 files changed, 141 insertions(+), 106 deletions(-)
Title: Analysis of Scientific Evidence Using Bayesian and Likelihood
Methods
Description: Bayesian (and some likelihoodist) functions as alternatives to hypothesis-testing functions in R base using a user interface patterned after those of R's hypothesis testing functions. See McElreath (2016, ISBN: 978-1-4822-5344-3), Gelman and Hill (2007, ISBN: 0-521-68689-X) (new edition in preparation) and Albert (2009, ISBN: 978-0-387-71384-7) for good introductions to Bayesian analysis and Pawitan (2002, ISBN: 0-19-850765-8) for the Likelihood approach. The functions in the package also make extensive use of graphical displays for data exploration and model comparison.
Author: Robert van Hulst
Maintainer: Robert van Hulst <rvhulst@ubishops.ca>
Diff between evidence versions 0.8.8 dated 2018-03-02 and 0.8.9 dated 2018-04-14
DESCRIPTION | 13 +++++++------ MD5 | 11 ++++++----- NAMESPACE | 4 +++- NEWS.md |only R/looicplot.R | 34 +++++++++++++++++++--------------- man/evidence-package.Rd | 4 ++-- man/looicplot.Rd | 11 ++++++----- 7 files changed, 43 insertions(+), 34 deletions(-)
Title: Regularized Greedy Forest
Description: Regularized Greedy Forest wrapper of the 'Regularized Greedy Forest' <https://github.com/fukatani/rgf_python> 'python' package, which also includes a Multi-core implementation (FastRGF) <https://github.com/baidu/fast_rgf>.
Author: Lampros Mouselimis [aut, cre],
Ryosuke Fukatani [cph] (Author of the python wrapper of the
'Regularized Greedy Forest' machine learning algorithm),
Tong Zhang [cph] (Author of the 'Regularized Greedy Forest' and of the
Multi-core implementation of Regularized Greedy Forest machine
learning algorithm),
Rie Johnson [cph] (Author of the 'Regularized Greedy Forest' machine
learning algorithm)
Maintainer: Lampros Mouselimis <mouselimislampros@gmail.com>
Diff between RGF versions 1.0.1 dated 2018-02-26 and 1.0.2 dated 2018-04-14
DESCRIPTION | 8 +- MD5 | 16 ++-- NEWS.md | 5 + R/utils.R | 38 +++++----- README.md | 1 inst/doc/the_RGF_package.html | 4 - man/RGF_Classifier.Rd | 2 man/dgCMatrix_2scipy_sparse.Rd | 35 +++++---- tests/testthat/test_package.R | 152 +++++++++++++++++++++-------------------- 9 files changed, 141 insertions(+), 120 deletions(-)
Title: Mixed-Effect Models, Particularly Spatial Models
Description: Inference in mixed-effect models, including generalized linear mixed models with spatial correlations and models with non-Gaussian random effects (e.g., Beta-Binomial). Variation in residual variance (heteroscedasticity) can itself be represented by a generalized linear mixed model. Various approximations of likelihood or restricted likelihood are implemented, in particular h-likelihood (Lee and Nelder 2001 <doi:10.1093/biomet/88.4.987>) and Laplace approximation.
Author: François Rousset [aut, cre, cph],
Jean-Baptiste Ferdy [aut, cph],
Alexandre Courtiol [aut],
GSL authors [ctb] (src/gsl_bessel.*)
Maintainer: François Rousset <francois.rousset@umontpellier.fr>
Diff between spaMM versions 2.4.0 dated 2018-04-05 and 2.4.8 dated 2018-04-14
DESCRIPTION | 8 +++---- MD5 | 44 +++++++++++++++++++-------------------- R/HLCor_body.R | 19 ++++++++-------- R/HLFactorList.R | 30 +++++++++++++++++++------- R/HLfit_body.R | 16 +++++++------- R/HLframes.R | 11 ++++----- R/MakeCovEst.R | 1 R/cov_new_fix.R | 6 ++--- R/negbin.R | 2 - R/precision_internals.R | 15 ++++++++++++- R/predict.R | 25 ++++++++++++++++------ R/preprocess.R | 45 ++++++++++++++++++++++------------------ R/simulate.HL.R | 2 - R/spaMM_boot.R | 2 - R/summary.HL.R | 2 - inst/NEWS.Rd | 15 +++++++++++++ man/CauchyCorr.Rd | 4 +-- man/corrHLfit.Rd | 2 - man/covStruct.Rd | 18 ++++++++++++++-- man/fitme.Rd | 2 - man/options.Rd | 2 - tests/testthat/test-spaMM.R | 4 +++ tests/testthat/test-truncated.R | 1 23 files changed, 177 insertions(+), 99 deletions(-)
Title: Case Influence in Structural Equation Models
Description: A set of tools for evaluating several measures of case influence for structural equation models.
Author: Massimiliano Pastore & Gianmarco Altoe'
Maintainer: Massimiliano Pastore <massimiliano.pastore@unipd.it>
Diff between influence.SEM versions 2.1 dated 2017-04-13 and 2.2 dated 2018-04-14
DESCRIPTION | 8 +++--- MD5 | 20 ++++++++-------- NEWS | 8 ++++++ R/Deltachi.R | 15 +++++++----- R/Likedist.R | 13 +++++----- R/fitinfluence.R | 62 +++++++++++++++++++++++++++++++++------------------- R/genCookDist.R | 14 +++++------ R/parinfluence.R | 42 ++++++++++++++++------------------- man/Deltachi.Rd | 6 ++--- man/fitinfluence.Rd | 14 +++++------ man/parinfluence.Rd | 2 - 11 files changed, 116 insertions(+), 88 deletions(-)
Title: Rubik's Cube Solving
Description: Functions for visualizing, animating, solving and
analyzing the Rubik's cube. Includes data structures for
solvable and unsolvable cubes, random moves and random
state scrambles and cubes, 3D displays and animations
using 'OpenGL', patterned cube generation, and lightweight
solvers. See Rokicki, T. (2008) <arXiv:0803.3435> for the
Kociemba solver.
Author: Alec Stephenson.
Maintainer: Alec Stephenson <alec_stephenson@hotmail.com>
Diff between cubing versions 1.0-3 dated 2018-03-24 and 1.0-4 dated 2018-04-14
DESCRIPTION | 8 ++++---- MD5 | 37 +++++++++++++++++++------------------ NAMESPACE | 2 +- build/vignette.rds |binary inst/doc/cubingintro.Rnw | 20 ++++++++++---------- inst/doc/cubingintro.pdf |binary man/composition.Rd | 6 ++---- man/cubieCube.Rd | 13 +++++++------ man/cycle.Rd | 2 +- man/getMovesCube.Rd | 9 ++++----- man/getMovesPattern.Rd | 3 ++- man/move.Rd | 20 +++++++++++--------- man/rotate.Rd | 15 ++++++++------- man/scramble.Rd | 6 +++--- man/solver.Rd | 6 +++--- man/stickerCube.Rd | 4 ++-- src/cubing_init.c | 9 ++------- src/header.h |only src/kociemba.c | 32 +------------------------------- vignettes/cubingintro.Rnw | 20 ++++++++++---------- 20 files changed, 90 insertions(+), 122 deletions(-)
Title: Censored Linear Mixture Regression Models
Description: Fit censored linear regression models where the random errors follow a finite mixture of Scale Mixture Normal distributions.
Fit censored linear models of finite mixture multivariate Student-t and Normal distributions.
Fit censored mixture regression models based on scale mixture of normal distributions.
Author: Luis Benites Sanchez[cre, aut], Victor Hugo Lachos[cre, aut],
Edgar J. Lopez Moreno[ctb]
Maintainer: Luis Benites Sanchez <lbenitesanchez@gmail.com>
Diff between CensMixReg versions 3.0 dated 2017-07-26 and 3.1 dated 2018-04-14
CensMixReg-3.0/CensMixReg/data/concentration.txt.gz |only CensMixReg-3.0/CensMixReg/data/wage.rates.txt.gz |only CensMixReg-3.1/CensMixReg/DESCRIPTION | 8 CensMixReg-3.1/CensMixReg/MD5 | 18 +- CensMixReg-3.1/CensMixReg/NAMESPACE | 3 CensMixReg-3.1/CensMixReg/R/algEM.fmr.smn.cr.R | 173 ++++++++++---------- CensMixReg-3.1/CensMixReg/R/fmr.smn.cr.R | 2 CensMixReg-3.1/CensMixReg/R/functions.fm.smn.cr.R | 2 CensMixReg-3.1/CensMixReg/R/functions.fmr.smn.cr.R | 115 ++++++------- CensMixReg-3.1/CensMixReg/data/concentration.txt |only CensMixReg-3.1/CensMixReg/data/wage.rates.txt |only CensMixReg-3.1/CensMixReg/man/wage.rates.Rd | 38 +++- 12 files changed, 196 insertions(+), 163 deletions(-)