Fri, 24 May 2019

Package trialr updated to version 0.1.1 with previous version 0.1.0 dated 2019-04-21

Title: Clinical Trial Designs in 'RStan'
Description: A showcase of Bayesian clinical trial designs, implemented in 'RStan' and R, including the Continual Reassessment Method (CRM) and EffTox. Given the emphasis on flexibility in Bayesian analysis, the implementations in a common language and style may serve as a cookbook to encourage the use of Bayesian methods in trials. Compiled 'RStan' models are installed, alongside helper classes and functions to work with models. There is a preponderance of early phase trial designs because this is where Bayesian methods are used most. If there is a published Bayesian design you want implemented in 'Stan', get in touch.
Author: Kristian Brock [aut, cre] (<https://orcid.org/0000-0002-3921-0166>), Trustees of Columbia University [cph]
Maintainer: Kristian Brock <kristian.brock@gmail.com>

Diff between trialr versions 0.1.0 dated 2019-04-21 and 0.1.1 dated 2019-05-24

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More information about trialr at CRAN
Permanent link

Package Rfast updated to version 1.9.4 with previous version 1.9.3 dated 2019-03-04

Title: A Collection of Efficient and Extremely Fast R Functions
Description: A collection of fast (utility) functions for data analysis. Column- and row- wise means, medians, variances, minimums, maximums, many t, F and G-square tests, many regressions (normal, logistic, Poisson), are some of the many fast functions. Reference: Tsagris M, Papadakis M. (2018). Taking R to its limits: 70+ tips. PeerJ Preprints 6:e26605v1 <doi:10.7287/peerj.preprints.26605v1>.
Author: Manos Papadakis, Michail Tsagris, Marios Dimitriadis, Stefanos Fafalios, Ioannis Tsamardinos, Matteo Fasiolo, Giorgos Borboudakis, John Burkardt, Changliang Zou, Kleanthi Lakiotaki and Christina Chatzipantsiou.
Maintainer: Manos Papadakis <rfastofficial@gmail.com>

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 Rfast-1.9.4/Rfast/R/bc.R                      |    1 
 Rfast-1.9.4/Rfast/R/bcdcor.R                  |    3 
 Rfast-1.9.4/Rfast/R/beta.mle.R                |    1 
 Rfast-1.9.4/Rfast/R/betabinom.mle.R           |    1 
 Rfast-1.9.4/Rfast/R/betageom.mle.R            |    1 
 Rfast-1.9.4/Rfast/R/betaprime.mle.R           |    1 
 Rfast-1.9.4/Rfast/R/bic.corfsreg.R            |   18 
 Rfast-1.9.4/Rfast/R/bic.fs.reg.R              |    1 
 Rfast-1.9.4/Rfast/R/binary_search.R           |    3 
 Rfast-1.9.4/Rfast/R/binom.mle.R               |    1 
 Rfast-1.9.4/Rfast/R/block.anova.R             |    5 
 Rfast-1.9.4/Rfast/R/block.anovas.R            |    1 
 Rfast-1.9.4/Rfast/R/boot.ttest2.R             |    1 
 Rfast-1.9.4/Rfast/R/borel.mle.R               |    1 
 Rfast-1.9.4/Rfast/R/bs.reg.R                  |    2 
 Rfast-1.9.4/Rfast/R/btmprobs.R                |    1 
 Rfast-1.9.4/Rfast/R/cat.goftests.R            |    2 
 Rfast-1.9.4/Rfast/R/cauchy.mle.R              |    1 
 Rfast-1.9.4/Rfast/R/check_data.R              |    1 
 Rfast-1.9.4/Rfast/R/chi2Test.R                |    2 
 Rfast-1.9.4/Rfast/R/chi2Test_univariate.R     |    2 
 Rfast-1.9.4/Rfast/R/chi2tests.R               |    2 
 Rfast-1.9.4/Rfast/R/chisq.mle.R               |    1 
 Rfast-1.9.4/Rfast/R/cholesky.R                |    2 
 Rfast-1.9.4/Rfast/R/circlin.cor.R             |    1 
 Rfast-1.9.4/Rfast/R/col.coxpoisrat.R          |    1 
 Rfast-1.9.4/Rfast/R/col.yule.R                |    1 
 Rfast-1.9.4/Rfast/R/colanovas.R               |    1 
 Rfast-1.9.4/Rfast/R/colar1.R                  |    1 
 Rfast-1.9.4/Rfast/R/colaucs.R                 |    2 
 Rfast-1.9.4/Rfast/R/colcvs.R                  |    1 
 Rfast-1.9.4/Rfast/R/coldiffs.R                |    2 
 Rfast-1.9.4/Rfast/R/colexp2.mle.R             |    1 
 Rfast-1.9.4/Rfast/R/colexpmle.R               |    1 
 Rfast-1.9.4/Rfast/R/colgammamle.R             |    1 
 Rfast-1.9.4/Rfast/R/colgeom.mle.R             |    1 
 Rfast-1.9.4/Rfast/R/colhameans.R              |    1 
 Rfast-1.9.4/Rfast/R/colinvgauss.mle.R         |    1 
 Rfast-1.9.4/Rfast/R/colkurtosis.R             |    1 
 Rfast-1.9.4/Rfast/R/collaplace.mle.R          |    1 
 Rfast-1.9.4/Rfast/R/collindley.mle.R          |    1 
 Rfast-1.9.4/Rfast/R/colmaxboltz.mle.R         |    2 
 Rfast-1.9.4/Rfast/R/colmeans.R                |    2 
 Rfast-1.9.4/Rfast/R/colnormal.mle.R           |    1 
 Rfast-1.9.4/Rfast/R/colnormlog.mle.R          |    2 
 Rfast-1.9.4/Rfast/R/colpareto.mle.R           |    1 
 Rfast-1.9.4/Rfast/R/colpois.tests.R           |    1 
 Rfast-1.9.4/Rfast/R/colpoisdisp.tests.R       |    1 
 Rfast-1.9.4/Rfast/R/colpoisson.anovas.R       |    1 
 Rfast-1.9.4/Rfast/R/colpoisson.mle.R          |    1 
 Rfast-1.9.4/Rfast/R/colquasipoisson.anovas.R  |    6 
 Rfast-1.9.4/Rfast/R/colrange.R                |    3 
 Rfast-1.9.4/Rfast/R/colrayleigh.mle.R         |    1 
 Rfast-1.9.4/Rfast/R/colrint.regbx.R           |    1 
 Rfast-1.9.4/Rfast/R/colrow.value.R            |    2 
 Rfast-1.9.4/Rfast/R/colskewness.R             |   11 
 Rfast-1.9.4/Rfast/R/colsums.R                 |    2 
 Rfast-1.9.4/Rfast/R/colvarcomps.mle.R         |    1 
 Rfast-1.9.4/Rfast/R/colvarcomps.mom.R         |    1 
 Rfast-1.9.4/Rfast/R/colvm.mle.R               |    1 
 Rfast-1.9.4/Rfast/R/colwatsons.R              |    3 
 Rfast-1.9.4/Rfast/R/colweibull.mle.R          |    1 
 Rfast-1.9.4/Rfast/R/cor.fbed.R                |    5 
 Rfast-1.9.4/Rfast/R/cor.fsreg.R               |   13 
 Rfast-1.9.4/Rfast/R/cora.R                    |    1 
 Rfast-1.9.4/Rfast/R/corpairs.R                |    1 
 Rfast-1.9.4/Rfast/R/correls.R                 |    1 
 Rfast-1.9.4/Rfast/R/count_value.R             |   20 
 Rfast-1.9.4/Rfast/R/cova.R                    |    1 
 Rfast-1.9.4/Rfast/R/cox.poisrat.R             |    1 
 Rfast-1.9.4/Rfast/R/cqtest.R                  |    5 
 Rfast-1.9.4/Rfast/R/cqtests.R                 |    1 
 Rfast-1.9.4/Rfast/R/ct.mle.R                  |    1 
 Rfast-1.9.4/Rfast/R/cumulative.R              |only
 Rfast-1.9.4/Rfast/R/data.frame.to_matrix.R    |    2 
 Rfast-1.9.4/Rfast/R/dcor.R                    |    2 
 Rfast-1.9.4/Rfast/R/dcor.ttest.R              |    1 
 Rfast-1.9.4/Rfast/R/dcov.R                    |    2 
 Rfast-1.9.4/Rfast/R/design_matrix.R           |    2 
 Rfast-1.9.4/Rfast/R/diri.nr2.R                |    9 
 Rfast-1.9.4/Rfast/R/dirimultinom.mle.R        |    1 
 Rfast-1.9.4/Rfast/R/dirknn.R                  |    1 
 Rfast-1.9.4/Rfast/R/dirknn.cv.R               |    1 
 Rfast-1.9.4/Rfast/R/dista.R                   |    2 
 Rfast-1.9.4/Rfast/R/dmvnorm.R                 |    1 
 Rfast-1.9.4/Rfast/R/dmvt.R                    |    1 
 Rfast-1.9.4/Rfast/R/dvar.R                    |    2 
 Rfast-1.9.4/Rfast/R/eachcol.apply.R           |    2 
 Rfast-1.9.4/Rfast/R/eachrow.R                 |    2 
 Rfast-1.9.4/Rfast/R/edist.R                   |    6 
 Rfast-1.9.4/Rfast/R/eel.test1.R               |    1 
 Rfast-1.9.4/Rfast/R/eel.test2.R               |    1 
 Rfast-1.9.4/Rfast/R/eigen.sym.R               |    1 
 Rfast-1.9.4/Rfast/R/el.test1.R                |    1 
 Rfast-1.9.4/Rfast/R/el.test2.R                |    1 
 Rfast-1.9.4/Rfast/R/env.copy.R                |    2 
 Rfast-1.9.4/Rfast/R/exact.ttest2.R            |    1 
 Rfast-1.9.4/Rfast/R/exp2.mle.R                |    1 
 Rfast-1.9.4/Rfast/R/expmle.R                  |    1 
 Rfast-1.9.4/Rfast/R/expregs.R                 |    1 
 Rfast-1.9.4/Rfast/R/fish.kent.R               |    1 
 Rfast-1.9.4/Rfast/R/floyd.R                   |    2 
 Rfast-1.9.4/Rfast/R/foldnorm.mle.R            |    1 
 Rfast-1.9.4/Rfast/R/frequency.R               |only
 Rfast-1.9.4/Rfast/R/fs.reg.R                  |    2 
 Rfast-1.9.4/Rfast/R/ftest.R                   |    5 
 Rfast-1.9.4/Rfast/R/ftests.R                  |    1 
 Rfast-1.9.4/Rfast/R/g2.R                      |only
 Rfast-1.9.4/Rfast/R/gamma.R                   |only
 Rfast-1.9.4/Rfast/R/gammacon.R                |    1 
 Rfast-1.9.4/Rfast/R/gammamle.R                |    1 
 Rfast-1.9.4/Rfast/R/gammanb.R                 |    1 
 Rfast-1.9.4/Rfast/R/gammanb.pred.R            |    1 
 Rfast-1.9.4/Rfast/R/gammareg.R                |    1 
 Rfast-1.9.4/Rfast/R/gammaregs.R               |    1 
 Rfast-1.9.4/Rfast/R/gaussian.nb.R             |    1 
 Rfast-1.9.4/Rfast/R/gaussiannb.pred.R         |    1 
 Rfast-1.9.4/Rfast/R/gchi2Test.R               |    1 
 Rfast-1.9.4/Rfast/R/geom.anova.R              |    5 
 Rfast-1.9.4/Rfast/R/geom.anovas.R             |    1 
 Rfast-1.9.4/Rfast/R/geom.mle.R                |    1 
 Rfast-1.9.4/Rfast/R/geom.nb.R                 |    1 
 Rfast-1.9.4/Rfast/R/geom.regs.R               |    1 
 Rfast-1.9.4/Rfast/R/geomnb.pred.R             |    1 
 Rfast-1.9.4/Rfast/R/ginis.R                   |    5 
 Rfast-1.9.4/Rfast/R/glm_logistic.R            |    1 
 Rfast-1.9.4/Rfast/R/glm_poisson.R             |    1 
 Rfast-1.9.4/Rfast/R/group.R                   |   54 +
 Rfast-1.9.4/Rfast/R/group.med.R               |    2 
 Rfast-1.9.4/Rfast/R/groupcorrels.R            |    1 
 Rfast-1.9.4/Rfast/R/gumbel.mle.R              |    1 
 Rfast-1.9.4/Rfast/R/halfnorm.mle.R            |    1 
 Rfast-1.9.4/Rfast/R/hd.eigen.R                |    1 
 Rfast-1.9.4/Rfast/R/hsecant01.mle.R           |    1 
 Rfast-1.9.4/Rfast/R/iag.mle.R                 |    1 
 Rfast-1.9.4/Rfast/R/ibeta.mle.R               |    1 
 Rfast-1.9.4/Rfast/R/invdir.mle.R              |    1 
 Rfast-1.9.4/Rfast/R/invgauss.mle.R            |    1 
 Rfast-1.9.4/Rfast/R/invgauss.reg.R            |    1 
 Rfast-1.9.4/Rfast/R/invgauss.regs.R           |    1 
 Rfast-1.9.4/Rfast/R/is.R                      |only
 Rfast-1.9.4/Rfast/R/iterator.R                |    1 
 Rfast-1.9.4/Rfast/R/james.R                   |    1 
 Rfast-1.9.4/Rfast/R/knn.R                     |    2 
 Rfast-1.9.4/Rfast/R/knn.cv.R                  |    2 
 Rfast-1.9.4/Rfast/R/kruskaltest.R             |    3 
 Rfast-1.9.4/Rfast/R/kruskaltests.R            |    1 
 Rfast-1.9.4/Rfast/R/kuiper.R                  |    1 
 Rfast-1.9.4/Rfast/R/kurt.R                    |    1 
 Rfast-1.9.4/Rfast/R/kurt.test2.R              |    1 
 Rfast-1.9.4/Rfast/R/laplace.mle.R             |    1 
 Rfast-1.9.4/Rfast/R/lindley.mle.R             |    1 
 Rfast-1.9.4/Rfast/R/list.ftests.R             |    1 
 Rfast-1.9.4/Rfast/R/lmfit.R                   |    1 
 Rfast-1.9.4/Rfast/R/logcauchy.mle.R           |    1 
 Rfast-1.9.4/Rfast/R/logical.R                 |only
 Rfast-1.9.4/Rfast/R/logistic.cat1.R           |    1 
 Rfast-1.9.4/Rfast/R/logistic.mle.R            |    1 
 Rfast-1.9.4/Rfast/R/logistic_only.R           |    2 
 Rfast-1.9.4/Rfast/R/logitnorm.mle.R           |    1 
 Rfast-1.9.4/Rfast/R/loglogistic.mle.R         |    1 
 Rfast-1.9.4/Rfast/R/lognorm.mle.R             |    1 
 Rfast-1.9.4/Rfast/R/logseries.mle.R           |    1 
 Rfast-1.9.4/Rfast/R/lomax.mle.R               |    1 
 Rfast-1.9.4/Rfast/R/mad2.R                    |   18 
 Rfast-1.9.4/Rfast/R/mahala.R                  |    2 
 Rfast-1.9.4/Rfast/R/match.coefs.R             |    1 
 Rfast-1.9.4/Rfast/R/matrix.R                  |only
 Rfast-1.9.4/Rfast/R/matrnorm.R                |    1 
 Rfast-1.9.4/Rfast/R/maxboltz.mle.R            |    1 
 Rfast-1.9.4/Rfast/R/mcnemar.R                 |    1 
 Rfast-1.9.4/Rfast/R/mcnemars.R                |    1 
 Rfast-1.9.4/Rfast/R/median.R                  |only
 Rfast-1.9.4/Rfast/R/mediandir.R               |    1 
 Rfast-1.9.4/Rfast/R/min_max.R                 |   55 +
 Rfast-1.9.4/Rfast/R/multinom.mle.R            |    1 
 Rfast-1.9.4/Rfast/R/multinom.nb.R             |    2 
 Rfast-1.9.4/Rfast/R/multinom.reg.R            |    1 
 Rfast-1.9.4/Rfast/R/multinom.regs.R           |    1 
 Rfast-1.9.4/Rfast/R/multinomnb.pred.R         |    1 
 Rfast-1.9.4/Rfast/R/multivmf.mle.R            |    1 
 Rfast-1.9.4/Rfast/R/mv.eeltest1.R             |    3 
 Rfast-1.9.4/Rfast/R/mv.eeltest2.R             |    1 
 Rfast-1.9.4/Rfast/R/mvbetas.R                 |    6 
 Rfast-1.9.4/Rfast/R/mvkurtosis.R              |    1 
 Rfast-1.9.4/Rfast/R/mvlnorm.mle.R             |    1 
 Rfast-1.9.4/Rfast/R/mvnorm.mle.R              |    1 
 Rfast-1.9.4/Rfast/R/mvt.mle.R                 |    1 
 Rfast-1.9.4/Rfast/R/negative.R                |    2 
 Rfast-1.9.4/Rfast/R/negbin.mle.R              |    1 
 Rfast-1.9.4/Rfast/R/normal.mle.R              |    1 
 Rfast-1.9.4/Rfast/R/normlog.mle.R             |    1 
 Rfast-1.9.4/Rfast/R/normlog.reg.R             |    1 
 Rfast-1.9.4/Rfast/R/normlog.regs.R            |    2 
 Rfast-1.9.4/Rfast/R/nth.R                     |   18 
 Rfast-1.9.4/Rfast/R/odds.R                    |    1 
 Rfast-1.9.4/Rfast/R/odds.ratio.R              |    1 
 Rfast-1.9.4/Rfast/R/omp.R                     |   16 
 Rfast-1.9.4/Rfast/R/ompr.R                    |    8 
 Rfast-1.9.4/Rfast/R/ordinal.mle.R             |    1 
 Rfast-1.9.4/Rfast/R/pareto.mle.R              |    1 
 Rfast-1.9.4/Rfast/R/pc.skel.R                 |    1 
 Rfast-1.9.4/Rfast/R/percent.ttest.R           |    1 
 Rfast-1.9.4/Rfast/R/percent.ttests.R          |    1 
 Rfast-1.9.4/Rfast/R/permcor.R                 |    1 
 Rfast-1.9.4/Rfast/R/permutation_combination.R |only
 Rfast-1.9.4/Rfast/R/pois.test.R               |    1 
 Rfast-1.9.4/Rfast/R/poisdisp.test.R           |    1 
 Rfast-1.9.4/Rfast/R/poisson.anova.R           |    3 
 Rfast-1.9.4/Rfast/R/poisson.anovas.R          |    1 
 Rfast-1.9.4/Rfast/R/poisson.cat1.R            |    1 
 Rfast-1.9.4/Rfast/R/poisson.mle.R             |    1 
 Rfast-1.9.4/Rfast/R/poisson.nb.R              |    1 
 Rfast-1.9.4/Rfast/R/poisson_only.R            |    2 
 Rfast-1.9.4/Rfast/R/poissonnb.pred.R          |    1 
 Rfast-1.9.4/Rfast/R/poly.cor.R                |    1 
 Rfast-1.9.4/Rfast/R/pooled.cov.R              |    2 
 Rfast-1.9.4/Rfast/R/positive.R                |    2 
 Rfast-1.9.4/Rfast/R/positive.negative.R       |    2 
 Rfast-1.9.4/Rfast/R/prods.R                   |only
 Rfast-1.9.4/Rfast/R/prop.reg.R                |    1 
 Rfast-1.9.4/Rfast/R/prop.regs.R               |    1 
 Rfast-1.9.4/Rfast/R/proptest.R                |    1 
 Rfast-1.9.4/Rfast/R/proptests.R               |    1 
 Rfast-1.9.4/Rfast/R/qpois.reg.R               |    1 
 Rfast-1.9.4/Rfast/R/qpois.regs.R              |    1 
 Rfast-1.9.4/Rfast/R/quasi.poisson_only.R      |    1 
 Rfast-1.9.4/Rfast/R/quasipoisson.anova.R      |    5 
 Rfast-1.9.4/Rfast/R/quasipoisson.anovas.R     |    1 
 Rfast-1.9.4/Rfast/R/racg.R                    |    1 
 Rfast-1.9.4/Rfast/R/rayleigh.mle.R            |    1 
 Rfast-1.9.4/Rfast/R/rbing.R                   |    2 
 Rfast-1.9.4/Rfast/R/rbingham.R                |    1 
 Rfast-1.9.4/Rfast/R/regression.R              |    1 
 Rfast-1.9.4/Rfast/R/rel.risk.R                |    1 
 Rfast-1.9.4/Rfast/R/replicate.R               |only
 Rfast-1.9.4/Rfast/R/rint.mle.R                |    1 
 Rfast-1.9.4/Rfast/R/rint.reg.R                |    1 
 Rfast-1.9.4/Rfast/R/rint.regbx.R              |    1 
 Rfast-1.9.4/Rfast/R/rint.regs.R               |    1 
 Rfast-1.9.4/Rfast/R/rm.anova.R                |    1 
 Rfast-1.9.4/Rfast/R/rm.anovas.R               |    1 
 Rfast-1.9.4/Rfast/R/rm.lines.R                |    1 
 Rfast-1.9.4/Rfast/R/rmdp.R                    |    1 
 Rfast-1.9.4/Rfast/R/rmvlaplace.R              |    1 
 Rfast-1.9.4/Rfast/R/rmvnorm.R                 |    1 
 Rfast-1.9.4/Rfast/R/rmvt.R                    |    1 
 Rfast-1.9.4/Rfast/R/rowcvs.R                  |    1 
 Rfast-1.9.4/Rfast/R/rowhameans.R              |    1 
 Rfast-1.9.4/Rfast/R/rowmeans.R                |    2 
 Rfast-1.9.4/Rfast/R/rowrange.R                |    2 
 Rfast-1.9.4/Rfast/R/rowsums.R                 |    2 
 Rfast-1.9.4/Rfast/R/rvmf.R                    |    1 
 Rfast-1.9.4/Rfast/R/rvonmises.R               |    1 
 Rfast-1.9.4/Rfast/R/score.betaregs.R          |   23 
 Rfast-1.9.4/Rfast/R/score.expregs.R           |    1 
 Rfast-1.9.4/Rfast/R/score.gammaregs.R         |   19 
 Rfast-1.9.4/Rfast/R/score.geomregs.R          |    2 
 Rfast-1.9.4/Rfast/R/score.glms.R              |   14 
 Rfast-1.9.4/Rfast/R/score.invgaussregs.R      |   19 
 Rfast-1.9.4/Rfast/R/score.multinomregs.R      |    1 
 Rfast-1.9.4/Rfast/R/score.negbinregs.R        |   25 
 Rfast-1.9.4/Rfast/R/score.weibregs.R          |   23 
 Rfast-1.9.4/Rfast/R/score.ztpregs.R           |   21 
 Rfast-1.9.4/Rfast/R/sftest.R                  |    1 
 Rfast-1.9.4/Rfast/R/sftests.R                 |    3 
 Rfast-1.9.4/Rfast/R/skew.R                    |    1 
 Rfast-1.9.4/Rfast/R/skew.test2.R              |    1 
 Rfast-1.9.4/Rfast/R/sort_unique.R             |    5 
 Rfast-1.9.4/Rfast/R/sourceR.R                 |    2 
 Rfast-1.9.4/Rfast/R/sourceRd.R                |    2 
 Rfast-1.9.4/Rfast/R/spat.med.R                |    2 
 Rfast-1.9.4/Rfast/R/spatmed.reg.R             |    1 
 Rfast-1.9.4/Rfast/R/spdinv.R                  |    1 
 Rfast-1.9.4/Rfast/R/spml.mle.R                |    1 
 Rfast-1.9.4/Rfast/R/spml.reg.R                |    1 
 Rfast-1.9.4/Rfast/R/spml.regs.R               |    1 
 Rfast-1.9.4/Rfast/R/squareform.R              |    2 
 Rfast-1.9.4/Rfast/R/sscov.R                   |    1 
 Rfast-1.9.4/Rfast/R/standardise.R             |    1 
 Rfast-1.9.4/Rfast/R/system_and_package.R      |only
 Rfast-1.9.4/Rfast/R/tmle.R                    |    1 
 Rfast-1.9.4/Rfast/R/tobit.mle.R               |    1 
 Rfast-1.9.4/Rfast/R/topological_sort.R        |    1 
 Rfast-1.9.4/Rfast/R/total.dist.R              |    2 
 Rfast-1.9.4/Rfast/R/total.dista.R             |    2 
 Rfast-1.9.4/Rfast/R/triangular.R              |only
 Rfast-1.9.4/Rfast/R/ttest.R                   |    1 
 Rfast-1.9.4/Rfast/R/ttest1.R                  |    1 
 Rfast-1.9.4/Rfast/R/ttest2.R                  |    2 
 Rfast-1.9.4/Rfast/R/ttests.R                  |    1 
 Rfast-1.9.4/Rfast/R/ttests.pairs.R            |    1 
 Rfast-1.9.4/Rfast/R/twoway.anova.R            |    5 
 Rfast-1.9.4/Rfast/R/twoway.anovas.R           |    1 
 Rfast-1.9.4/Rfast/R/ufactor.R                 |    2 
 Rfast-1.9.4/Rfast/R/univglms.R                |    1 
 Rfast-1.9.4/Rfast/R/univglms2.R               |    1 
 Rfast-1.9.4/Rfast/R/var2test.R                |    1 
 Rfast-1.9.4/Rfast/R/var2tests.R               |    1 
 Rfast-1.9.4/Rfast/R/varcomps.mle.R            |    3 
 Rfast-1.9.4/Rfast/R/varcomps.mom.R            |    3 
 Rfast-1.9.4/Rfast/R/vartest.R                 |    1 
 Rfast-1.9.4/Rfast/R/vartests.R                |    1 
 Rfast-1.9.4/Rfast/R/vecdist.R                 |    2 
 Rfast-1.9.4/Rfast/R/vm.mle.R                  |    2 
 Rfast-1.9.4/Rfast/R/vmf.mle.R                 |    1 
 Rfast-1.9.4/Rfast/R/watson.R                  |    1 
 Rfast-1.9.4/Rfast/R/weib.reg.R                |    2 
 Rfast-1.9.4/Rfast/R/weibull.mle.R             |    1 
 Rfast-1.9.4/Rfast/R/which.is.R                |    2 
 Rfast-1.9.4/Rfast/R/wigner.mle.R              |    1 
 Rfast-1.9.4/Rfast/R/wrapcauchy.mle.R          |    1 
 Rfast-1.9.4/Rfast/R/yule.R                    |    1 
 Rfast-1.9.4/Rfast/R/zip.mle.R                 |    1 
 Rfast-1.9.4/Rfast/R/ztp.mle.R                 |    1 
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Package EpiStats updated to version 1.3-1 with previous version 1.2-2 dated 2019-05-24

Title: Tools for Epidemiologists
Description: Provides set of functions aimed at epidemiologists. They include commands for measures of association and impact for case control studies and cohort studies. They may be particularly useful for outbreak investigations and include univariate and stratified analyses. The functions for cohort studies include the CS(), CSTable() and CSInter() commands. The functions for case control studies include the CC(), CCTable() and CCInter() commands.
Author: Jean Pierre Decorps [aut, cre], Esther Kissling [ctb]
Maintainer: Jean Pierre Decorps <jp.decorps@epiconcept.fr>

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Package dbarts updated to version 0.9-12 with previous version 0.9-11 dated 2019-04-20

Title: Discrete Bayesian Additive Regression Trees Sampler
Description: Fits Bayesian additive regression trees (BART; Chipman, George, and McCulloch (2010) <doi:10.1214/09-AOAS285>) while allowing the updating of predictors or response so that BART can be incorporated as a conditional model in a Gibbs/MH sampler. Also serves as a drop-in replacement for package 'BayesTree'.
Author: Vincent Dorie [aut, cre], Hugh Chipman [aut], Robert McCulloch [aut]
Maintainer: Vincent Dorie <vdorie@gmail.com>

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Package bife updated to version 0.6 with previous version 0.5 dated 2018-03-07

Title: Binary Choice Models with Fixed Effects
Description: Estimates fixed effects binary choice models (logit and probit) with potentially many individual fixed effects and computes average partial effects. Incidental parameter bias can be reduced with an asymptotic bias-correction proposed by Fernandez-Val (2009) <doi:10.1016/j.jeconom.2009.02.007>.
Author: Amrei Stammann [aut, cre], Daniel Czarnowske [aut] (<https://orcid.org/0000-0002-0030-929X>), Florian Heiss [aut], Daniel McFadden [ctb]
Maintainer: Amrei Stammann <amrei.stammann@hhu.de>

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Package icpsrdata updated to version 0.4.0 with previous version 0.3.0 dated 2016-12-08

Title: Reproducible Data Retrieval from the ICPSR Archive
Description: Reproducible, programmatic retrieval of datasets from the Inter-university Consortium for Political and Social Research archive.
Author: Frederick Solt [aut, cre], Kellen Gracey [aut], Eric Persson [ctb], Joanna Pepin [ctb], J. Hathaway [ctb]
Maintainer: Frederick Solt <frederick-solt@uiowa.edu>

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Package AzureStor updated to version 2.0.2 with previous version 2.0.1 dated 2019-03-21

Title: Storage Management in 'Azure'
Description: Manage storage in Microsoft's 'Azure' cloud: <https://azure.microsoft.com/services/storage>. On the admin side, 'AzureStor' includes features to create, modify and delete storage accounts. On the client side, it includes an interface to blob storage, file storage, and 'Azure Data Lake Storage Gen2': upload and download files and blobs; list containers and files/blobs; create containers; and so on. Authenticated access to storage is supported, via either a shared access key or a shared access signature (SAS).
Author: Hong Ooi [aut, cre], Microsoft [cph]
Maintainer: Hong Ooi <hongooi@microsoft.com>

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Package rcites updated to version 1.0.1 with previous version 1.0.0 dated 2018-11-17

Title: R Interface to the Species+ Database
Description: A programmatic interface to the Species+ <https://speciesplus.net/> database via the Species+/CITES Checklist API <https://api.speciesplus.net/>.
Author: Jonas Geschke [aut] (<https://orcid.org/0000-0002-5654-9313>), Kevin Cazelles [aut, cre] (<https://orcid.org/0000-0001-6619-9874>), Ignasi Bartomeus [aut] (<https://orcid.org/0000-0001-7893-4389>), Jonathan Goldenberg [ctb], Marie-Bé Leduc [ctb], Yasmine Verzelen [ctb], Noam Ross [rev], Margaret Siple [rev]
Maintainer: Kevin Cazelles <kevin.cazelles@gmail.com>

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Package icesTAF updated to version 3.1-1 with previous version 3.0-0 dated 2019-04-25

Title: Functions to Support the ICES Transparent Assessment Framework
Description: Functions to support the ICES Transparent Assessment Framework <http://taf.ices.dk> to organize data, methods, and results used in ICES assessments. ICES is an organization facilitating international collaboration in marine science.
Author: Arni Magnusson [aut, cre], Colin Millar [aut], Alexandros Kokkalis [ctb]
Maintainer: Arni Magnusson <arni.magnusson@ices.dk>

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New package hmstimer with initial version 0.0.1
Package: hmstimer
Title: hms Based Timer
Version: 0.0.1
Authors@R: person(given = "Joe", family = "Thorley", role = c("aut", "cre"), email = "joe@poissonconsulting.ca", comment = c(ORCID = "0000-0002-7683-4592"))
Description: Tracks elapsed clock time using a hms() scalar (inherits from difftime() with seconds as the unit).
License: MIT + file LICENSE
Suggests: hms, covr, testthat
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-24 15:42:57 UTC; joe
Author: Joe Thorley [aut, cre] (<https://orcid.org/0000-0002-7683-4592>)
Maintainer: Joe Thorley <joe@poissonconsulting.ca>
Repository: CRAN
Date/Publication: 2019-05-24 16:30:03 UTC

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Package georob updated to version 0.3-10 with previous version 0.3-9 dated 2019-04-08

Title: Robust Geostatistical Analysis of Spatial Data
Description: Provides functions for efficiently fitting linear models with spatially correlated errors by robust and Gaussian (Restricted) Maximum Likelihood and for computing robust and customary point and block external-drift Kriging predictions, along with utility functions for variogram modelling in ad hoc geostatistical analyses, model building, model evaluation by cross-validation, (conditional) simulation of Gaussian processes, unbiased back-transformation of Kriging predictions of log-transformed data.
Author: Andreas Papritz [cre, aut], Cornelia Schwierz [ctb]
Maintainer: Andreas Papritz <andreas.papritz@env.ethz.ch>

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New package genio with initial version 1.0.9
Package: genio
Title: Genetics Input/Output Functions
Version: 1.0.9
Authors@R: person(given = "Alejandro", family = "Ochoa", role = c("aut", "cre"), email = "alejandro.ochoa@duke.edu", comment = c(ORCID = "0000-0003-4928-3403"))
Description: Implements readers and writers for file formats associated with genetics data. Reading and writing plink BED/BIM/FAM formats is fully supported, including a lightning-fast BED reader and writer implementations. Other functions are 'readr' wrappers that are more constrained, user-friendly, and efficient for these particular applications; handles plink and eigenstrat tables (FAM, BIM, IND, and SNP files). There are also "make" functions for FAM and BIM tables with default values to go with simulated genotype data.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1.9000
Imports: readr, tibble, Rcpp
LinkingTo: Rcpp
Suggests: testthat, knitr, rmarkdown, lfa, BEDMatrix, snpStats, pryr
VignetteBuilder: knitr
URL: https://github.com/OchoaLab/genio
BugReports: https://github.com/OchoaLab/genio/issues
NeedsCompilation: yes
Packaged: 2019-05-24 14:58:48 UTC; viiia
Author: Alejandro Ochoa [aut, cre] (<https://orcid.org/0000-0003-4928-3403>)
Maintainer: Alejandro Ochoa <alejandro.ochoa@duke.edu>
Repository: CRAN
Date/Publication: 2019-05-24 16:11:41 UTC

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New package tranSurv with initial version 1.2.0
Package: tranSurv
Title: Estimating a Survival Distribution in the Presence of Dependent Left Truncation and Right Censoring
Version: 1.2.0
Authors@R: c(person("Sy Han (Steven)", "Chiou", email = "schiou@utdallas.edu", role = c("aut", "cre")))
Description: A structural transformation model for a latent, quasi-independent truncation time as a function of the observed dependent truncation time and the event time, and an unknown dependence parameter. The dependence parameter is chosen to minimize the conditional Kendall's tau (Martin and Betensky, 2005) <doi:10.1198/016214504000001538>. The marginal distribution for the truncation time and the event time are completely left unspecified.
License: GPL (>= 3)
URL: http://github.com/stc04003/tranSurv
BugReports: http://github.com/stc04003/tranSurv/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: survival, SQUAREM, methods
Suggests: MASS, boot
NeedsCompilation: yes
Packaged: 2019-05-23 20:52:52 UTC; schiou
Author: Sy Han (Steven) Chiou [aut, cre]
Maintainer: Sy Han (Steven) Chiou <schiou@utdallas.edu>
Repository: CRAN
Date/Publication: 2019-05-24 15:30:03 UTC

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New package SupMZ with initial version 0.1.0
Package: SupMZ
Type: Package
Title: Detecting Structural Change with Heteroskedasticity
Version: 0.1.0
Authors@R: c( person(c("Muhammad", "Yaseen"), email = "myaseen208@gmail.com", role = c("aut", "cre")) , person(c("Sami", "Ullah"), email = "samiullahuos@gmail.com", role = c("aut", "ctb")) , person(c("Gulfam", "Haider"), email = "haider.gulfam786@gmail.com", role = c("aut", "ctb")) )
Author: Muhammad Yaseen [aut, cre], Sami Ullah [aut, ctb], Gulfam Haider [aut, ctb]
Maintainer: Muhammad Yaseen <myaseen208@gmail.com>
Description: Calculates the sup MZ value to detect the unknown structural break points under Heteroskedasticity as given in Ahmed et al. (2017) (<DOI: 10.1080/03610926.2016.1235200>).
Depends: R (>= 3.5.0)
Imports: dplyr, magrittr
License: GPL-2
URL: https://github.com/myaseen208/SupMZ, https://myaseen208.github.io/SupMZ/
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Note: Department of Mathematics and Statistics, University of Agriculture Faisalabad, Faisalabad-Pakistan.
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-05-24 10:05:02 UTC; myaseen
Repository: CRAN
Date/Publication: 2019-05-24 15:20:03 UTC

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New package QUALYPSO with initial version 1.0.1
Package: QUALYPSO
Type: Package
Date: 2019-04-29
License: GPL-3
Title: Partitioning Uncertainty Components of an Incomplete Ensemble of Climate Projections
Version: 1.0.1
Authors@R: c(person("Guillaume","Evin",role = c("aut", "cre"),email="guillaume.evin@irstea.fr"))
Author: Guillaume Evin [aut, cre]
Maintainer: Guillaume Evin <guillaume.evin@irstea.fr>
Imports: MASS, expm, Rfast, foreach, doParallel, methods, stats, graphics, grDevices
Description: These functions use data augmentation and Bayesian techniques for the assessment of single-member and incomplete ensembles of climate projections. It provides unbiased estimates of climate change responses of all simulation chains and of all uncertainty variables. It additionally propagates uncertainty due to missing information in the estimates. - Evin, G., B. Hingray, J. Blanchet, N. Eckert, S. Morin, and D. Verfaillie. (2019) <doi:10.1175/JCLI-D-18-0606.1>.
Depends: R (>= 2.10)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-24 15:17:18 UTC; guillaume.evin
Repository: CRAN
Date/Publication: 2019-05-24 15:40:03 UTC

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Package EpiStats updated to version 1.2-2 with previous version 1.2 dated 2018-10-08

Title: Tools for Epidemiologists
Description: Provides set of functions aimed at epidemiologists. They include commands for measures of association and impact for case control studies and cohort studies. They may be particularly useful for outbreak investigations and include univariate and stratified analyses. The functions for cohort studies include the CS(), CSTable() and CSInter() commands. The functions for case control studies include the CC(), CCTable() and CCInter() commands.
Author: Jean Pierre Decorps [aut, cre], Esther Kissling [ctb]
Maintainer: Jean Pierre Decorps <jp.decorps@epiconcept.fr>

Diff between EpiStats versions 1.2 dated 2018-10-08 and 1.2-2 dated 2019-05-24

 DESCRIPTION            |    8 +-
 MD5                    |   40 ++++++-------
 R/01_EpiFuns.R         |   40 ++++++-------
 R/CCInter_.R           |  143 ++++++++++++++++++++++++-------------------------
 R/CC_.R                |   78 +++++++++++++-------------
 R/CSInter_.R           |   71 +++++++++++-------------
 R/crosstable.R         |   12 ++--
 README.md              |    2 
 build/vignette.rds     |binary
 inst/doc/EpiStats.R    |   84 +++++++++++++++-------------
 inst/doc/EpiStats.Rmd  |   28 +++++----
 inst/doc/EpiStats.pdf  |binary
 man/CC.Rd              |   11 +--
 man/CCInter.Rd         |   10 +--
 man/CCTable.Rd         |   11 +--
 man/CS.Rd              |    3 -
 man/CSInter.Rd         |    7 +-
 man/CSTable.Rd         |   13 ++--
 man/crossTable.Rd      |    3 -
 man/orderFactors.Rd    |    3 -
 vignettes/EpiStats.Rmd |   28 +++++----
 21 files changed, 300 insertions(+), 295 deletions(-)

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Package alpaca updated to version 0.3.1 with previous version 0.3 dated 2019-05-14

Title: Fit GLM's with High-Dimensional k-Way Fixed Effects
Description: Provides a routine to concentrate out factors with many levels during the optimization of the log-likelihood function of the corresponding generalized linear model (glm). The package is based on the algorithm proposed by Stammann (2018) <arXiv:1707.01815> and is restricted to glm's that are based on maximum likelihood estimation and non-linear. It also offers an efficient algorithm to recover estimates of the fixed effects in a post-estimation routine and includes robust and multi-way clustered standard errors. Further the package provides an analytical bias-correction for binary choice models (logit and probit) derived by Fernandez-Val and Weidner (2016) <doi:10.1016/j.jeconom.2015.12.014>.
Author: Amrei Stammann [aut, cre], Daniel Czarnowske [aut] (<https://orcid.org/0000-0002-0030-929X>)
Maintainer: Amrei Stammann <amrei.stammann@hhu.de>

Diff between alpaca versions 0.3 dated 2019-05-14 and 0.3.1 dated 2019-05-24

 alpaca-0.3.1/alpaca/DESCRIPTION               |    6 +-
 alpaca-0.3.1/alpaca/MD5                       |   53 ++++++++++++-------------
 alpaca-0.3.1/alpaca/NAMESPACE                 |    2 
 alpaca-0.3.1/alpaca/R/alpaca.R                |    4 -
 alpaca-0.3.1/alpaca/R/biasCorr.R              |   30 +-------------
 alpaca-0.3.1/alpaca/R/feglm.R                 |   45 +++++++++------------
 alpaca-0.3.1/alpaca/R/feglm.nb.R              |   28 ++++++-------
 alpaca-0.3.1/alpaca/R/generics.R              |    8 +--
 alpaca-0.3.1/alpaca/R/getAPEs.R               |   39 +++++++++---------
 alpaca-0.3.1/alpaca/R/helpers.R               |   28 +++++++++----
 alpaca-0.3.1/alpaca/inst/CITATION             |    4 -
 alpaca-0.3.1/alpaca/inst/NEWS.Rd              |only
 alpaca-0.3.1/alpaca/inst/doc/howto.R          |   28 ++++++-------
 alpaca-0.3.1/alpaca/inst/doc/howto.Rmd        |   49 ++++++++++-------------
 alpaca-0.3.1/alpaca/inst/doc/howto.html       |   55 ++++++++++----------------
 alpaca-0.3.1/alpaca/inst/doc/replication.R    |    2 
 alpaca-0.3.1/alpaca/inst/doc/replication.Rmd  |    2 
 alpaca-0.3.1/alpaca/inst/doc/replication.html |    2 
 alpaca-0.3.1/alpaca/man/alpaca-package.Rd     |only
 alpaca-0.3.1/alpaca/man/biasCorr.Rd           |    8 ---
 alpaca-0.3.1/alpaca/man/feglm.Rd              |    4 -
 alpaca-0.3.1/alpaca/man/feglm.nb.Rd           |   10 ----
 alpaca-0.3.1/alpaca/man/feglmControl.Rd       |    2 
 alpaca-0.3.1/alpaca/man/getAPEs.Rd            |   12 ++++-
 alpaca-0.3.1/alpaca/man/predict.feglm.Rd      |    2 
 alpaca-0.3.1/alpaca/vignettes/howto.Rmd       |   49 ++++++++++-------------
 alpaca-0.3.1/alpaca/vignettes/lit.bib         |   14 +++---
 alpaca-0.3.1/alpaca/vignettes/replication.Rmd |    2 
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 29 files changed, 225 insertions(+), 263 deletions(-)

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New package vfprogression with initial version 0.7.1
Package: vfprogression
Type: Package
Title: Visual Field (VF) Progression Analysis and Plotting Methods
Version: 0.7.1
Date: 2019-05-21
Author: Tobias Elze, Dian Li (documentation), Eun Young Choi (QC)
Maintainer: Dian Li <lidian@zju.edu.cn>
Description: Realization of published methods to analyze visual field (VF) progression. Introduction to the plotting methods (designed by author TE) for VF output visualization. A sample dataset for two eyes, each with 10 follow-ups is included. The VF analysis methods could be found in -- Musch et al. (1999) <doi:10.1016/S0161-6420(99)90147-1>, Nouri-Mahdavi et at. (2012) <doi:10.1167/iovs.11-9021>, Schell et at. (2014) <doi:10.1016/j.ophtha.2014.02.021>, Aptel et al. (2015) <doi:10.1111/aos.12788>.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 2.10)
Imports: stats, grDevices, graphics
NeedsCompilation: no
Packaged: 2019-05-23 20:39:50 UTC; LiD2
Repository: CRAN
Date/Publication: 2019-05-24 15:00:02 UTC

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New package SuperPCA with initial version 0.2.0
Package: SuperPCA
Type: Package
Title: Supervised Principal Component Analysis
Version: 0.2.0
Author: Gen Li <gl2521@cumc.columbia.edu>, Haocheng Ding <haochengding@ufl.edu>, Jiayi Ji <jj2876@caa.columbia.edu>
Maintainer: Jiayi Ji <jj2876@caa.columbia.edu>
Description: Dimension reduction of complex data with supervision from auxiliary information. The package contains a series of methods for different data types (e.g., multi-view or multi-way data) including the supervised singular value decomposition (SupSVD), supervised sparse and functional principal component (SupSFPC), supervised integrated factor analysis (SIFA) and supervised PARAFAC/CANDECOMP factorization (SupCP). When auxiliary data are available and potentially affect the intrinsic structure of the data of interest, the methods will accurately recover the underlying low-rank structure by taking into account the supervision from the auxiliary data. For more details, see the paper by Gen Li, <DOI:10.1111/biom.12698>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: RSpectra, psych, fBasics, R.matlab, glmnet, MASS, matrixStats, timeSeries, stats, matlabr, spls, pracma, matlab
Depends: Matrix
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2019-05-24 01:51:48 UTC; JiayiJi
Repository: CRAN
Date/Publication: 2019-05-24 14:10:03 UTC

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New package see with initial version 0.1.0
Package: see
Type: Package
Title: Visualisation Toolbox for 'easystats' and Extra Geoms, Themes and Color Palettes for 'ggplot2'
Version: 0.1.0
Date: 2019-05-23
Authors@R: c( person("Daniel", "Lüdecke", role = c("aut", "cre"), email = "d.luedecke@uke.de", comment = c(ORCID = "0000-0002-8895-3206")), person("Dominique", "Makowski", email = "dom.makowski@gmail.com", role = c("aut", "inv"), comment = c(ORCID = "0000-0001-5375-9967")), person("Philip", "Waggoner", email = "philip.waggoner@gmail.com", role = c("aut", "ctb"), comment = c(ORCID = "0000-0002-7825-7573")), person("Mattan S.", "Ben-Shachar", role = c("aut"), email = "matanshm@post.bgu.ac.il", comment = c(ORCID = "0000-0002-4287-4801")) )
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>
URL: https://easystats.github.io/see/
BugReports: https://github.com/easystats/see/issues
Description: Provides plotting utilities supporting easystats-packages (<https://github.com/easystats/easystats>) and some extra themes, geoms, and scales for 'ggplot2'. Color scales are based on <https://www.materialui.co/colors>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.0), graphics, grDevices, stats
Imports: dplyr, ggplot2, ggridges, grid, gridExtra, insight, magrittr, rlang, scales
Suggests: bayestestR, covr, tidyr, rmarkdown, rstanarm, stringr, testthat
RoxygenNote: 6.1.1
Language: en-GB
NeedsCompilation: no
Packaged: 2019-05-23 06:36:23 UTC; mail
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>), Dominique Makowski [aut, inv] (<https://orcid.org/0000-0001-5375-9967>), Philip Waggoner [aut, ctb] (<https://orcid.org/0000-0002-7825-7573>), Mattan S. Ben-Shachar [aut] (<https://orcid.org/0000-0002-4287-4801>)
Repository: CRAN
Date/Publication: 2019-05-24 14:50:03 UTC

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New package RcppXsimd with initial version 7.1.3
Package: RcppXsimd
Type: Package
Title: Xsimd C++ Header-Only Library Files
Version: 7.1.3
Date: 2019-05-22
Authors@R: c( person("Marc A.", "Suchard", email = "msuchard@ucla.edu", role = c("aut","cre")), person("Andrew J.", "Holbrook", role = "aut"), person("Observational Health Data Sciences and Informatics", role = "cph"), person("Johan", "Mabille", role = c("cph", "ctb"), comment = "author and copyright holder of Xsimd library under a BSD-3 license"), person("Sylvain", "Corlay", role = c("cph", "ctb"), comment = "author and copyright holder of Xsimd library under a BSD-3 license"), person("Alexander J.", "Lee", role = c("cph", "ctb"), comment = "author and copyright holder of FeatureDetector library under a CC0 1.0 license") )
Description: This header-only library provides modern, portable C++ wrappers for SIMD intrinsics and parallelized, optimized math implementations (SSE, AVX, NEON, AVX512). By placing this library in this package, we offer an efficient distribution system for Xsimd <https://github.com/QuantStack/xsimd> for R packages using CRAN.
License: BSD_3_clause + file LICENSE
Imports: Rcpp (>= 1.0.0)
LinkingTo: Rcpp
RoxygenNote: 6.1.1
Encoding: UTF-8
Suggests: testthat
NeedsCompilation: yes
Packaged: 2019-05-22 14:22:46 UTC; msuchard
Author: Marc A. Suchard [aut, cre], Andrew J. Holbrook [aut], Observational Health Data Sciences and Informatics [cph], Johan Mabille [cph, ctb] (author and copyright holder of Xsimd library under a BSD-3 license), Sylvain Corlay [cph, ctb] (author and copyright holder of Xsimd library under a BSD-3 license), Alexander J. Lee [cph, ctb] (author and copyright holder of FeatureDetector library under a CC0 1.0 license)
Maintainer: Marc A. Suchard <msuchard@ucla.edu>
Repository: CRAN
Date/Publication: 2019-05-24 14:20:02 UTC

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New package adept with initial version 1.0.1
Package: adept
Type: Package
Title: Adaptive Empirical Pattern Transformation
Version: 1.0.1
Authors@R: c( person("Marta", "Karas", email = "marta.karass@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-5889-3970")), person("Jacek", "Urbanek", role = c("aut"), comment = c(ORCID = "0000-0002-1890-8899")), person("Ciprian", "Crainiceanu", role = c("aut")), person("John", "Muschelli", role = c("ctb"), comment = c(ORCID = "0000-0001-6469-1750")), person("Adi", "Gherman", role = c("ctb")) )
Description: Designed for optimal use in performing fast, accurate walking strides segmentation from high-density data collected from a wearable accelerometer worn during continuous walking activity.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
URL: https://github.com/martakarass/adept
BugReports: https://github.com/martakarass/adept/issues
Depends: R (>= 2.10)
Suggests: knitr, rmarkdown, testthat, ggplot2, lubridate, reshape2, gridExtra, spelling, cluster, adeptdata
VignetteBuilder: knitr
Imports: runstats, tibble, dplyr, future, magrittr
Language: en-US
NeedsCompilation: no
Packaged: 2019-05-22 22:40:19 UTC; martakaras
Author: Marta Karas [aut, cre] (<https://orcid.org/0000-0001-5889-3970>), Jacek Urbanek [aut] (<https://orcid.org/0000-0002-1890-8899>), Ciprian Crainiceanu [aut], John Muschelli [ctb] (<https://orcid.org/0000-0001-6469-1750>), Adi Gherman [ctb]
Maintainer: Marta Karas <marta.karass@gmail.com>
Repository: CRAN
Date/Publication: 2019-05-24 14:30:03 UTC

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New package parcoords with initial version 1.0.0
Package: parcoords
Title: 'Htmlwidget' for 'd3.js' Parallel Coordinates Chart
Version: 1.0.0
Date: 2019-05-13
Authors@R: c( person("Mike", "Bostock", role = c("aut", "cph"), comment = "d3.js library in htmlwidgets/lib, http://d3js.org"), person("Kai", "Chang",role = c( "aut","cph" ), comment = "parallel coordinates reusable chart, https://github.com/syntagmatic/parallel-coordinates"), person("Xing", "Yun", role = c( "aut","cph" ), comment = "'es6' parallel coordinates, https://github.com/BigFatDog/parcoords-es"), person("Kenton","Russell", role = c("aut","cre"), comment = "R interface", email = "kent.russell@timelyportfolio.com"), person("Anobel","Odisho", role = c("aut"), comment = "R interface guidance, suggestions, testing, review, and feedback", email = "Anobel.Odisho@ucsf.edu"), person("Mark","Albrecht",role = c("ctb"),comment = "Shiny output and example", email="malbrech@nmdp.org") )
Maintainer: Kenton Russell <kent.russell@timelyportfolio.com>
Description: Create interactive parallel coordinates charts with this 'htmlwidget' wrapper for 'd3.js' <https://github.com/BigFatDog/parcoords-es> {'parallel-coordinates'}.
URL: https://github.com/timelyportfolio/parcoords
BugReports: https://github.com/timelyportfolio/parcoords/issues
Depends: R (>= 3.2.0)
License: MIT + file LICENSE
LazyData: true
Imports: crosstalk, htmlwidgets (>= 0.6.0), utils
Suggests: d3r, ggplot2, htmltools, knitr, shiny, testthat, rmarkdown
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-05-22 03:29:18 UTC; kentr
Author: Mike Bostock [aut, cph] (d3.js library in htmlwidgets/lib, http://d3js.org), Kai Chang [aut, cph] (parallel coordinates reusable chart, https://github.com/syntagmatic/parallel-coordinates), Xing Yun [aut, cph] ('es6' parallel coordinates, https://github.com/BigFatDog/parcoords-es), Kenton Russell [aut, cre] (R interface), Anobel Odisho [aut] (R interface guidance, suggestions, testing, review, and feedback), Mark Albrecht [ctb] (Shiny output and example)
Repository: CRAN
Date/Publication: 2019-05-24 13:10:03 UTC

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Package neonUtilities updated to version 1.2.2 with previous version 1.2.1 dated 2019-03-06

Title: Utilities for Working with NEON Data
Description: NEON data packages can be accessed through the NEON Data Portal <http://data.neonscience.org> or through the NEON Data API (see <http://data.neonscience.org/data-api> for documentation). Data delivered from the Data Portal are provided as monthly zip files packaged within a parent zip file, while individual files can be accessed from the API. This package provides tools that aid in discovering, downloading, and reformatting data prior to use in analyses. This includes downloading data via the API, merging data tables by type, and converting formats. For more information, see the readme file at <https://github.com/NEONScience/NEON-utilities>.
Author: Christine Laney <claney@battelleecology.org>, Claire Lunch <clunch@battelleecology.org>
Maintainer: Claire Lunch <clunch@battelleecology.org>

Diff between neonUtilities versions 1.2.1 dated 2019-03-06 and 1.2.2 dated 2019-05-24

 DESCRIPTION              |    8 ++++----
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Package mdatools updated to version 0.9.4 with previous version 0.9.1 dated 2018-07-06

Title: Multivariate Data Analysis for Chemometrics
Description: Package implements projection based methods for preprocessing, exploring and analysis of multivariate data used in chemometrics.
Author: Sergey Kucheryavskiy
Maintainer: Sergey Kucheryavskiy <svkucheryavski@gmail.com>

Diff between mdatools versions 0.9.1 dated 2018-07-06 and 0.9.4 dated 2019-05-24

 DESCRIPTION                       |   11 +-
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 NAMESPACE                         |    2 
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 R/mdaplots.R                      |    4 -
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 R/pls.R                           |  147 +++++++++++++++++++-------------------
 R/plsda.R                         |    3 
 R/prep.R                          |   22 ++++-
 README.md                         |   20 +----
 data/pellets.RData                |binary
 data/people.RData                 |binary
 data/simdata.RData                |binary
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 man/mdaplot.showRegressionLine.Rd |    4 -
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 man/setResLimits.pca.Rd           |    3 
 man/summary.regcoeffs.Rd          |    3 
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 63 files changed, 376 insertions(+), 333 deletions(-)

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New package fgeo with initial version 1.1.3
Package: fgeo
Title: Analyze Forest Diversity and Dynamics
Version: 1.1.3
Authors@R: c(person(given = "Mauro", family = "Lepore", role = c("aut", "ctr", "cre"), email = "leporem@si.edu", comment = c(ORCID = "0000-0002-1986-7988")), person(given = "Gabriel", family = "Arellano", role = c("aut", "rev"), email = "gabriel.arellano.torres@gmail.com"), person(given = "Richard ", family = "Condit", role = "aut", email = "richardcondit@gmail.com"), person(given = "Stuart", family = "Davies", role = c("aut", "rev"), email = "daviess@si.edu"), person(given = "Matteo", family = "Detto", role = "aut", email = "teoparaglider@gmail.com"), person(given = "Erika", family = "Gonzalez-Akre", role = c("aut", "rev"), email = "GonzalezEB@si.edu", comment = c(ORCID = "0000-0001-8305-6672")), person(given = "Pamela", family = "Hall", role = "aut", email = "phall@alum.mit.edu"), person(given = "Kyle", family = "Harms", role = "aut", email = " kharms@lsu.edu"), person(given = "Valentine", family = "Herrmann", role = c("aut", "rev"), email = "HerrmannV@si.edu", comment = c(ORCID = "0000-0002-4519-481X")), person(given = "Aaron", family = "Hogan", role = "rev", email = "jamesaaronhogan@gmail.com", comment = c(ORCID = "0000-0001-9806-3074")), person(given = "Bier", family = "Kraichak", role = "rev", email = "ekraichak@gmail.com"), person(given = "David", family = "Kenfack", role = c("aut", "rev"), email = "KenfackD@si.edu "), person(given = "Lauren", family = "Krizel", role = "rev", email = "KrizelL@si.edu"), person(given = "Suzanne", family = "Lao", role = c("aut", "rev"), email = "laoz@si.edu"), person(given = "Sean", family = "McMahon", role = c("aut", "rev"), email = "mcmahons@si.edu"), person(given = "Haley", family = "Overstreet", role = "rev", email = "OverstreetH@si.edu"), person(given = "Sabrina", family = "Russo", role = c("aut", "rev"), email = "srusso2@unl.edu"), person(given = "Cara", family = "Scalpone", role = "rev", email = "ScalponeC@si.edu", comment = c(ORCID = "0000-0001-8448-2147")), person(given = "Kristina", family = "Anderson-Teixeira", role = c("aut", "rev"), email = "TeixeiraK@si.edu"), person(given = "Graham", family = "Zemunik", role = c("aut", "rev"), email = "grah.zem@gmail.com"), person(given = "Daniel", family = "Zuleta", role = c("aut", "rev"), email = "dfzuleta@gmail.com"), person(given = "CTFS-ForestGEO", role = c("cph", "fnd"), email = "ForestGEO@si.edu"))
Description: To help you access, transform, analyze, and visualize ForestGEO data, we developed a collection of R packages (<https://forestgeo.github.io/fgeo/>). This package, in particular, helps you to install and load the entire package-collection with a single R command, and provides convenient ways to find relevant documentation. Most commonly, you should not worry about the individual packages that make up the package-collection as you can access all features via this package. To learn more about ForestGEO visit <http://www.forestgeo.si.edu/>.
License: GPL-3
URL: http://forestgeo.github.io/fgeo, https://github.com/forestgeo/fgeo
BugReports: https://github.com/forestgeo/fgeo/issues
Depends: R (>= 3.2)
Imports: cli (>= 1.1.0), crayon (>= 1.3.4), dplyr (>= 0.8.1), fgeo.analyze (>= 1.1.10), fgeo.plot (>= 1.1.6), fgeo.tool (>= 1.2.4), fgeo.x (>= 1.1.3), glue (>= 1.3.1), magrittr (>= 1.5), purrr (>= 0.3.2), rlang (>= 0.3.4), rstudioapi (>= 0.10), utils
Suggests: covr (>= 3.2.1), DT (>= 0.6), kableExtra (>= 1.1.0), knitr (>= 1.23), rmarkdown (>= 1.12), spelling (>= 2.1), testthat (>= 2.1.1)
Encoding: UTF-8
Language: en-US
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-21 18:33:08 UTC; LeporeM
Author: Mauro Lepore [aut, ctr, cre] (<https://orcid.org/0000-0002-1986-7988>), Gabriel Arellano [aut, rev], Richard Condit [aut], Stuart Davies [aut, rev], Matteo Detto [aut], Erika Gonzalez-Akre [aut, rev] (<https://orcid.org/0000-0001-8305-6672>), Pamela Hall [aut], Kyle Harms [aut], Valentine Herrmann [aut, rev] (<https://orcid.org/0000-0002-4519-481X>), Aaron Hogan [rev] (<https://orcid.org/0000-0001-9806-3074>), Bier Kraichak [rev], David Kenfack [aut, rev], Lauren Krizel [rev], Suzanne Lao [aut, rev], Sean McMahon [aut, rev], Haley Overstreet [rev], Sabrina Russo [aut, rev], Cara Scalpone [rev] (<https://orcid.org/0000-0001-8448-2147>), Kristina Anderson-Teixeira [aut, rev], Graham Zemunik [aut, rev], Daniel Zuleta [aut, rev], CTFS-ForestGEO [cph, fnd]
Maintainer: Mauro Lepore <leporem@si.edu>
Repository: CRAN
Date/Publication: 2019-05-24 13:30:03 UTC

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New package climateStability with initial version 0.1.1
Package: climateStability
Title: Estimating Climate Stability from Climate Model Data
Version: 0.1.1
Authors@R: person("Hannah", "Owens", email = "hannah.owens@gmail.com", role = c("aut", "cre"))
Description: Climate stability measures are not formalized in the literature and tools for generating stability metrics from existing data are nascent. This package provides tools for calculating climate stability from raster data encapsulating climate change as a series of time slices. The methods follow Owens and Guralnick. Submitted, Biodiversity Informatics.
Depends: R (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: raster, knitr
Suggests: rangeBuilder
VignetteBuilder: knitr
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2019-05-22 06:46:41 UTC; Hannah
Author: Hannah Owens [aut, cre]
Maintainer: Hannah Owens <hannah.owens@gmail.com>
Repository: CRAN
Date/Publication: 2019-05-24 13:10:07 UTC

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Package bcrm updated to version 0.5.2 with previous version 0.5.1 dated 2019-05-22

Title: Bayesian Continual Reassessment Method for Phase I Dose-Escalation Trials
Description: Implements a wide variety of one- and two-parameter Bayesian CRM designs. The program can run interactively, allowing the user to enter outcomes after each cohort has been recruited, or via simulation to assess operating characteristics.
Author: Michael Sweeting [aut], Graham Wheeler [aut, cre]
Maintainer: Graham Wheeler <graham.wheeler@ucl.ac.uk>

Diff between bcrm versions 0.5.1 dated 2019-05-22 and 0.5.2 dated 2019-05-24

 DESCRIPTION      |   11 +++++-----
 MD5              |   10 ++++-----
 NEWS             |    8 +++++++
 R/bcrm-package.R |    2 -
 R/bcrm.R         |   59 ++++++++++++++++++++++++++++++++++++++++---------------
 R/posteriors.R   |   47 +++++++++++++++++++++++++++++++++++++++++++
 6 files changed, 110 insertions(+), 27 deletions(-)

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New package bayesvl with initial version 0.8.5
Package: bayesvl
Type: Package
Title: Visually Learning the Graphical Structure of Bayesian Networks and Performing MCMC with 'Stan'
Version: 0.8.5
Date: 2019-05-20
Authors@R: c(person("Viet-Phuong", "La", role = c("aut", "cre"), email = "lvphuong@gmail.com"), person("Quan-Hoang", "Vuong", role = c("aut"), email = "hoang.vuongquan@phenikaa-uni.edu.vn"))
Author: Viet-Phuong La [aut, cre], Quan-Hoang Vuong [aut]
Maintainer: Viet-Phuong La <lvphuong@gmail.com>
Imports: coda, bnlearn, ggplot2, bayesplot, viridis, reshape2, dplyr
Suggests: loo (>= 2.0.0)
Depends: R (>= 3.4.0), rstan (>= 2.10.0), StanHeaders (>= 2.18.0), stats, graphics, methods
Description: Provides users with its associated functions for pedagogical purposes in visually learning Bayesian networks and Markov chain Monte Carlo (MCMC) computations. It enables users to: a) Create and examine the (starting) graphical structure of Bayesian networks; b) Create random Bayesian networks using a dataset with customized constraints; c) Generate 'Stan' code for structures of Bayesian networks for sampling the data and learning parameters; d) Plot the network graphs; e) Perform Markov chain Monte Carlo computations and produce graphs for posteriors checks. The package refers to one reference item, which describes the methods and algorithms: Vuong, Quan-Hoang and La, Viet-Phuong (2019) <doi:10.31219/osf.io/w5dx6> The 'bayesvl' R package. Open Science Framework (May 18).
License: GPL (>= 3)
BugReports: https://github.com/sshpa/bayesvl/issues
URL: https://github.com/sshpa/bayesvl
NeedsCompilation: no
Packaged: 2019-05-22 16:21:34 UTC; phuong
Repository: CRAN
Date/Publication: 2019-05-24 13:40:06 UTC

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New package simml with initial version 0.1.0
Package: simml
Type: Package
Title: Single-Index Models with Multiple-Links
Version: 0.1.0
Author: Park, H., Petkova, E., Tarpey, T., Ogden, R.T.
Maintainer: Hyung Park <parkh15@nyu.edu>
Description: A major challenge in estimating treatment decision rules from a randomized clinical trial dataset with covariates measured at baseline lies in detecting relatively small treatment effect modification-related variability (i.e., the treatment-by-covariates interaction effects on treatment outcomes) against a relatively large non-treatment-related variability (i.e., the main effects of covariates on treatment outcomes). The class of Single-Index Models with Multiple-Links is a novel single-index model specifically designed to estimate a single-index (a linear combination) of the covariates associated with the treatment effect modification-related variability, while allowing a nonlinear association with the treatment outcomes via flexible link functions. The models provide a flexible regression approach to developing treatment decision rules based on patients' data measured at baseline. We refer to Petkova, Tarpey, Su, and Ogden (2017) <doi: 10.1093/biostatistics/kxw035> and "A constrained single-index model for estimating interactions between a treatment and covariates" (under review, 2019) for detail. The main function of this package is simml().
License: GPL-3
Imports: mgcv, plyr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-21 17:39:18 UTC; parkh15
Repository: CRAN
Date/Publication: 2019-05-24 12:40:03 UTC

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New package rwebstat with initial version 1.0.2
Package: rwebstat
Title: Download Data from the Webstat API
Version: 1.0.2
Authors@R: c( person("Vincent", "Guegan", email = "vincent.guegan@banque-france.fr", role = c("aut", "cre")), person("Etienne", "Kintzler", email = "etienne.kintzler@banque-france.fr", role = "aut"), person("Jules", "Lecocq", email = "jules.lecocq@banque-france.fr", role = "aut"))
Description: Access the Webstat API, download data and metadata from more than 35000 time series from the Banque de France statistics web portal. Access requires a free client ID easily available from the API portal <https://developer.webstat.banque-france.fr/>.
URL: https://developer.webstat.banque-france.fr,http://webstat.banque-france.fr
BugReports: https://developer.webstat.banque-france.fr/contact
Depends: R (>= 3.2.0)
Imports: dplyr, getPass, httr, readr
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
RoxygenNote: 6.0.1
Packaged: 2019-05-21 16:04:48 UTC; X831079
Author: Vincent Guegan [aut, cre], Etienne Kintzler [aut], Jules Lecocq [aut]
Maintainer: Vincent Guegan <vincent.guegan@banque-france.fr>
Repository: CRAN
Date/Publication: 2019-05-24 12:30:03 UTC

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New package mssm with initial version 0.1.0
Package: mssm
Type: Package
Title: Multivariate State Space Models
Version: 0.1.0
Authors@R: c( person("Benjamin", "Christoffersen", email = "boennecd@gmail.com", role = c("cre", "aut")), person("Anthony", "Williams", role = c("cph")))
Description: Provides methods to perform parameter estimation and make analysis of multivariate observed outcomes through time which depends on a latent state variable. All methods scale well in the dimension of the observed outcomes at each time point. The package contains an implementation of a Laplace approximation, particle filters like suggested by Lin, Zhang, Cheng, & Chen (2005) <doi:10.1198/016214505000000349>, and the gradient and observed information matrix approximation suggested by Poyiadjis, Doucet, & Singh (2011) <doi:10.1093/biomet/asq062>.
License: GPL-2
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0), stats, graphics
LinkingTo: Rcpp, RcppArmadillo, testthat, nloptr (>= 1.2.0)
Imports: Rcpp, nloptr (>= 1.2.0)
RoxygenNote: 6.1.1
SystemRequirements: C++11
Suggests: testthat, microbenchmark, Ecdat
NeedsCompilation: yes
Packaged: 2019-05-21 15:46:53 UTC; boennecd
Author: Benjamin Christoffersen [cre, aut], Anthony Williams [cph]
Maintainer: Benjamin Christoffersen <boennecd@gmail.com>
Repository: CRAN
Date/Publication: 2019-05-24 12:30:06 UTC

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Package BNSP updated to version 2.1.0 with previous version 2.0.9 dated 2019-05-15

Title: Bayesian Non- And Semi-Parametric Model Fitting
Description: MCMC algorithms & processing functions for non- and semi-parametric models: 1. Dirichlet process mixtures & 2. spike-slab for multivariate (and univariate) response analysis, with nonparametric models for the means, the variances and the correlation matrix.
Author: Georgios Papageorgiou
Maintainer: Georgios Papageorgiou <gpapageo@gmail.com>

Diff between BNSP versions 2.0.9 dated 2019-05-15 and 2.1.0 dated 2019-05-24

 BNSP-2.0.9/BNSP/man/mmvrm.Rd        |only
 BNSP-2.0.9/BNSP/man/mmvrm2mcmc.Rd   |only
 BNSP-2.1.0/BNSP/DESCRIPTION         |   10 
 BNSP-2.1.0/BNSP/MD5                 |   42 +-
 BNSP-2.1.0/BNSP/NAMESPACE           |    7 
 BNSP-2.1.0/BNSP/R/bnpMulti.R        |  394 +++++++++++---------
 BNSP-2.1.0/BNSP/R/mvrm.R            |  699 ------------------------------------
 BNSP-2.1.0/BNSP/inst/CITATION       |   25 -
 BNSP-2.1.0/BNSP/man/BNSP-package.Rd |   15 
 BNSP-2.1.0/BNSP/man/clustering.Rd   |    2 
 BNSP-2.1.0/BNSP/man/continue.Rd     |   10 
 BNSP-2.1.0/BNSP/man/histCorr.Rd     |    6 
 BNSP-2.1.0/BNSP/man/mvrm.Rd         |  144 +++++--
 BNSP-2.1.0/BNSP/man/mvrm2mcmc.Rd    |    4 
 BNSP-2.1.0/BNSP/man/plot.mvrm.Rd    |    8 
 BNSP-2.1.0/BNSP/man/summary.mvrm.Rd |    3 
 BNSP-2.1.0/BNSP/src/BNSP_init.c     |    4 
 BNSP-2.1.0/BNSP/src/BayesMult.c     |   76 +--
 BNSP-2.1.0/BNSP/src/BayesMultG.c    |   65 +--
 BNSP-2.1.0/BNSP/src/BayesMultGV.c   |   70 +--
 BNSP-2.1.0/BNSP/src/OneResLtnt.c    |    2 
 BNSP-2.1.0/BNSP/src/mvrmGAM.c       |  158 +++++---
 BNSP-2.1.0/BNSP/src/pdfs.h          |    2 
 23 files changed, 595 insertions(+), 1151 deletions(-)

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New package sismonr with initial version 1.1.2
Package: sismonr
Type: Package
Title: Simulation of in Silico Multi-Omic Networks
Version: 1.1.2
Authors@R: c( person("Olivia", "Angelin-Bonnet", email = "olivia.angelinbonnet@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-7708-2919")), person("Patrick", "Biggs", role = c("aut"), comment = c(ORCID = "0000-0002-0285-4101")), person("Matthieu", "Vignes", role = c("aut"), comment = c(ORCID = "0000-0001-8929-2975")), person("John M.", "Chambers", role = c("ctb")))
Maintainer: Olivia Angelin-Bonnet <olivia.angelinbonnet@gmail.com>
Description: A tool for the simulation of gene expression profiles for in silico regulatory networks. The package generates gene regulatory networks, which include protein-coding and noncoding genes linked via different types of regulation: regulation of transcription, translation, RNA or protein decay, and post-translational modifications. The effect of genetic mutations on the system behaviour is accounted for via the simulation of genetically different in silico individuals. The ploidy of the system is not restricted to the usual haploid or diploid situations, but is defined by the user. A choice of stochastic simulation algorithms allow us to simulate the expression profiles (RNA and if applicable protein abundance) of the genes in the in silico system for the different in silico individuals. A tutorial explaining how to use the package is available at <https://oliviaab.github.io/sismonr/>. Manuscript in preparation; see also Angelin-Bonnet O., Biggs P.J. and Vignes M. (2018) <doi:10.1109/BIBM.2018.8621131>.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
URL: https://oliviaab.github.io/sismonr/
BugReports: https://github.com/oliviaAB/sismonr/issues
Imports: XRJulia (>= 0.9.0), parallel, truncnorm, tictoc, stats, utils, dplyr, magrittr, stringr, XR, jsonlite, methods, tidyr, ggpubr, ggplot2, rlang, grDevices, igraph, graphics, scales
SystemRequirements: Julia, v 1.0 or later
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, tcltk, rgl, testthat (>= 2.1.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-05-20 00:47:10 UTC; oangelin
Author: Olivia Angelin-Bonnet [aut, cre] (<https://orcid.org/0000-0002-7708-2919>), Patrick Biggs [aut] (<https://orcid.org/0000-0002-0285-4101>), Matthieu Vignes [aut] (<https://orcid.org/0000-0001-8929-2975>), John M. Chambers [ctb]
Repository: CRAN
Date/Publication: 2019-05-24 11:30:03 UTC

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New package integr with initial version 1.0.0
Package: integr
Type: Package
Title: An Implementation of Interaction Graphs of Aleks Jakulin
Version: 1.0.0
Authors@R: person("Petar", "Markovic", email = "peleplay@gmail.com", role = c("aut", "cre"))
Description: Generates a 'Graphviz' graph of the most significant 3-way interaction gains (i.e. conditional information gains) based on a provided discrete data frame. Various output formats are supported ('Graphviz', SVG, PNG, PDF, PS). For references, see the webpage of Aleks Jakulin <http://stat.columbia.edu/~jakulin/Int/>.
Depends: R (>= 3.5.0), dplyr (>= 0.7.6), DiagrammeR (>= 1.0.0), DiagrammeRsvg (>= 0.1), rsvg (>= 1.3), gtools (>= 3.5.0), utils (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/peleplay/integr
BugReports: https://github.com/peleplay/integr/issues
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-05-24 11:14:53 UTC; peleplay
Author: Petar Markovic [aut, cre]
Maintainer: Petar Markovic <peleplay@gmail.com>
Repository: CRAN
Date/Publication: 2019-05-24 11:50:03 UTC

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Package IncDTW updated to version 1.1.1 with previous version 1.1.0 dated 2019-04-08

Title: Incremental Calculation of Dynamic Time Warping
Description: The Dynamic Time Warping (DTW) distance measure for time series allows non-linear alignments of time series to match similar patterns in time series of different lengths and or different speeds. IncDTW is characterized by (1) the incremental calculation of DTW (reduces runtime complexity to a linear level for updating the DTW distance) - especially for life data streams or subsequence matching, (2) the vector based implementation of DTW which is faster because no matrices are allocated (reduces the space complexity from a quadratic to a linear level in the number of observations) - for all runtime intensive DTW computations, (3) the subsequence matching algorithm runDTW, that efficiently finds the k-NN to a query pattern in a long time series, and (4) C++ in the heart. For details about DTW see the original paper "Dynamic programming algorithm optimization for spoken word recognition" by Sakoe and Chiba (1978) <DOI:10.1109/TASSP.1978.1163055>.
Author: Maximilian Leodolter
Maintainer: Maximilian Leodolter <maximilian.leodolter@gmail.com>

Diff between IncDTW versions 1.1.0 dated 2019-04-08 and 1.1.1 dated 2019-05-24

 IncDTW-1.1.0/IncDTW/R/data_preparation.R                           |only
 IncDTW-1.1.0/IncDTW/R/notes.R                                      |only
 IncDTW-1.1.1/IncDTW/DESCRIPTION                                    |    8 
 IncDTW-1.1.1/IncDTW/MD5                                            |   26 
 IncDTW-1.1.1/IncDTW/R/RcppExports.R                                |   20 
 IncDTW-1.1.1/IncDTW/R/dtw.R                                        |  172 -
 IncDTW-1.1.1/IncDTW/inst/doc/Incremental_Dynamic_Time_Warping.html |  287 -
 IncDTW-1.1.1/IncDTW/man/drink_glass.Rd                             |    2 
 IncDTW-1.1.1/IncDTW/man/rundtw.Rd                                  |   69 
 IncDTW-1.1.1/IncDTW/src/RcppExports.cpp                            |   74 
 IncDTW-1.1.1/IncDTW/src/init.c                                     |   14 
 IncDTW-1.1.1/IncDTW/src/rundtw.cpp                                 | 1578 +++++++++-
 IncDTW-1.1.1/IncDTW/tests/testthat/test_rundtw_multiv.R            |   28 
 IncDTW-1.1.1/IncDTW/tests/testthat/test_rundtw_multiv_znorm.R      |only
 IncDTW-1.1.1/IncDTW/tests/testthat/test_rundtw_univ.R              |   86 
 IncDTW-1.1.1/IncDTW/tests/testthat/test_rundtw_univ_znorm.R        |only
 16 files changed, 2034 insertions(+), 330 deletions(-)

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Package gprofiler2 updated to version 0.1.4 with previous version 0.1.3 dated 2019-04-23

Title: Interface to the 'g:Profiler' Toolset
Description: A toolset for functional enrichment analysis and visualization, gene/protein/SNP identifier conversion and mapping orthologous genes across species via 'g:Profiler' (<https://biit.cs.ut.ee/gprofiler>). The main tools are: (1) 'g:GOSt' - functional enrichment analysis and visualization of gene lists; (2) 'g:Convert' - gene/protein/transcript identifier conversion across various namespaces; (3) 'g:Orth' - orthology search across species; (4) 'g:SNPense' - mapping SNP rs identifiers to chromosome positions, genes and variant effects This package is an R interface corresponding to the 2019 update of 'g:Profiler' and provides access to 'g:Profiler' for versions 'e94_eg41_p11' and higher. See the package 'gProfileR' for accessing older versions from the 'g:Profiler' toolset.
Author: Liis Kolberg <liis.kolberg@ut.ee>, Uku Raudvere <uku.raudvere@ut.ee>
Maintainer: Liis Kolberg <liis.kolberg@ut.ee>

Diff between gprofiler2 versions 0.1.3 dated 2019-04-23 and 0.1.4 dated 2019-05-24

 DESCRIPTION              |    6 -
 MD5                      |   11 +-
 NAMESPACE                |    1 
 R/gprofiler2.R           |  221 ++++++++++++++++++++++++++++++++++++++++++-----
 man/gost.Rd              |   10 +-
 man/publish_gosttable.Rd |only
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 7 files changed, 218 insertions(+), 35 deletions(-)

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Package clusterSim updated to version 0.47-4 with previous version 0.47-3 dated 2018-11-28

Title: Searching for Optimal Clustering Procedure for a Data Set
Description: Distance measures (GDM1, GDM2, Sokal-Michener, Bray-Curtis, for symbolic interval-valued data), cluster quality indices (Calinski-Harabasz, Baker-Hubert, Hubert-Levine, Silhouette, Krzanowski-Lai, Hartigan, Gap, Davies-Bouldin), data normalization formulas (metric data, interval-valued symbolic data), data generation (typical and non-typical data), HINoV method, replication analysis, linear ordering methods, spectral clustering, agreement indices between two partitions, plot functions (for categorical and symbolic interval-valued data). (MILLIGAN, G.W., COOPER, M.C. (1985) <doi:10.1007/BF02294245>, HUBERT, L., ARABIE, P. (1985) <doi:10.1007%2FBF01908075>, RAND, W.M. (1971) <doi:10.1080/01621459.1971.10482356>, JAJUGA, K., WALESIAK, M. (2000) <doi:10.1007/978-3-642-57280-7_11>, MILLIGAN, G.W., COOPER, M.C. (1988) <doi:10.1007/BF01897163>, JAJUGA, K., WALESIAK, M., BAK, A. (2003) <doi:10.1007/978-3-642-55721-7_12>, DAVIES, D.L., BOULDIN, D.W. (1979) <doi:10.1109/TPAMI.1979.4766909>, CALINSKI, T., HARABASZ, J. (1974) <doi:10.1080/03610927408827101>, HUBERT, L. (1974) <doi:10.1080/01621459.1974.10480191>, TIBSHIRANI, R., WALTHER, G., HASTIE, T. (2001) <doi:10.1111/1467-9868.00293>, BRECKENRIDGE, J.N. (2000) <doi:10.1207/S15327906MBR3502_5>, WALESIAK, M., DUDEK, A. (2008) <doi:10.1007/978-3-540-78246-9_11>).
Author: Marek Walesiak <marek.walesiak@ue.wroc.pl>, Andrzej Dudek <andrzej.dudek@ue.wroc.pl>
Maintainer: Andrzej Dudek <andrzej.dudek@ue.wroc.pl>

Diff between clusterSim versions 0.47-3 dated 2018-11-28 and 0.47-4 dated 2019-05-24

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 5 files changed, 36 insertions(+), 14 deletions(-)

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Package wavScalogram updated to version 1.0.0 with previous version 0.1.0 dated 2019-03-06

Title: Wavelet Scalogram Tools for Time Series Analysis
Description: Provides scalogram based wavelet tools for time series analysis: wavelet power spectrum, scalogram, windowed scalogram, windowed scalogram difference (see Bolos et al. (2017) <doi:10.1016/j.amc.2017.05.046>), scale index and windowed scale index (Benitez et al. (2010) <doi:10.1016/j.camwa.2010.05.010>).
Author: Vicente J. Bolos and Rafael Benitez
Maintainer: Vicente J. Bolos <vicente.bolos@uv.es>

Diff between wavScalogram versions 0.1.0 dated 2019-03-06 and 1.0.0 dated 2019-05-24

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Package StepReg updated to version 1.1.0 with previous version 1.0.1 dated 2019-01-17

Title: Stepwise Regression Analysis
Description: Stepwise regression analysis for variable selection can be used to get the best candidate final regression model in univariate or multivariate regression analysis with the 'forward' and 'stepwise' steps. Procedure uses Akaike information criterion, the small-sample-size corrected version of Akaike information criterion, Bayesian information criterion, Hannan and Quinn information criterion, the corrected form of Hannan and Quinn information criterion, Schwarz criterion and significance levels as selection criteria, where the significance levels for entry and for stay are set to 0.15 as default. Multicollinearity detection in regression model are performed by checking tolerance value, which is set to 1e-7 as default. Continuous variables nested within class effect and weighted stepwise regression are also considered in this package.
Author: Junhui Li,Kun Cheng,Wenxin Liu
Maintainer: Junhui Li <junhuili@cau.edu.cn>

Diff between StepReg versions 1.0.1 dated 2019-01-17 and 1.1.0 dated 2019-05-24

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Package SCCI updated to version 1.1 with previous version 1.0 dated 2019-03-01

Title: Stochastic Complexity-Based Conditional Independence Test for Discrete Data
Description: An efficient implementation of SCCI using 'Rcpp'. SCCI is short for the Stochastic Complexity-based Conditional Independence criterium (Marx and Vreeken, 2019). SCCI is an asymptotically unbiased and L2 consistent estimator of (conditional) mutual information for discrete data.
Author: Alexander Marx [aut,cre] Jilles Vreeken [aut]
Maintainer: Alexander Marx <amarx@mpi-inf.mpg.de>

Diff between SCCI versions 1.0 dated 2019-03-01 and 1.1 dated 2019-05-24

 DESCRIPTION   |    8 ++++----
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New package R62S3 with initial version 1.2.1
Package: R62S3
Title: Automatic S3 Method Generation from R6
Version: 1.2.1
Authors@R: person("Raphael", "Sonabend", email = "raphael.sonabend.15@ucl.ac.uk", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-9225-4654"))
Description: After defining an R6 class, R62S3 is used to automatically generate S3 generics and methods for dispatch. Also allows piping for R6 objects.
Depends: R (>= 3.4.0)
Imports: checkmate
Suggests: testthat, R6, pkgdown
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
URL: https://github.com/RaphaelS1/R62S3/
BugReports: https://github.com/RaphaelS1/R62S3/issues
NeedsCompilation: no
Packaged: 2019-05-16 15:10:43 UTC; raphael
Author: Raphael Sonabend [aut, cre] (<https://orcid.org/0000-0001-9225-4654>)
Maintainer: Raphael Sonabend <raphael.sonabend.15@ucl.ac.uk>
Repository: CRAN
Date/Publication: 2019-05-24 10:00:12 UTC

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New package gdalcubes with initial version 0.1.0
Package: gdalcubes
Title: Earth Observation Data Cubes from Satellite Image Collections
Version: 0.1.0
Date: 2019-05-15
Authors@R: c( person(given = "Marius", family = "Appel", role = c("aut", "cre"), email = "marius.appel@uni-muenster.de", comment = c(ORCID = "0000-0001-5281-3896")), person(given = "Edzer", family = "Pebesma", role = "ctb", comment = c(ORCID = "0000-0001-8049-7069")), person(given = "Lewis", family = "Van Winkle", role = "cph"), person(given = "Ole Christian", family = "Eidheim", role = "cph"), person(given = "Niels", family = "Lohmann", role = "cph"), person(given = "Howard", family = "Hinnant", role = "cph"), person(given = "Adrian", family = "Colomitchi", role = "cph"), person(given = "Florian", family = "Dang", role = "cph"), person(given = "Paul", family = "Thompson", role = "cph"), person(given = "Tomasz", family = "Kamiński", role = "cph"))
Description: Processing collections of Earth observation images as on-demand multispectral, multitemporal data cubes. Users define cubes by spatiotemporal extent, resolution, and spatial reference system and let 'gdalcubes' automatically apply cropping, reprojection, and resampling using the 'Geospatial Data Abstraction Library' ('GDAL'). Implemented functions on data cubes include reduction over space and time, applying arithmetic expressions on pixel band values, moving window aggregates over time, filtering by space, time, bands, and predicates on pixel values, materializing data cubes as 'netCDF' files, and plotting. User-defined 'R' functions can be applied over chunks of data cubes. The package implements lazy evaluation and multithreading. All computational parts are implemented in C++, linking to the 'GDAL', 'netCDF', 'CURL', and 'SQLite' libraries.
Depends: R (>= 3.3.0), Rcpp, RcppProgress, jsonlite, ncdf4
License: MIT + file LICENSE
URL: https://github.com/appelmar/gdalcubes_R
BugReports: https://github.com/appelmar/gdalcubes_R/issues/
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
LinkingTo: Rcpp, RcppProgress
Suggests: knitr, magrittr, processx, rmarkdown, stars
VignetteBuilder: knitr
Copyright: file inst/COPYRIGHTS
NeedsCompilation: yes
SystemRequirements: cxx11, gdal, libgdal, libproj, libcurl, netcdf4
Packaged: 2019-05-15 12:08:47 UTC; marius
Author: Marius Appel [aut, cre] (<https://orcid.org/0000-0001-5281-3896>), Edzer Pebesma [ctb] (<https://orcid.org/0000-0001-8049-7069>), Lewis Van Winkle [cph], Ole Christian Eidheim [cph], Niels Lohmann [cph], Howard Hinnant [cph], Adrian Colomitchi [cph], Florian Dang [cph], Paul Thompson [cph], Tomasz Kamiński [cph]
Maintainer: Marius Appel <marius.appel@uni-muenster.de>
Repository: CRAN
Date/Publication: 2019-05-24 10:00:07 UTC

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New package dyndimred with initial version 1.0.1
Package: dyndimred
Type: Package
Title: Dimensionality Reduction Methods in a Common Format
Version: 1.0.1
Authors@R: c( person( "Robrecht", "Cannoodt", email = "rcannood@gmail.com", role = c("aut"), comment = c(ORCID = "0000-0003-3641-729X", github = "rcannood") ), person( "Wouter", "Saelens", email = "wouter.saelens@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-7114-6248", github = "zouter") ) )
Description: Provides a common interface for applying dimensionality reduction methods, such as Principal Component Analysis ('PCA'), Independent Component Analysis ('ICA'), diffusion maps, Locally-Linear Embedding ('LLE'), t-distributed Stochastic Neighbor Embedding ('t-SNE'), and Uniform Manifold Approximation and Projection ('UMAP'). Has built-in support for sparse matrices.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: dynutils (>= 1.0.3), Matrix, irlba
Suggests: testthat, destiny, diffusionMap, fastICA, lle, MASS, Rtsne, smacof, uwot
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-20 08:24:25 UTC; rcannood
Author: Robrecht Cannoodt [aut] (<https://orcid.org/0000-0003-3641-729X>, rcannood), Wouter Saelens [aut, cre] (<https://orcid.org/0000-0002-7114-6248>, zouter)
Maintainer: Wouter Saelens <wouter.saelens@gmail.com>
Repository: CRAN
Date/Publication: 2019-05-24 09:10:02 UTC

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Package armspp updated to version 0.0.2 with previous version 0.0.1 dated 2019-04-04

Title: Adaptive Rejection Metropolis Sampling (ARMS) via 'Rcpp'
Description: An efficient 'Rcpp' implementation of the Adaptive Rejection Metropolis Sampling (ARMS) algorithm proposed by Gilks, W. R., Best, N. G. and Tan, K. K. C. (1995) <doi:10.2307/2986138>. This allows for sampling from a univariate target probability distribution specified by its (potentially unnormalised) log density.
Author: Michael Bertolacci [aut, cre]
Maintainer: Michael Bertolacci <m.bertolacci@gmail.com>

Diff between armspp versions 0.0.1 dated 2019-04-04 and 0.0.2 dated 2019-05-24

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New package xtune with initial version 0.1.0
Package: xtune
Type: Package
Title: Regularized Regression with Differential Penalties Integrating External Information
Version: 0.1.0
Author: Chubing Zeng
Maintainer: Chubing Zeng <chubingz@usc.edu>
Description: Extends standard penalized regression (Lasso and Ridge) to allow differential shrinkage based on external information with the goal of achieving a better prediction accuracy. Examples of external information include the grouping of predictors, prior knowledge of biological importance, external p-values, function annotations, etc. The choice of multiple tuning parameters is done using an Empirical Bayes approach. A majorization-minimization algorithm is employed for implementation.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: glmnet, stats, selectiveInference
Depends: R (>= 2.10)
RoxygenNote: 6.0.1
Suggests: knitr, numDeriv, lbfgs, rmarkdown, testthat, covr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-05-17 20:40:48 UTC; chubingzeng
Repository: CRAN
Date/Publication: 2019-05-24 09:00:03 UTC

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Package OpenMx updated to version 2.13.0 with previous version 2.12.2 dated 2019-02-08

Title: Extended Structural Equation Modelling
Description: Create structural equation models that can be manipulated programmatically. Models may be specified with matrices or paths (LISREL or RAM) Example models include confirmatory factor, multiple group, mixture distribution, categorical threshold, modern test theory, differential Fit functions include full information maximum likelihood, maximum likelihood, and weighted least squares. equations, state space, and many others. Support and advanced package binaries available at <http://openmx.ssri.psu.edu>. The software is described in Neale, Hunter, Pritikin, Zahery, Brick, Kirkpatrick, Estabrook, Bates, Maes, & Boker (2016) <doi:10.1007/s11336-014-9435-8>.
Author: Steven M. Boker [aut], Michael C. Neale [aut], Hermine H. Maes [aut], Michael J. Wilde [ctb], Michael Spiegel [aut], Timothy R. Brick [aut], Ryne Estabrook [aut], Timothy C. Bates [aut], Paras Mehta [ctb], Timo von Oertzen [ctb], Ross J. Gore [aut], Michael D. Hunter [aut], Daniel C. Hackett [ctb], Julian Karch [ctb], Andreas M. Brandmaier [ctb], Joshua N. Pritikin [aut, cre], Mahsa Zahery [aut], Robert M. Kirkpatrick [aut], Yang Wang [ctb], Charles Driver [ctb], Massachusetts Institute of Technology [cph], S. G. Johnson [cph], Association for Computing Machinery [cph], Dieter Kraft [cph], Stefan Wilhelm [cph], Sarah Medland [cph], Carl F. Falk [cph], Matt Keller [cph], Manjunath B G [cph], The Regents of the University of California [cph], Lester Ingber [cph], Wong Shao Voon [cph], Juan Palacios [cph], Jiang Yang [cph], Gavin Band [cph], Yann Collet [cph], Facebook, Inc. [cph], Yuta Mori [cph], Shaun Purcell [cph], Christopher Chang [cph]
Maintainer: Joshua N. Pritikin <jpritikin@pobox.com>

Diff between OpenMx versions 2.12.2 dated 2019-02-08 and 2.13.0 dated 2019-05-24

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 OpenMx-2.13.0/OpenMx/NAMESPACE                                                              |    3 
 OpenMx-2.13.0/OpenMx/NEWS.md                                                                |   52 
 OpenMx-2.13.0/OpenMx/R/0ClassUnion.R                                                        |    4 
 OpenMx-2.13.0/OpenMx/R/MxAlgebra.R                                                          |   40 
 OpenMx-2.13.0/OpenMx/R/MxAlgebraConvert.R                                                   |    4 
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 OpenMx-2.13.0/OpenMx/R/MxDataWLS.R                                                          |   15 
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 OpenMx-2.13.0/OpenMx/R/MxExpectationBA81.R                                                  |    1 
 OpenMx-2.13.0/OpenMx/R/MxExpectationGREML.R                                                 |    2 
 OpenMx-2.13.0/OpenMx/R/MxExpectationLISREL.R                                                |    5 
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 OpenMx-2.13.0/OpenMx/R/MxFactorScores.R                                                     |   89 
 OpenMx-2.13.0/OpenMx/R/MxFitFunctionWLS.R                                                   |   96 
 OpenMx-2.13.0/OpenMx/R/MxLISRELModel.R                                                      |    6 
 OpenMx-2.13.0/OpenMx/R/MxMI.R                                                               |    1 
 OpenMx-2.13.0/OpenMx/R/MxMMI.R                                                              |   82 
 OpenMx-2.13.0/OpenMx/R/MxModel.R                                                            |   17 
 OpenMx-2.13.0/OpenMx/R/MxModelFunctions.R                                                   |   10 
 OpenMx-2.13.0/OpenMx/R/MxModelParameters.R                                                  |    6 
 OpenMx-2.13.0/OpenMx/R/MxMultiModel.R                                                       |   20 
 OpenMx-2.13.0/OpenMx/R/MxNamespace.R                                                        |   36 
 OpenMx-2.13.0/OpenMx/R/MxOptions.R                                                          |   22 
 OpenMx-2.13.0/OpenMx/R/MxPath.R                                                             |   10 
 OpenMx-2.13.0/OpenMx/R/MxRAMModel.R                                                         |   11 
 OpenMx-2.13.0/OpenMx/R/MxRobustSE.R                                                         |   32 
 OpenMx-2.13.0/OpenMx/R/MxRun.R                                                              |   33 
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 OpenMx-2.13.0/OpenMx/R/MxSE.R                                                               |   89 
 OpenMx-2.13.0/OpenMx/R/MxSaturatedModel.R                                                   |    9 
 OpenMx-2.13.0/OpenMx/R/MxSummary.R                                                          |   66 
 OpenMx-2.13.0/OpenMx/R/MxTryHard.R                                                          |  129 
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 OpenMx-2.13.0/OpenMx/R/MxVersion.R                                                          |    2 
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 OpenMx-2.13.0/OpenMx/README.md                                                              |   43 
 OpenMx-2.13.0/OpenMx/configure                                                              |    3 
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 OpenMx-2.13.0/OpenMx/inst/CITATION                                                          |   16 
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Permanent link

New package MDSPCAShiny with initial version 0.1.0
Package: MDSPCAShiny
Type: Package
Title: Interactive Document for Working with Multidimensional Scaling and Principal Component Analysis
Version: 0.1.0
Author: Kartikeya Bolar
Maintainer: Kartikeya Bolar <kartikeya.bolar@tapmi.edu.in>
Description: An interactive document on the topic of multidimensional scaling and principal component analysis using 'rmarkdown' and 'shiny' packages. Runtime examples are provided in the package function as well as at <https://kartikeyabolar.shinyapps.io/MDS_PCAShiny/>.
License: GPL-2
Encoding: UTF-8
LazyData: TRUE
Depends: R (>= 3.0.3)
Imports: shiny,rmarkdown,dplyr,datasets,psych,MASS
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-18 18:00:54 UTC; KARTIKEYA
Repository: CRAN
Date/Publication: 2019-05-24 08:20:20 UTC

More information about MDSPCAShiny at CRAN
Permanent link

Package spaero updated to version 0.5.0 with previous version 0.4.0 dated 2018-12-16

Title: Software for Project AERO
Description: Implements methods for anticipating the emergence and eradication of infectious diseases from surveillance time series. Also provides support for computational experiments testing the performance of such methods.
Author: Eamon O'Dea [aut, cre]
Maintainer: Eamon O'Dea <odea35@gmail.com>

Diff between spaero versions 0.4.0 dated 2018-12-16 and 0.5.0 dated 2019-05-24

 DESCRIPTION                       |    8 ++--
 MD5                               |   18 +++++-----
 NEWS.md                           |    6 ++-
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 build/vignette.rds                |binary
 inst/doc/spaero-introduction.Rmd  |   31 ++++++++++--------
 inst/doc/spaero-introduction.pdf  |binary
 tests/testthat/test-simulator.R   |   63 +++++++++++++++++++++++++++----------
 tests/testthat/test-stats.R       |   19 ++++++++++-
 vignettes/spaero-introduction.Rmd |   31 ++++++++++--------
 10 files changed, 158 insertions(+), 82 deletions(-)

More information about spaero at CRAN
Permanent link

Package restriktor updated to version 0.2-15 with previous version 0.1-80.911 dated 2018-10-31

Title: Restricted Statistical Estimation and Inference for Linear Models
Description: Allow for easy-to-use testing or evaluating of linear equality and inequality restrictions about parameters and effects in (generalized) linear statistical models.
Author: Leonard Vanbrabant [aut, cre], Yves Rosseel [ctb]
Maintainer: Leonard Vanbrabant <Leonard.Vanbrabant@Ugent.be>

Diff between restriktor versions 0.1-80.911 dated 2018-10-31 and 0.2-15 dated 2019-05-24

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Permanent link

Package phenofit updated to version 0.2.4 with previous version 0.2.3 dated 2019-05-23

Title: Extract Remote Sensing Vegetation Phenology
Description: The merits of 'TIMESAT' and 'phenopix' are adopted. Besides, a simple and growing season dividing method and a practical snow elimination method based on Whittaker were proposed. 7 curve fitting methods and 4 phenology extraction methods were provided. Parameters boundary are considered for every curve fitting methods according to their ecological meaning. And 'optimx' is used to select best optimization method for different curve fitting methods. Reference: Dongdong Kong, R package: A state-of-the-art Vegetation Phenology extraction package, phenofit version 0.2.3, <https://github.com/kongdd/phenofit>; Zhang, Q., Kong, D., Shi, P., Singh, V.P., Sun, P., 2018. Vegetation phenology on the Qinghai-Tibetan Plateau and its response to climate change (1982–2013). Agric. For. Meteorol. 248, 408–417. <doi:10.1016/j.agrformet.2017.10.026>.
Author: Dongdong Kong [aut, cre], Mingzhong Xiao [aut], Yongqiang Zhang [aut], Xihui Gu [aut], Jianjian Cui [aut]
Maintainer: Dongdong Kong <kongdd.sysu@gmail.com>

Diff between phenofit versions 0.2.3 dated 2019-05-23 and 0.2.4 dated 2019-05-24

 DESCRIPTION |   12 +++++++++---
 MD5         |    2 +-
 2 files changed, 10 insertions(+), 4 deletions(-)

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Package bivariate updated to version 0.4.1 with previous version 0.3.1 dated 2019-02-27

Title: Bivariate Probability Distributions
Description: Contains convenience functions for constructing, plotting and evaluating bivariate probability distributions, including their probability mass functions, probability density functions and cumulative distribution functions. Supports uniform (discrete and continuous), binomial, Poisson, categorical, normal, bimodal and Dirichlet (trivariate) distributions, and kernel smoothing and empirical cumulative distribution functions.
Author: Abby Spurdle
Maintainer: Abby Spurdle <spurdle.a@gmail.com>

Diff between bivariate versions 0.3.1 dated 2019-02-27 and 0.4.1 dated 2019-05-24

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More information about bivariate at CRAN
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Package wrapr updated to version 1.8.7 with previous version 1.8.6 dated 2019-04-02

Title: Wrap R Tools for Debugging and Parametric Programming
Description: Tools for writing and debugging R code. Provides: '%.>%' dot-pipe (an 'S3' configurable pipe), 'let()' (converts non-standard evaluation interfaces to parametric standard evaluation interfaces, inspired by 'gtools:strmacro()' and 'base::bquote()'), 'build_frame()'/'draw_frame()' ('data.frame' example tools), 'qc()' (quoting concatenate), ':=' (named map builder), and more.
Author: John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

Diff between wrapr versions 1.8.6 dated 2019-04-02 and 1.8.7 dated 2019-05-24

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Package RobinHood updated to version 1.0.7 with previous version 1.0.5 dated 2019-04-06

Title: Interface for the RobinHood.com No Commission Investing Platform
Description: Execute API calls to the RobinHood <https://robinhood.com> investing platform. Functionality includes accessing account data and current holdings, retrieving investment statistics and quotes, placing and canceling orders, getting market trading hours, searching investments by popular tag, and interacting with watch lists.
Author: Joseph Blubaugh
Maintainer: Joseph Blubaugh <jestonblu@gmail.com>

Diff between RobinHood versions 1.0.5 dated 2019-04-06 and 1.0.7 dated 2019-05-24

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Package Eagle updated to version 1.5.1 with previous version 1.5.0 dated 2019-05-17

Title: Multiple Locus Association Mapping on a Genome-Wide Scale
Description: An implementation of multiple-locus association mapping on a genome-wide scale. 'Eagle' can handle inbred and outbred study populations, populations of arbitrary unknown complexity, and data larger than the memory capacity of the computer. Since 'Eagle' is based on linear mixed models, it is best suited to the analysis of data on continuous traits. However, it can tolerate non-normal data. 'Eagle' reports, as its findings, the best set of snp in strongest association with a trait. For users unfamiliar with R, to perform an analysis, run 'OpenGUI()'. This opens a web browser to the menu-driven user interface for the input of data, and for performing genome-wide analysis.
Author: Andrew George [aut, cre], Joshua Bowden [ctb], Ryan Stephenson [ctb], Hyun Kang [ctb], Noah Zaitlen [ctb], Claire Wade [ctb], Andrew Kirby [ctb], David Heckerman [ctb], Mark Daly [ctb], Eleazar Eskin [ctb]
Maintainer: Andrew George <andrew.george@csiro.au>

Diff between Eagle versions 1.5.0 dated 2019-05-17 and 1.5.1 dated 2019-05-24

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More information about Eagle at CRAN
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Package datarobot updated to version 2.13.0 with previous version 2.12.1 dated 2019-02-27

Title: 'DataRobot' Predictive Modeling API
Description: For working with the 'DataRobot' predictive modeling platform's API <https://www.datarobot.com/>.
Author: Ron Pearson [aut], Zachary Deane-Mayer [aut], David Chudzicki [aut], Dallin Akagi [aut], Sergey Yurgenson [aut], Thakur Raj Anand [aut], Peter Hurford [aut]
Maintainer: Peter Hurford <api-maintainer@datarobot.com>

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 datarobot-2.13.0/datarobot/man/summary.listOfDataRobotTuningParameters.Rd          |only
 datarobot-2.13.0/datarobot/tests/testthat/test-CreateGroupPartition.R              |    4 
 datarobot-2.13.0/datarobot/tests/testthat/test-CreateRandomPartition.R             |    4 
 datarobot-2.13.0/datarobot/tests/testthat/test-CreateStratifiedPartition.R         |    4 
 datarobot-2.13.0/datarobot/tests/testthat/test-CreateUserPartition.R               |    4 
 datarobot-2.13.0/datarobot/tests/testthat/test-StartAutopilot.R                    |    6 
 datarobot-2.13.0/datarobot/vignettes/AdvancedTuning.Rmd                            |only
 datarobot-2.13.0/datarobot/vignettes/AdvancedTuning.md                             |only
 datarobot-2.13.0/datarobot/vignettes/DatetimePartitionedProjects.Rmd               |    4 
 datarobot-2.13.0/datarobot/vignettes/IntroductionToDataRobot.Rmd                   |   15 
 datarobot-2.13.0/datarobot/vignettes/Multiclass.Rmd                                |    6 
 datarobot-2.13.0/datarobot/vignettes/PartialDependence.Rmd                         |   12 
 datarobot-2.13.0/datarobot/vignettes/PredictionExplanations.Rmd                    |only
 datarobot-2.13.0/datarobot/vignettes/PredictionExplanations.rds                    |only
 datarobot-2.13.0/datarobot/vignettes/PredictionExplanationsExposure.rds            |only
 datarobot-2.13.0/datarobot/vignettes/PredictionExplanationsModelResults.rds        |only
 datarobot-2.13.0/datarobot/vignettes/PredictionExplanationsTestPredictions.rds     |only
 datarobot-2.13.0/datarobot/vignettes/TimeSeries.Rmd                                |  158 ++++-
 datarobot-2.13.0/datarobot/vignettes/TrainingPredictions.Rmd                       |   18 
 167 files changed, 1835 insertions(+), 939 deletions(-)

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