Title: Multilevel Joint Modelling Multiple Imputation
Description: Similarly to Schafer's package pan, jomo is a package for multilevel joint modelling multiple imputation.
Novel aspects of jomo are the possibility of handling binary and categorical data through latent normal variables and the option to use cluster-specific covariance matrices.
Author: Matteo Quartagno, James Carpenter
Maintainer: Matteo Quartagno <matteo.quartagno@lshtm.ac.uk>
Diff between jomo versions 0.2-0 dated 2015-03-24 and 1.1-0 dated 2015-06-12
jomo-0.2-0/jomo/src/jomo1mix2.c |only jomo-0.2-0/jomo/src/jomo1ranmix2.c |only jomo-1.1-0/jomo/DESCRIPTION | 12 - jomo-1.1-0/jomo/MD5 | 91 +++++++++---- jomo-1.1-0/jomo/NAMESPACE | 4 jomo-1.1-0/jomo/R/jomo1.MCMCchain.R |only jomo-1.1-0/jomo/R/jomo1.R |only jomo-1.1-0/jomo/R/jomo1cat.MCMCchain.R |only jomo-1.1-0/jomo/R/jomo1cat.R | 27 +--- jomo-1.1-0/jomo/R/jomo1con.MCMCchain.R |only jomo-1.1-0/jomo/R/jomo1con.R | 13 + jomo-1.1-0/jomo/R/jomo1mix.MCMCchain.R |only jomo-1.1-0/jomo/R/jomo1mix.R | 27 +--- jomo-1.1-0/jomo/R/jomo1ran.MCMCchain.R |only jomo-1.1-0/jomo/R/jomo1ran.R |only jomo-1.1-0/jomo/R/jomo1rancat.MCMCchain.R |only jomo-1.1-0/jomo/R/jomo1rancat.R | 34 +++-- jomo-1.1-0/jomo/R/jomo1rancathr.MCMCchain.R |only jomo-1.1-0/jomo/R/jomo1rancathr.R | 38 +++++ jomo-1.1-0/jomo/R/jomo1rancon.MCMCchain.R |only jomo-1.1-0/jomo/R/jomo1rancon.R | 20 ++- jomo-1.1-0/jomo/R/jomo1ranconhr.MCMCchain.R |only jomo-1.1-0/jomo/R/jomo1ranconhr.R | 26 +++ jomo-1.1-0/jomo/R/jomo1ranmix.MCMCchain.R |only jomo-1.1-0/jomo/R/jomo1ranmix.R | 34 +++-- jomo-1.1-0/jomo/R/jomo1ranmixhr.MCMCchain.R |only jomo-1.1-0/jomo/R/jomo1ranmixhr.R | 40 +++++- jomo-1.1-0/jomo/inst/CITATION | 12 - jomo-1.1-0/jomo/man/jomo-package.Rd | 8 - jomo-1.1-0/jomo/man/jomo1.MCMCchain.Rd |only jomo-1.1-0/jomo/man/jomo1.Rd |only jomo-1.1-0/jomo/man/jomo1cat.MCMCchain.Rd |only jomo-1.1-0/jomo/man/jomo1cat.Rd | 17 -- jomo-1.1-0/jomo/man/jomo1con.MCMCchain.Rd |only jomo-1.1-0/jomo/man/jomo1con.Rd | 4 jomo-1.1-0/jomo/man/jomo1mix.MCMCchain.Rd |only jomo-1.1-0/jomo/man/jomo1mix.Rd | 21 +-- jomo-1.1-0/jomo/man/jomo1ran.MCMCchain.Rd |only jomo-1.1-0/jomo/man/jomo1ran.Rd |only jomo-1.1-0/jomo/man/jomo1rancat.MCMCchain.Rd |only jomo-1.1-0/jomo/man/jomo1rancat.Rd | 20 +-- jomo-1.1-0/jomo/man/jomo1rancathr.MCMCchain.Rd |only jomo-1.1-0/jomo/man/jomo1rancathr.Rd | 18 +- jomo-1.1-0/jomo/man/jomo1rancon.MCMCchain.Rd |only jomo-1.1-0/jomo/man/jomo1rancon.Rd | 2 jomo-1.1-0/jomo/man/jomo1ranconhr.MCMCchain.Rd |only jomo-1.1-0/jomo/man/jomo1ranconhr.Rd | 10 - jomo-1.1-0/jomo/man/jomo1ranmix.MCMCchain.Rd |only jomo-1.1-0/jomo/man/jomo1ranmix.Rd | 20 --- jomo-1.1-0/jomo/man/jomo1ranmixhr.MCMCchain.Rd |only jomo-1.1-0/jomo/man/jomo1ranmixhr.Rd | 19 +- jomo-1.1-0/jomo/src/MCMCjomo1con.c |only jomo-1.1-0/jomo/src/MCMCjomo1mix.c |only jomo-1.1-0/jomo/src/MCMCjomo1rancon.c |only jomo-1.1-0/jomo/src/MCMCjomo1ranconhf.c |only jomo-1.1-0/jomo/src/MCMCjomo1ranconhr.c |only jomo-1.1-0/jomo/src/MCMCjomo1ranmix.c |only jomo-1.1-0/jomo/src/MCMCjomo1ranmixhf.c |only jomo-1.1-0/jomo/src/MCMCjomo1ranmixhr.c |only jomo-1.1-0/jomo/src/jomo1ranconhr.c | 14 +- jomo-1.1-0/jomo/src/jomo1ranmix.c | 24 --- jomo-1.1-0/jomo/src/jomo1ranmixhf.c |only jomo-1.1-0/jomo/src/jomo1ranmixhr.c | 164 +++++++++++++------------ jomo-1.1-0/jomo/src/pdflib.c | 22 +-- jomo-1.1-0/jomo/src/pdflib.h | 10 - 65 files changed, 437 insertions(+), 314 deletions(-)
Title: Temporal and Spatio-Temporal Modeling and Monitoring of Epidemic
Phenomena
Diff between surveillance versions 1.9-0 dated 2015-06-11 and 1.9-1 dated 2015-06-12
Description: Implementation of statistical methods for the modeling and
change-point detection in time series of counts, proportions and
categorical data, as well as for the modeling of continuous-time
epidemic phenomena, e.g., discrete-space setups such as the spatially
enriched Susceptible-Exposed-Infectious-Recovered (SEIR) models,
or continuous-space point process data such as the
occurrence of infectious diseases. Main focus is on outbreak
detection in count data time series originating from public health
surveillance of communicable diseases, but applications could just as well
originate from environmetrics, reliability engineering, econometrics or
social sciences.
Currently, the package contains implementations of many typical
outbreak detection procedures such as Farrington et al (1996),
Noufaily et al (2012) or the negative binomial LR-CUSUM method
described in Höhle and Paul (2008). A novel CUSUM approach combining
logistic and multinomial logistic modelling is also included.
Furthermore, inference methods for the retrospective infectious
disease models in Held et al (2005), Held et al (2006),
Paul et al (2008), Paul and Held (2011), Held and Paul (2012),
and Meyer and Held (2014) are provided.
Continuous self-exciting spatio-temporal point processes are
modeled through additive-multiplicative conditional
intensities as described in Höhle (2009) ('twinSIR', discrete
space) and Meyer et al (2012) ('twinstim', continuous space).
The package contains several real-world data sets, the ability
to simulate outbreak data, visualize the results of the
monitoring in temporal, spatial or spatio-temporal fashion.
Note: Using the 'boda' algorithm requires the 'INLA'
package, which should be installed automatically through the
specified Additional_repositories, if uninstalled dependencies
are also requested. As this might not work under OS X it
might be necessary to manually install the 'INLA' package as
specified at
Author: Michael Höhle [aut, cre, ths], Sebastian Meyer [aut],
Michaela Paul [aut], Leonhard Held [ctb, ths],
Thais Correa [ctb], Mathias Hofmann [ctb], Christian Lang [ctb],
Juliane Manitz [ctb], Andrea Riebler [ctb], Daniel Sabanés Bové [ctb],
Maëlle Salmon [ctb], Dirk Schumacher [ctb], Stefan Steiner [ctb],
Mikko Virtanen [ctb], Valentin Wimmer [ctb], R Core Team [ctb]
(A few code segments are modified versions of code from base R)
Maintainer: Michael Höhle
DESCRIPTION | 10 +-
MD5 | 32 ++++----
R/bodaDelay.R | 122 ++++++++++++++++++++-------------
R/hhh4.R | 7 -
R/hhh4_W.R | 16 ++--
R/hhh4_methods.R | 29 ++++---
R/zzz.R | 16 ++--
build/partial.rdb |binary
inst/NEWS.Rd | 15 ++++
inst/doc/glrnb.pdf |binary
inst/doc/hhh4.pdf |binary
inst/doc/surveillance.pdf |binary
man/bodaDelay.Rd | 71 -------------------
man/formatPval.Rd | 6 -
man/surveillance.options.Rd | 12 +--
tests/testthat/test-bodaDelay.R | 32 ++++----
tests/testthat/test-hhh4+derivatives.R | 4 -
17 files changed, 184 insertions(+), 188 deletions(-)
Title: Simulating Longitudinal Data with Causal Inference Applications
Description: A flexible tool for simulating complex longitudinal data using
structural equations, with emphasis on problems in causal inference.
Specify interventions and simulate from intervened data generating
distributions. Define and evaluate treatment-specific means, the average
treatment effects and coefficients from working marginal structural models.
User interface designed to facilitate the conduct of transparent and
reproducible simulation studies, and allows concise expression of complex
functional dependencies for a large number of time-varying nodes. See the
package vignette for more information, documentation and examples.
Author: Oleg Sofrygin [aut, cre],
Mark J. van der Laan [aut],
Romain Neugebauer [aut]
Maintainer: Oleg Sofrygin <oleg.sofrygin@gmail.com>
Diff between simcausal versions 0.1 dated 2015-05-16 and 0.2.0 dated 2015-06-12
simcausal-0.1/simcausal/man/node.depr.Rd |only simcausal-0.2.0/simcausal/DESCRIPTION | 20 simcausal-0.2.0/simcausal/MD5 | 118 +- simcausal-0.2.0/simcausal/NAMESPACE | 3 simcausal-0.2.0/simcausal/NEWS | 14 simcausal-0.2.0/simcausal/R/action_node_indexing.R | 10 simcausal-0.2.0/simcausal/R/distributions.R | 32 simcausal-0.2.0/simcausal/R/estimatetarget.r | 10 simcausal-0.2.0/simcausal/R/interface.r | 229 +--- simcausal-0.2.0/simcausal/R/node.R | 339 ++---- simcausal-0.2.0/simcausal/R/simcausal-package.r | 107 +- simcausal-0.2.0/simcausal/R/simcausal.r | 171 --- simcausal-0.2.0/simcausal/R/simulation.r | 80 - simcausal-0.2.0/simcausal/R/targetparam.r | 16 simcausal-0.2.0/simcausal/R/zzz.R |only simcausal-0.2.0/simcausal/README.md | 110 ++ simcausal-0.2.0/simcausal/build |only simcausal-0.2.0/simcausal/inst |only simcausal-0.2.0/simcausal/man/A.Rd | 8 simcausal-0.2.0/simcausal/man/DAG.empty.Rd | 2 simcausal-0.2.0/simcausal/man/DF.to.long.Rd | 12 simcausal-0.2.0/simcausal/man/DF.to.longDT.Rd | 8 simcausal-0.2.0/simcausal/man/N.Rd | 10 simcausal-0.2.0/simcausal/man/add.action.Rd | 18 simcausal-0.2.0/simcausal/man/add.nodes.Rd | 16 simcausal-0.2.0/simcausal/man/distr.list.Rd | 6 simcausal-0.2.0/simcausal/man/doLTCF.Rd | 62 + simcausal-0.2.0/simcausal/man/eval.target.Rd | 4 simcausal-0.2.0/simcausal/man/node.Rd | 122 +- simcausal-0.2.0/simcausal/man/parents.Rd | 2 simcausal-0.2.0/simcausal/man/plotDAG.Rd | 6 simcausal-0.2.0/simcausal/man/plotSurvEst.Rd | 22 simcausal-0.2.0/simcausal/man/print.DAG.Rd | 6 simcausal-0.2.0/simcausal/man/print.DAG.action.Rd | 6 simcausal-0.2.0/simcausal/man/print.DAG.node.Rd | 6 simcausal-0.2.0/simcausal/man/rbern.Rd | 10 simcausal-0.2.0/simcausal/man/rcategor.Rd | 8 simcausal-0.2.0/simcausal/man/rcategor.int.Rd | 8 simcausal-0.2.0/simcausal/man/rconst.Rd | 10 simcausal-0.2.0/simcausal/man/rdistr.template.Rd | 4 simcausal-0.2.0/simcausal/man/set.DAG.Rd | 165 ++- simcausal-0.2.0/simcausal/man/set.targetE.Rd | 6 simcausal-0.2.0/simcausal/man/set.targetMSM.Rd | 4 simcausal-0.2.0/simcausal/man/sim.Rd | 54 + simcausal-0.2.0/simcausal/man/simcausal.Rd | 74 + simcausal-0.2.0/simcausal/man/simfull.Rd | 14 simcausal-0.2.0/simcausal/man/simobs.Rd | 12 simcausal-0.2.0/simcausal/man/vecfun.add.Rd | 4 simcausal-0.2.0/simcausal/man/vecfun.all.print.Rd | 6 simcausal-0.2.0/simcausal/man/vecfun.print.Rd | 6 simcausal-0.2.0/simcausal/man/vecfun.remove.Rd | 4 simcausal-0.2.0/simcausal/man/vecfun.reset.Rd | 4 simcausal-0.2.0/simcausal/tests/RUnit/add.action.R |only simcausal-0.2.0/simcausal/tests/RUnit/runittests.R | 491 ++-------- simcausal-0.2.0/simcausal/tests/RUnit/set.DAG.R |only simcausal-0.2.0/simcausal/tests/RUnit/sim.impute.examples12.R |only simcausal-0.2.0/simcausal/vignettes |only 57 files changed, 1214 insertions(+), 1245 deletions(-)
Title: Web Application Framework for R
Description: Makes it incredibly easy to build interactive web
applications with R. Automatic "reactive" binding between inputs and
outputs and extensive pre-built widgets make it possible to build
beautiful, responsive, and powerful applications with minimal effort.
Author: Winston Chang [aut, cre],
Joe Cheng [aut],
JJ Allaire [aut],
Yihui Xie [aut],
Jonathan McPherson [aut],
RStudio [cph],
jQuery Foundation [cph] (jQuery library and jQuery UI library),
jQuery contributors [ctb, cph] (jQuery library; authors listed in
inst/www/shared/jquery-AUTHORS.txt),
jQuery UI contributors [ctb, cph] (jQuery UI library; authors listed in
inst/www/shared/jqueryui/1.10.4/AUTHORS.txt),
Mark Otto [ctb] (Bootstrap library),
Jacob Thornton [ctb] (Bootstrap library),
Bootstrap contributors [ctb] (Bootstrap library),
Twitter, Inc [cph] (Bootstrap library),
Alexander Farkas [ctb, cph] (html5shiv library),
Scott Jehl [ctb, cph] (Respond.js library),
Stefan Petre [ctb, cph] (Bootstrap-datepicker library),
Andrew Rowls [ctb, cph] (Bootstrap-datepicker library),
Dave Gandy [ctb, cph] (Font-Awesome font),
Brian Reavis [ctb, cph] (selectize.js library),
Kristopher Michael Kowal [ctb, cph] (es5-shim library),
es5-shim contributors [ctb, cph] (es5-shim library),
Denis Ineshin [ctb, cph] (ion.rangeSlider library),
SpryMedia Limited [ctb, cph] (DataTables library),
John Fraser [ctb, cph] (showdown.js library),
John Gruber [ctb, cph] (showdown.js library),
Ivan Sagalaev [ctb, cph] (highlight.js library),
R Core Team [ctb, cph] (tar implementation from R)
Maintainer: Winston Chang <winston@rstudio.com>
Diff between shiny versions 0.12.0 dated 2015-05-18 and 0.12.1 dated 2015-06-12
DESCRIPTION | 8 ++++---- MD5 | 18 +++++++++--------- NEWS | 11 +++++++++++ R/bootstrap.R | 3 --- R/shinywrappers.R | 10 +++------- inst/www/shared/shiny.js | 8 +++++--- inst/www/shared/shiny.js.map | 2 +- inst/www/shared/shiny.min.js | 6 +++--- inst/www/shared/shiny.min.js.map | 2 +- man/renderDataTable.Rd | 7 +++---- 10 files changed, 40 insertions(+), 35 deletions(-)
Title: Scale Functions for Visualization
Description: Graphical scales map data to aesthetics, and provide
methods for automatically determining breaks and labels
for axes and legends.
Author: Hadley Wickham [aut, cre],
RStudio [cph]
Maintainer: Hadley Wickham <hadley@rstudio.com>
Diff between scales versions 0.2.4 dated 2014-04-22 and 0.2.5 dated 2015-06-12
DESCRIPTION | 29 +++--- MD5 | 172 ++++++++++++++++++++------------------- NAMESPACE | 14 ++- NEWS | 44 +++++++++ R/RcppExports.R |only R/bounds.r | 21 ++-- R/colour-manip.r | 10 +- R/colour-mapping.r |only R/date-time.r | 24 ++--- R/formatter.r | 139 ++++++++++++++++++++++++++++--- R/pal-brewer.r | 33 ++++--- R/pal-hue.r | 2 R/pal-shape.r | 2 R/scales.r | 3 R/trans-date.r | 6 - R/trans-numeric.r | 5 - README.md | 2 build/partial.rdb |binary man/Range-class.Rd | 3 man/abs_area.Rd | 3 man/alpha.Rd | 3 man/area_pal.Rd | 3 man/as.trans.Rd | 3 man/asn_trans.Rd | 3 man/atanh_trans.Rd | 3 man/boxcox_trans.Rd | 3 man/brewer_pal.Rd | 9 +- man/cbreaks.Rd | 3 man/censor.Rd | 3 man/col2hcl.Rd | 7 - man/col_numeric.Rd |only man/colour_ramp.Rd |only man/comma_format.Rd | 11 ++ man/cscale.Rd | 3 man/date_breaks.Rd | 3 man/date_format.Rd | 8 + man/date_trans.Rd | 3 man/dichromat_pal.Rd | 3 man/discard.Rd | 3 man/div_gradient_pal.Rd | 3 man/dollar_format.Rd | 27 +++++- man/dscale.Rd | 3 man/exp_trans.Rd | 3 man/expand_range.Rd | 3 man/extended_breaks.Rd | 3 man/format_format.Rd | 3 man/fullseq.Rd | 3 man/gradient_n_pal.Rd | 3 man/grey_pal.Rd | 3 man/hue_pal.Rd | 8 + man/identity_pal.Rd | 3 man/identity_trans.Rd | 3 man/linetype_pal.Rd | 3 man/log1p_trans.Rd | 7 + man/log_breaks.Rd | 3 man/log_trans.Rd | 3 man/manual_pal.Rd | 3 man/math_format.Rd | 5 - man/muted.Rd | 3 man/ordinal_format.Rd |only man/package-scales.Rd | 3 man/parse_format.Rd | 5 - man/percent_format.Rd | 5 - man/pretty_breaks.Rd | 3 man/probability_trans.Rd | 3 man/reciprocal_trans.Rd | 3 man/rescale.Rd | 3 man/rescale_max.Rd | 3 man/rescale_mid.Rd | 3 man/rescale_none.Rd | 3 man/rescale_pal.Rd | 3 man/reverse_trans.Rd | 3 man/scientific_format.Rd | 5 - man/seq_gradient_pal.Rd | 3 man/shape_pal.Rd | 3 man/show_col.Rd | 9 +- man/sqrt_trans.Rd | 3 man/squish.Rd | 3 man/squish_infinite.Rd | 3 man/time_trans.Rd | 3 man/trans_breaks.Rd | 3 man/trans_format.Rd | 5 - man/trans_new.Rd | 3 man/trans_range.Rd | 3 man/unit_format.Rd |only man/wrap_format.Rd |only man/zero_range.Rd | 16 +-- src |only tests/testthat/test-colors.r |only tests/testthat/test-formatter.r | 111 ++++++++++++++++--------- tests/testthat/test-zero-range.r | 11 +- 91 files changed, 622 insertions(+), 283 deletions(-)
Title: Node Harvest for Regression and Classification
Description: Node harvest is a simple interpretable tree-like estimator for high-dimensional regression and classification. A few nodes are selected from an initially large ensemble of nodes, each associated with a positive weight. New observations can fall into one or several nodes and predictions are the weighted average response across all these groups. The package offers visualization of the estimator. Predictions can return the nodes a new observation fell into, along with the mean response of training observations in each node, offering a simple explanation of the prediction.
Author: Nicolai Meinshausen
Maintainer: Nicolai Meinshausen <meinshausen@stat.math.ethz.ch>
Diff between nodeHarvest versions 0.7-2 dated 2015-06-09 and 0.7-3 dated 2015-06-12
DESCRIPTION | 8 ++++---- MD5 | 8 ++++---- R/getI.R | 17 +++++++++++++---- R/nodeHarvest.R | 12 ++++++------ R/predict.nodeHarvest.R | 7 ++++--- 5 files changed, 31 insertions(+), 21 deletions(-)
Title: Machine Learning in R
Description: Interface to a large number of classification and regression
techniques, including machine-readable parameter descriptions. There is
also an experimental extension for survival analysis, clustering and
general, example-specific cost-sensitive learning. Generic resampling,
including cross-validation, bootstrapping and subsampling. Hyperparameter
tuning with modern optimization techniques, for single- and multi-objective
problems. Filter and wrapper methods for feature selection. Extension of
basic learners with additional operations common in machine learning, also
allowing for easy nested resampling. Most operations can be parallelized.
Author: Bernd Bischl [aut, cre],
Michel Lang [aut],
Jakob Richter [aut],
Jakob Bossek [aut],
Leonard Judt [aut],
Tobias Kuehn [aut],
Erich Studerus [aut],
Lars Kotthoff [aut],
Zachary Jones [ctb]
Maintainer: Bernd Bischl <bernd_bischl@gmx.net>
Diff between mlr versions 2.3 dated 2015-02-04 and 2.4 dated 2015-06-12
mlr-2.3/mlr/R/RLearner_classif_xgboost.R |only mlr-2.3/mlr/R/RLearner_regr_xgboost.R |only mlr-2.3/mlr/R/getFilterValues.R |only mlr-2.3/mlr/R/plotFilterValues.R |only mlr-2.3/mlr/R/plotROCRCurves.R |only mlr-2.3/mlr/R/plotThreshVsPerf.R |only mlr-2.3/mlr/R/showHyperPars.R |only mlr-2.3/mlr/man/showHyperPars.Rd |only mlr-2.3/mlr/tests/testthat/test_base_plotThreshVsPerf.R |only mlr-2.3/mlr/tests/testthat/test_base_showHyperPars.R |only mlr-2.3/mlr/tests/testthat/test_classif_xgboost.R |only mlr-2.3/mlr/tests/testthat/test_regr_IBk.R |only mlr-2.3/mlr/tests/testthat/test_regr_bartMachine.R |only mlr-2.3/mlr/tests/testthat/test_regr_bcart.R |only mlr-2.3/mlr/tests/testthat/test_regr_bdk.R |only mlr-2.3/mlr/tests/testthat/test_regr_bgp.R |only mlr-2.3/mlr/tests/testthat/test_regr_bgpllm.R |only mlr-2.3/mlr/tests/testthat/test_regr_blackboost.R |only mlr-2.3/mlr/tests/testthat/test_regr_blm.R |only mlr-2.3/mlr/tests/testthat/test_regr_brnn.R |only mlr-2.3/mlr/tests/testthat/test_regr_btgp.R |only mlr-2.3/mlr/tests/testthat/test_regr_btgpllm.R |only mlr-2.3/mlr/tests/testthat/test_regr_btlm.R |only mlr-2.3/mlr/tests/testthat/test_regr_cforest.R |only mlr-2.3/mlr/tests/testthat/test_regr_crs.R |only mlr-2.3/mlr/tests/testthat/test_regr_ctree.R |only mlr-2.3/mlr/tests/testthat/test_regr_cubist.R |only mlr-2.3/mlr/tests/testthat/test_regr_earth.R |only mlr-2.3/mlr/tests/testthat/test_regr_elmNN.R |only mlr-2.3/mlr/tests/testthat/test_regr_extraTrees.R |only mlr-2.3/mlr/tests/testthat/test_regr_fnn.R |only mlr-2.3/mlr/tests/testthat/test_regr_gbm.R |only mlr-2.3/mlr/tests/testthat/test_regr_glmnet.R |only mlr-2.3/mlr/tests/testthat/test_regr_kknn.R |only mlr-2.3/mlr/tests/testthat/test_regr_km.R |only mlr-2.3/mlr/tests/testthat/test_regr_ksvm.R |only mlr-2.3/mlr/tests/testthat/test_regr_laGP.R |only mlr-2.3/mlr/tests/testthat/test_regr_lm.R |only mlr-2.3/mlr/tests/testthat/test_regr_mob.R |only mlr-2.3/mlr/tests/testthat/test_regr_penalized_lasso.R |only mlr-2.3/mlr/tests/testthat/test_regr_penalized_ridge.R |only mlr-2.3/mlr/tests/testthat/test_regr_plsr.R |only mlr-2.3/mlr/tests/testthat/test_regr_randomForest.R |only mlr-2.3/mlr/tests/testthat/test_regr_randomForestSRC.R |only mlr-2.3/mlr/tests/testthat/test_regr_randomForest_se.R |only mlr-2.3/mlr/tests/testthat/test_regr_rpart.R |only mlr-2.3/mlr/tests/testthat/test_regr_rsm.R |only mlr-2.3/mlr/tests/testthat/test_regr_svm.R |only mlr-2.3/mlr/tests/testthat/test_regr_xgboost.R |only mlr-2.3/mlr/tests/testthat/test_regr_xyf.R |only mlr-2.3/mlr/tests/testthat/test_tune_tuneIraceR.R |only mlr-2.4/mlr/DESCRIPTION | 44 mlr-2.4/mlr/LICENSE | 2 mlr-2.4/mlr/MD5 | 633 ++++------ mlr-2.4/mlr/NAMESPACE | 72 - mlr-2.4/mlr/NEWS | 60 mlr-2.4/mlr/R/BaggingWrapper.R | 2 mlr-2.4/mlr/R/BaseWrapper.R | 13 mlr-2.4/mlr/R/BenchmarkResult_operators.R | 4 mlr-2.4/mlr/R/ChainModel.R | 17 mlr-2.4/mlr/R/ClassifTask.R | 3 mlr-2.4/mlr/R/CostSensClassifWrapper.R | 3 mlr-2.4/mlr/R/CostSensRegrWrapper.R | 5 mlr-2.4/mlr/R/CostSensWeightedPairsLearner.R | 3 mlr-2.4/mlr/R/DownsampleWrapper.R | 2 mlr-2.4/mlr/R/FeatSelControl.R | 6 mlr-2.4/mlr/R/Filter.R | 24 mlr-2.4/mlr/R/FilterWrapper.R | 1 mlr-2.4/mlr/R/HomogeneousEnsemble.R | 4 mlr-2.4/mlr/R/Learner.R | 16 mlr-2.4/mlr/R/ModelMultiplexer.R | 2 mlr-2.4/mlr/R/MulticlassWrapper.R | 5 mlr-2.4/mlr/R/OptWrapper.R | 2 mlr-2.4/mlr/R/OverBaggingWrapper.R | 2 mlr-2.4/mlr/R/OverUndersampleWrapper.R | 5 mlr-2.4/mlr/R/PreprocWrapper.R | 4 mlr-2.4/mlr/R/PreprocWrapperCaret.R | 8 mlr-2.4/mlr/R/RLearner.R | 2 mlr-2.4/mlr/R/RLearner_classif_LiblineaRBinary.R | 2 mlr-2.4/mlr/R/RLearner_classif_LiblineaRLogReg.R | 2 mlr-2.4/mlr/R/RLearner_classif_LiblineaRMultiClass.R | 2 mlr-2.4/mlr/R/RLearner_classif_ada.R | 17 mlr-2.4/mlr/R/RLearner_classif_bdk.R | 2 mlr-2.4/mlr/R/RLearner_classif_blackboost.R | 2 mlr-2.4/mlr/R/RLearner_classif_bst.R |only mlr-2.4/mlr/R/RLearner_classif_cforest.R | 4 mlr-2.4/mlr/R/RLearner_classif_ctree.R | 2 mlr-2.4/mlr/R/RLearner_classif_geoDA.R | 2 mlr-2.4/mlr/R/RLearner_classif_glmnet.R | 2 mlr-2.4/mlr/R/RLearner_classif_hdrda.R |only mlr-2.4/mlr/R/RLearner_classif_kknn.R | 4 mlr-2.4/mlr/R/RLearner_classif_linDA.R | 2 mlr-2.4/mlr/R/RLearner_classif_mda.R | 14 mlr-2.4/mlr/R/RLearner_classif_nodeHarvest.R |only mlr-2.4/mlr/R/RLearner_classif_pamr.R |only mlr-2.4/mlr/R/RLearner_classif_qda.R | 2 mlr-2.4/mlr/R/RLearner_classif_quaDA.R | 2 mlr-2.4/mlr/R/RLearner_classif_rFerns.R |only mlr-2.4/mlr/R/RLearner_classif_randomForest.R | 7 mlr-2.4/mlr/R/RLearner_classif_randomForestSRC.R | 2 mlr-2.4/mlr/R/RLearner_classif_rrlda.R | 2 mlr-2.4/mlr/R/RLearner_classif_sparseLDA.R |only mlr-2.4/mlr/R/RLearner_classif_xyf.R | 4 mlr-2.4/mlr/R/RLearner_regr_bcart.R | 2 mlr-2.4/mlr/R/RLearner_regr_bdk.R | 2 mlr-2.4/mlr/R/RLearner_regr_blackBoost.R | 4 mlr-2.4/mlr/R/RLearner_regr_bst.R |only mlr-2.4/mlr/R/RLearner_regr_btgp.R | 2 mlr-2.4/mlr/R/RLearner_regr_btgpllm.R | 2 mlr-2.4/mlr/R/RLearner_regr_btlm.R | 2 mlr-2.4/mlr/R/RLearner_regr_cforest.R | 4 mlr-2.4/mlr/R/RLearner_regr_ctree.R | 2 mlr-2.4/mlr/R/RLearner_regr_frbs.R |only mlr-2.4/mlr/R/RLearner_regr_kknn.R | 4 mlr-2.4/mlr/R/RLearner_regr_km.R | 1 mlr-2.4/mlr/R/RLearner_regr_laGP.R | 1 mlr-2.4/mlr/R/RLearner_regr_nodeHarvest.R |only mlr-2.4/mlr/R/RLearner_regr_slim.R |only mlr-2.4/mlr/R/RLearner_regr_xyf.R | 2 mlr-2.4/mlr/R/RLearner_surv_cforest.R | 4 mlr-2.4/mlr/R/ResampleResult.R | 4 mlr-2.4/mlr/R/ResampleResult_operators.R |only mlr-2.4/mlr/R/SMOTEWrapper.R | 2 mlr-2.4/mlr/R/StackedLearner.R | 21 mlr-2.4/mlr/R/Task_operators.R | 40 mlr-2.4/mlr/R/TuneControl.R | 8 mlr-2.4/mlr/R/TuneControlDesign.R |only mlr-2.4/mlr/R/TuneWrapper.R | 2 mlr-2.4/mlr/R/WeightedClassesWrapper.R | 2 mlr-2.4/mlr/R/WrappedModel.R | 8 mlr-2.4/mlr/R/aggregations.R | 4 mlr-2.4/mlr/R/aucc.R |only mlr-2.4/mlr/R/benchmark.R | 7 mlr-2.4/mlr/R/capLargeValues.R | 10 mlr-2.4/mlr/R/checkPrediction.R | 4 mlr-2.4/mlr/R/checkTunerParset.R | 2 mlr-2.4/mlr/R/filterFeatures.R | 29 mlr-2.4/mlr/R/generateFilterValues.R |only mlr-2.4/mlr/R/generateLearningCurve.R |only mlr-2.4/mlr/R/generateROCRCurves.R |only mlr-2.4/mlr/R/generateThreshVsPerf.R |only mlr-2.4/mlr/R/getConfMatrix.R | 2 mlr-2.4/mlr/R/getNestedTuneResults.R |only mlr-2.4/mlr/R/getParamSet.R | 9 mlr-2.4/mlr/R/helpers.R | 2 mlr-2.4/mlr/R/listLearners.R | 5 mlr-2.4/mlr/R/logFunOpt.R | 15 mlr-2.4/mlr/R/measures.R | 51 mlr-2.4/mlr/R/normalizeFeatures.R | 33 mlr-2.4/mlr/R/plotTuneMultiCritResult.R | 37 mlr-2.4/mlr/R/plotViperCharts.R | 2 mlr-2.4/mlr/R/predictLearner.R | 2 mlr-2.4/mlr/R/resample.R | 37 mlr-2.4/mlr/R/resample_convenience.R | 28 mlr-2.4/mlr/R/selectFeaturesSequential.R | 10 mlr-2.4/mlr/R/setPredictThreshold.R | 2 mlr-2.4/mlr/R/tuneCMAES.R | 2 mlr-2.4/mlr/R/tuneDesign.R |only mlr-2.4/mlr/R/tuneIrace.R | 14 mlr-2.4/mlr/R/tuneParams.R | 1 mlr-2.4/mlr/R/utils_opt.R | 4 mlr-2.4/mlr/build |only mlr-2.4/mlr/data/pid.task.RData |binary mlr-2.4/mlr/inst/doc |only mlr-2.4/mlr/inst/makeData.R | 2 mlr-2.4/mlr/man/Aggregation.Rd | 2 mlr-2.4/mlr/man/BenchmarkResult.Rd | 2 mlr-2.4/mlr/man/FailureModel.Rd | 2 mlr-2.4/mlr/man/FeatSelControl.Rd | 8 mlr-2.4/mlr/man/FeatSelResult.Rd | 2 mlr-2.4/mlr/man/FilterValues.Rd | 18 mlr-2.4/mlr/man/LearnerProperties.Rd | 4 mlr-2.4/mlr/man/LearningCurveData.Rd |only mlr-2.4/mlr/man/Prediction.Rd | 2 mlr-2.4/mlr/man/RLearner.Rd | 2 mlr-2.4/mlr/man/ResamplePrediction.Rd | 5 mlr-2.4/mlr/man/ResampleResult.Rd | 8 mlr-2.4/mlr/man/Task.Rd | 2 mlr-2.4/mlr/man/TaskDesc.Rd | 2 mlr-2.4/mlr/man/TuneControl.Rd | 24 mlr-2.4/mlr/man/TuneMultiCritControl.Rd | 11 mlr-2.4/mlr/man/TuneMultiCritResult.Rd | 2 mlr-2.4/mlr/man/TuneResult.Rd | 2 mlr-2.4/mlr/man/aggregations.Rd | 2 mlr-2.4/mlr/man/agri.task.Rd | 2 mlr-2.4/mlr/man/analyzeFeatSelResult.Rd | 2 mlr-2.4/mlr/man/asROCRPrediction.Rd | 10 mlr-2.4/mlr/man/bc.task.Rd | 2 mlr-2.4/mlr/man/benchmark.Rd | 11 mlr-2.4/mlr/man/bh.task.Rd | 2 mlr-2.4/mlr/man/capLargeValues.Rd | 12 mlr-2.4/mlr/man/configureMlr.Rd | 2 mlr-2.4/mlr/man/costiris.task.Rd | 2 mlr-2.4/mlr/man/createDummyFeatures.Rd | 2 mlr-2.4/mlr/man/crossover.Rd | 2 mlr-2.4/mlr/man/downsample.Rd | 2 mlr-2.4/mlr/man/dropFeatures.Rd | 2 mlr-2.4/mlr/man/estimateResidualVariance.Rd | 2 mlr-2.4/mlr/man/filterFeatures.Rd | 11 mlr-2.4/mlr/man/generateFilterValuesData.Rd |only mlr-2.4/mlr/man/generateLearningCurveData.Rd |only mlr-2.4/mlr/man/generateROCRCurvesData.Rd |only mlr-2.4/mlr/man/generateThreshVsPerfData.Rd |only mlr-2.4/mlr/man/getBMRAggrPerformances.Rd | 2 mlr-2.4/mlr/man/getBMRFeatSelResults.Rd | 2 mlr-2.4/mlr/man/getBMRFilteredFeatures.Rd | 2 mlr-2.4/mlr/man/getBMRLearnerIds.Rd | 2 mlr-2.4/mlr/man/getBMRPerformances.Rd | 2 mlr-2.4/mlr/man/getBMRPredictions.Rd | 2 mlr-2.4/mlr/man/getBMRTaskIds.Rd | 2 mlr-2.4/mlr/man/getBMRTuneResults.Rd | 2 mlr-2.4/mlr/man/getConfMatrix.Rd | 2 mlr-2.4/mlr/man/getFailureModelMsg.Rd | 2 mlr-2.4/mlr/man/getFeatSelResult.Rd | 2 mlr-2.4/mlr/man/getFilterValues.Rd | 25 mlr-2.4/mlr/man/getFilteredFeatures.Rd | 7 mlr-2.4/mlr/man/getHomogeneousEnsembleModels.Rd | 2 mlr-2.4/mlr/man/getHyperPars.Rd | 4 mlr-2.4/mlr/man/getLearnerModel.Rd | 2 mlr-2.4/mlr/man/getMlrOptions.Rd | 2 mlr-2.4/mlr/man/getNestedTuneResultsOptPathDf.Rd |only mlr-2.4/mlr/man/getNestedTuneResultsX.Rd |only mlr-2.4/mlr/man/getParamSet.Rd | 4 mlr-2.4/mlr/man/getProbabilities.Rd | 4 mlr-2.4/mlr/man/getRRPredictions.Rd |only mlr-2.4/mlr/man/getStackedBaseLearnerPredictions.Rd | 2 mlr-2.4/mlr/man/getTaskCosts.Rd | 3 mlr-2.4/mlr/man/getTaskData.Rd | 6 mlr-2.4/mlr/man/getTaskDescription.Rd | 3 mlr-2.4/mlr/man/getTaskFeatureNames.Rd | 3 mlr-2.4/mlr/man/getTaskFormula.Rd | 15 mlr-2.4/mlr/man/getTaskId.Rd | 4 mlr-2.4/mlr/man/getTaskNFeats.Rd | 4 mlr-2.4/mlr/man/getTaskSize.Rd |only mlr-2.4/mlr/man/getTaskTargetNames.Rd | 6 mlr-2.4/mlr/man/getTaskTargets.Rd | 3 mlr-2.4/mlr/man/getTaskType.Rd | 3 mlr-2.4/mlr/man/getTuneResult.Rd | 5 mlr-2.4/mlr/man/imputations.Rd | 2 mlr-2.4/mlr/man/impute.Rd | 2 mlr-2.4/mlr/man/iris.task.Rd | 2 mlr-2.4/mlr/man/isFailureModel.Rd | 2 mlr-2.4/mlr/man/joinClassLevels.Rd | 2 mlr-2.4/mlr/man/learnerArgsToControl.Rd | 2 mlr-2.4/mlr/man/learners.Rd | 2 mlr-2.4/mlr/man/listFilterMethods.Rd | 2 mlr-2.4/mlr/man/listLearners.Rd | 6 mlr-2.4/mlr/man/listMeasures.Rd | 2 mlr-2.4/mlr/man/lung.task.Rd | 2 mlr-2.4/mlr/man/makeAggregation.Rd | 2 mlr-2.4/mlr/man/makeBaggingWrapper.Rd | 2 mlr-2.4/mlr/man/makeCostMeasure.Rd | 21 mlr-2.4/mlr/man/makeCostSensClassifWrapper.Rd | 2 mlr-2.4/mlr/man/makeCostSensRegrWrapper.Rd | 2 mlr-2.4/mlr/man/makeCostSensWeightedPairsWrapper.Rd | 2 mlr-2.4/mlr/man/makeCustomResampledMeasure.Rd | 21 mlr-2.4/mlr/man/makeDownsampleWrapper.Rd | 2 mlr-2.4/mlr/man/makeFeatSelWrapper.Rd | 2 mlr-2.4/mlr/man/makeFilter.Rd | 2 mlr-2.4/mlr/man/makeFilterWrapper.Rd | 7 mlr-2.4/mlr/man/makeFixedHoldoutInstance.Rd | 2 mlr-2.4/mlr/man/makeImputeMethod.Rd | 2 mlr-2.4/mlr/man/makeImputeWrapper.Rd | 2 mlr-2.4/mlr/man/makeLearner.Rd | 10 mlr-2.4/mlr/man/makeMeasure.Rd | 21 mlr-2.4/mlr/man/makeModelMultiplexer.Rd | 5 mlr-2.4/mlr/man/makeModelMultiplexerParamSet.Rd | 5 mlr-2.4/mlr/man/makeMulticlassWrapper.Rd | 2 mlr-2.4/mlr/man/makeOverBaggingWrapper.Rd | 2 mlr-2.4/mlr/man/makePreprocWrapper.Rd | 2 mlr-2.4/mlr/man/makePreprocWrapperCaret.Rd | 6 mlr-2.4/mlr/man/makeResampleDesc.Rd | 5 mlr-2.4/mlr/man/makeResampleInstance.Rd | 5 mlr-2.4/mlr/man/makeSMOTEWrapper.Rd | 2 mlr-2.4/mlr/man/makeStackedLearner.Rd | 2 mlr-2.4/mlr/man/makeTuneWrapper.Rd | 7 mlr-2.4/mlr/man/makeUndersampleWrapper.Rd | 2 mlr-2.4/mlr/man/makeWeightedClassesWrapper.Rd | 2 mlr-2.4/mlr/man/makeWrappedModel.Rd | 2 mlr-2.4/mlr/man/measures.Rd | 11 mlr-2.4/mlr/man/mergeSmallFactorLevels.Rd | 2 mlr-2.4/mlr/man/mtcars.task.Rd | 2 mlr-2.4/mlr/man/normalizeFeatures.Rd | 35 mlr-2.4/mlr/man/oversample.Rd | 2 mlr-2.4/mlr/man/performance.Rd | 21 mlr-2.4/mlr/man/pid.task.Rd | 2 mlr-2.4/mlr/man/plotFilterValues.Rd | 35 mlr-2.4/mlr/man/plotFilterValuesGGVIS.Rd |only mlr-2.4/mlr/man/plotLearnerPrediction.Rd | 2 mlr-2.4/mlr/man/plotLearningCurve.Rd |only mlr-2.4/mlr/man/plotLearningCurveGGVIS.Rd |only mlr-2.4/mlr/man/plotROCRCurves.Rd | 104 - mlr-2.4/mlr/man/plotROCRCurvesGGVIS.Rd |only mlr-2.4/mlr/man/plotThreshVsPerf.Rd | 49 mlr-2.4/mlr/man/plotThreshVsPerfGGVIS.Rd |only mlr-2.4/mlr/man/plotTuneMultiCritResult.Rd | 5 mlr-2.4/mlr/man/plotTuneMultiCritResultGGVIS.Rd |only mlr-2.4/mlr/man/plotViperCharts.Rd | 6 mlr-2.4/mlr/man/predict.WrappedModel.Rd | 4 mlr-2.4/mlr/man/predictLearner.Rd | 2 mlr-2.4/mlr/man/reimpute.Rd | 2 mlr-2.4/mlr/man/removeConstantFeatures.Rd | 2 mlr-2.4/mlr/man/removeHyperPars.Rd | 4 mlr-2.4/mlr/man/resample.Rd | 36 mlr-2.4/mlr/man/selectFeatures.Rd | 2 mlr-2.4/mlr/man/setAggregation.Rd | 2 mlr-2.4/mlr/man/setHyperPars.Rd | 4 mlr-2.4/mlr/man/setHyperPars2.Rd | 2 mlr-2.4/mlr/man/setId.Rd | 4 mlr-2.4/mlr/man/setPredictThreshold.Rd | 6 mlr-2.4/mlr/man/setPredictType.Rd | 7 mlr-2.4/mlr/man/setThreshold.Rd | 2 mlr-2.4/mlr/man/smote.Rd | 2 mlr-2.4/mlr/man/sonar.task.Rd | 2 mlr-2.4/mlr/man/subsetTask.Rd | 5 mlr-2.4/mlr/man/summarizeColumns.Rd | 2 mlr-2.4/mlr/man/summarizeLevels.Rd | 2 mlr-2.4/mlr/man/train.Rd | 2 mlr-2.4/mlr/man/trainLearner.Rd | 2 mlr-2.4/mlr/man/tuneParams.Rd | 5 mlr-2.4/mlr/man/tuneParamsMultiCrit.Rd | 3 mlr-2.4/mlr/man/tuneThreshold.Rd | 5 mlr-2.4/mlr/man/wpbc.task.Rd | 2 mlr-2.4/mlr/tests/testthat/Rplots.pdf |binary mlr-2.4/mlr/tests/testthat/helper_objects.R | 2 mlr-2.4/mlr/tests/testthat/test_base_BaseWrapper.R | 2 mlr-2.4/mlr/tests/testthat/test_base_Learner.R | 2 mlr-2.4/mlr/tests/testthat/test_base_PreprocWrapperCaret.R | 6 mlr-2.4/mlr/tests/testthat/test_base_SupervisedTask.R | 9 mlr-2.4/mlr/tests/testthat/test_base_TuneWrapper.R | 29 mlr-2.4/mlr/tests/testthat/test_base_UnsupervisedTask.R | 3 mlr-2.4/mlr/tests/testthat/test_base_clustering.R | 13 mlr-2.4/mlr/tests/testthat/test_base_costsens.R | 4 mlr-2.4/mlr/tests/testthat/test_base_generateLearningCurve.R |only mlr-2.4/mlr/tests/testthat/test_base_generateThreshVsPerf.R |only mlr-2.4/mlr/tests/testthat/test_base_getConfMatrix.R | 9 mlr-2.4/mlr/tests/testthat/test_base_getParamSet.R | 2 mlr-2.4/mlr/tests/testthat/test_base_getTaskFormula.R |only mlr-2.4/mlr/tests/testthat/test_base_measures.R | 19 mlr-2.4/mlr/tests/testthat/test_base_rocr.R | 25 mlr-2.4/mlr/tests/testthat/test_base_selectFeatures.R | 10 mlr-2.4/mlr/tests/testthat/test_classif_LiblineaRBinary.R | 2 mlr-2.4/mlr/tests/testthat/test_classif_LiblineaRLogReg.R | 2 mlr-2.4/mlr/tests/testthat/test_classif_LiblineaRMultiClass.R | 4 mlr-2.4/mlr/tests/testthat/test_classif_bdk.R | 2 mlr-2.4/mlr/tests/testthat/test_classif_bst.R |only mlr-2.4/mlr/tests/testthat/test_classif_hdrda.R |only mlr-2.4/mlr/tests/testthat/test_classif_knn.R | 2 mlr-2.4/mlr/tests/testthat/test_classif_mda.R | 8 mlr-2.4/mlr/tests/testthat/test_classif_nodeHarvest.R |only mlr-2.4/mlr/tests/testthat/test_classif_pamr.R |only mlr-2.4/mlr/tests/testthat/test_classif_rFerns.R |only mlr-2.4/mlr/tests/testthat/test_classif_randomForest.R | 2 mlr-2.4/mlr/tests/testthat/test_classif_sparseLDA.R |only mlr-2.4/mlr/tests/testthat/test_classif_xyf.R | 4 mlr-2.4/mlr/tests/testthat/test_cluster_cmeans.R | 2 mlr-2.4/mlr/tests/testthat/test_cluster_kmeans.R | 2 mlr-2.4/mlr/tests/testthat/test_featsel_analyzeFeatSelResult.R | 11 mlr-2.4/mlr/tests/testthat/test_featsel_filterFeatures.R | 44 mlr-2.4/mlr/tests/testthat/test_learners_all.R | 125 + mlr-2.4/mlr/tests/testthat/test_learners_classiflabelswitch.R | 10 mlr-2.4/mlr/tests/testthat/test_parallel_all.R | 36 mlr-2.4/mlr/tests/testthat/test_tune_tuneDesign.R |only mlr-2.4/mlr/tests/testthat/test_tune_tuneIrace.R |only mlr-2.4/mlr/tests/testthat/test_tune_tuneParamsMultiCrit.R | 2 mlr-2.4/mlr/vignettes |only 366 files changed, 1676 insertions(+), 1029 deletions(-)
Title: Data Analysis of Liquid-Liquid Systems
Description: Analyses experimental data from liquid-liquid phase diagrams and provide a simple way to obtain its parameters and a simplified report. Designed initially to analyse Aqueous Two-Phases Systems, the package will include (every other update) new functions in order to comprise useful tools in liquid-liquid analysis.
Author: Diego F Coelho <diegofcoelho@gmail.com>
Maintainer: Diego F Coelho <diegofcoelho@gmail.com>
Diff between LLSR versions 0.0.1.9225 dated 2015-04-30 and 0.0.1.9425 dated 2015-06-12
DESCRIPTION | 10 - MD5 | 72 +++++------ NAMESPACE | 52 ++++---- R/AQSearch.CAS.R | 80 ++++++------ R/AQSearch.R | 162 ++++++++++++------------- R/AQSearchUtils.R | 38 ++--- R/AQSys.R | 260 ++++++++++++++++++++-------------------- R/AQSys.err.R | 90 ++++++------- R/AQSys.gsnchk.R | 140 ++++++++++----------- R/AQSys.mathDesc.R | 88 ++++++------- R/AQSys.mrchk.R | 192 ++++++++++++++--------------- R/AQSys.mrgsn.R | 154 +++++++++++------------ R/AQSysCurve.R | 116 +++++++++--------- R/AQSysDB.R | 277 +++++++++++++++++++++---------------------- R/AQSysFormulas.R | 128 +++++++++---------- R/AQSysUtils.R | 101 ++++++++++----- R/LLSRUtils.R | 21 +-- R/LLSRxy.R | 42 +++--- R/datasets.R | 38 ++--- README.md | 8 - man/AQSearch.CAS.Rd | 48 +++---- man/AQSearch.Rd | 94 +++++++------- man/AQSys.Rd | 98 +++++++-------- man/AQSys.crpt.Rd | 70 +++++----- man/AQSys.gsnchk.Rd | 112 ++++++++--------- man/AQSys.plot.Rd | 130 ++++++++++---------- man/AQSys.tielines.Rd | 86 ++++++------- man/AQSysBancroft.Rd | 80 ++++++------ man/AQSysCurve.Rd | 122 +++++++++--------- man/AQSysDB.Rd | 48 +++---- man/AQSysList.Rd | 24 +-- man/AQSysOthmer.Rd | 80 ++++++------ man/LLSR.info.Rd | 24 +-- man/LLSRxy.Rd | 62 ++++----- man/peg4kslt.Rd | 52 ++++---- tests/testthat.R | 8 - tests/testthat/testMainFns.R | 26 ++-- 37 files changed, 1635 insertions(+), 1598 deletions(-)
Title: Doubly Robust Generalized Estimating Equations
Description: Fit restricted mean models for the conditional association
between an exposure and an outcome, given covariates. Three methods
are implemented: O-estimation, where a nuisance model for the
association between the covariates and the outcome is used;
E-estimation where a nuisance model for the association
between the covariates and the exposure is used, and doubly robust (DR)
estimation where both nuisance models are used. In DR-estimation,
the estimates will be consistent when at least one of the nuisance
models is correctly specified, not necessarily both.
Author: Johan Zetterqvist <johan.zetterqvist@ki.se> , Arvid Sjölander <arvid.sjolander@ki.se> with contributions from Alexander Ploner.
Maintainer: Johan Zetterqvist <johan.zetterqvist@ki.se>
Diff between drgee versions 1.1.2 dated 2015-05-19 and 1.1.3 dated 2015-06-12
DESCRIPTION | 8 +-- MD5 | 9 ++-- R/drgeeData.R | 128 +++++++++++++++++++++++++++++++++++++++++++++------------- R/eFit.R | 6 -- R/geeFit.R | 2 inst |only 6 files changed, 111 insertions(+), 42 deletions(-)
Title: Bayesian Inference for Marketing/Micro-Econometrics
Description: Covers many important models used
in marketing and micro-econometrics applications.
The package includes:
Bayes Regression (univariate or multivariate dep var),
Bayes Seemingly Unrelated Regression (SUR),
Binary and Ordinal Probit,
Multinomial Logit (MNL) and Multinomial Probit (MNP),
Multivariate Probit,
Negative Binomial (Poisson) Regression,
Multivariate Mixtures of Normals (including clustering),
Dirichlet Process Prior Density Estimation with normal base,
Hierarchical Linear Models with normal prior and covariates,
Hierarchical Linear Models with a mixture of normals prior and covariates,
Hierarchical Multinomial Logits with a mixture of normals prior
and covariates,
Hierarchical Multinomial Logits with a Dirichlet Process prior and covariates,
Hierarchical Negative Binomial Regression Models,
Bayesian analysis of choice-based conjoint data,
Bayesian treatment of linear instrumental variables models,
Analysis of Multivariate Ordinal survey data with scale
usage heterogeneity (as in Rossi et al, JASA (01)),
Bayesian Analysis of Aggregate Random Coefficient Logit Models as in BLP (see
Jiang, Manchanda, Rossi 2009)
For further reference, consult our book, Bayesian Statistics and
Marketing by Rossi, Allenby and McCulloch (Wiley 2005) and Bayesian Non- and Semi-Parametric
Methods and Applications (Princeton U Press 2014).
Author: Peter Rossi <perossichi@gmail.com>
Maintainer: Peter Rossi <perossichi@gmail.com>
Diff between bayesm versions 2.2-5 dated 2012-05-16 and 3.0-0 dated 2015-06-12
bayesm-2.2-5/bayesm/R/breg.R |only bayesm-2.2-5/bayesm/R/cgetC.R |only bayesm-2.2-5/bayesm/R/clusterMix.R |only bayesm-2.2-5/bayesm/R/ghkvec.R |only bayesm-2.2-5/bayesm/R/llmnl.R |only bayesm-2.2-5/bayesm/R/lndIChisq.R |only bayesm-2.2-5/bayesm/R/lndIWishart.R |only bayesm-2.2-5/bayesm/R/lndMvn.R |only bayesm-2.2-5/bayesm/R/lndMvst.R |only bayesm-2.2-5/bayesm/R/rDPGibbs.R |only bayesm-2.2-5/bayesm/R/rbprobitGibbs.R |only bayesm-2.2-5/bayesm/R/rdirichlet.R |only bayesm-2.2-5/bayesm/R/rhierLinearMixture.R |only bayesm-2.2-5/bayesm/R/rhierLinearModel.R |only bayesm-2.2-5/bayesm/R/rhierMnlDP.R |only bayesm-2.2-5/bayesm/R/rhierMnlRwMixture.R |only bayesm-2.2-5/bayesm/R/rhierNegbinRw.R |only bayesm-2.2-5/bayesm/R/rivDP.R |only bayesm-2.2-5/bayesm/R/rivGibbs.R |only bayesm-2.2-5/bayesm/R/rmixGibbs.R |only bayesm-2.2-5/bayesm/R/rmixture.R |only bayesm-2.2-5/bayesm/R/rmnlIndepMetrop.R |only bayesm-2.2-5/bayesm/R/rmnpGibbs.R |only bayesm-2.2-5/bayesm/R/rmultireg.R |only bayesm-2.2-5/bayesm/R/rmvpGibbs.R |only bayesm-2.2-5/bayesm/R/rmvst.R |only bayesm-2.2-5/bayesm/R/rnegbinRw.R |only bayesm-2.2-5/bayesm/R/rnmixGibbs.R |only bayesm-2.2-5/bayesm/R/rordprobitGibbs.R |only bayesm-2.2-5/bayesm/R/rscaleUsage.R |only bayesm-2.2-5/bayesm/R/rsurGibbs.R |only bayesm-2.2-5/bayesm/R/rtrun.R |only bayesm-2.2-5/bayesm/R/runireg.R |only bayesm-2.2-5/bayesm/R/runiregGibbs.R |only bayesm-2.2-5/bayesm/R/rwishart.R |only bayesm-2.2-5/bayesm/data/datalist |only bayesm-2.2-5/bayesm/inst/doc |only bayesm-2.2-5/bayesm/src/bayesmc.c |only bayesm-2.2-5/bayesm/src/bayesmcpp.cpp |only bayesm-2.2-5/bayesm/src/thetadraw.c |only bayesm-3.0-0/bayesm/DESCRIPTION | 64 +- bayesm-3.0-0/bayesm/MD5 | 257 ++++---- bayesm-3.0-0/bayesm/NAMESPACE | 23 bayesm-3.0-0/bayesm/R/BayesmConstants.R |only bayesm-3.0-0/bayesm/R/BayesmFunctions.R |only bayesm-3.0-0/bayesm/R/clusterMix_rcpp.R |only bayesm-3.0-0/bayesm/R/createX.R | 143 ++-- bayesm-3.0-0/bayesm/R/llnhlogit.R | 9 bayesm-3.0-0/bayesm/R/mnpProb.R | 9 bayesm-3.0-0/bayesm/R/plot.bayesm.hcoef.R | 89 +- bayesm-3.0-0/bayesm/R/plot.bayesm.mat.R | 117 +-- bayesm-3.0-0/bayesm/R/rbayesBLP_rcpp.R |only bayesm-3.0-0/bayesm/R/rbiNormGibbs.R | 235 +++---- bayesm-3.0-0/bayesm/R/rbprobitgibbs_rcpp.r |only bayesm-3.0-0/bayesm/R/rcppexports.r |only bayesm-3.0-0/bayesm/R/rdpgibbs_rcpp.r |only bayesm-3.0-0/bayesm/R/rhierBinLogit.R | 455 +++++++-------- bayesm-3.0-0/bayesm/R/rhierLinearMixture_rcpp.r |only bayesm-3.0-0/bayesm/R/rhierLinearModel_rcpp.R |only bayesm-3.0-0/bayesm/R/rhierMnlDP_rcpp.r |only bayesm-3.0-0/bayesm/R/rhierMnlRwMixture_rcpp.r |only bayesm-3.0-0/bayesm/R/rhiernegbinrw_rcpp.r |only bayesm-3.0-0/bayesm/R/rivDP_rcpp.R |only bayesm-3.0-0/bayesm/R/rivGibbs_rcpp.R |only bayesm-3.0-0/bayesm/R/rmnlIndepMetrop_rcpp.R |only bayesm-3.0-0/bayesm/R/rmnpgibbs_rcpp.r |only bayesm-3.0-0/bayesm/R/rmvpgibbs_rcpp.r |only bayesm-3.0-0/bayesm/R/rnegbinrw_rcpp.r |only bayesm-3.0-0/bayesm/R/rnmixgibbs_rcpp.r |only bayesm-3.0-0/bayesm/R/rordprobitgibbs_rcpp.r |only bayesm-3.0-0/bayesm/R/rscaleusage_rcpp.r |only bayesm-3.0-0/bayesm/R/rsurgibbs_rcpp.r |only bayesm-3.0-0/bayesm/R/runireg_rcpp.r |only bayesm-3.0-0/bayesm/R/runireggibbs_rcpp.r |only bayesm-3.0-0/bayesm/R/simnhlogit.R | 14 bayesm-3.0-0/bayesm/R/summary.bayesm.var.R | 2 bayesm-3.0-0/bayesm/data/Scotch.rda |binary bayesm-3.0-0/bayesm/data/bank.rda |binary bayesm-3.0-0/bayesm/data/cheese.rda |binary bayesm-3.0-0/bayesm/data/customerSat.rda |binary bayesm-3.0-0/bayesm/data/detailing.rda |binary bayesm-3.0-0/bayesm/data/margarine.rda |binary bayesm-3.0-0/bayesm/data/orangeJuice.rda |binary bayesm-3.0-0/bayesm/data/tuna.rda |binary bayesm-3.0-0/bayesm/inst/include |only bayesm-3.0-0/bayesm/man/bank.Rd | 254 ++++---- bayesm-3.0-0/bayesm/man/breg.Rd | 2 bayesm-3.0-0/bayesm/man/cgetC.Rd | 2 bayesm-3.0-0/bayesm/man/cheese.Rd | 166 ++--- bayesm-3.0-0/bayesm/man/clusterMix.Rd | 176 ++--- bayesm-3.0-0/bayesm/man/condMom.Rd | 2 bayesm-3.0-0/bayesm/man/customerSat.Rd | 76 +- bayesm-3.0-0/bayesm/man/detailing.Rd | 24 bayesm-3.0-0/bayesm/man/eMixMargDen.Rd | 4 bayesm-3.0-0/bayesm/man/ghkvec.Rd | 115 ++- bayesm-3.0-0/bayesm/man/llmnl.Rd | 2 bayesm-3.0-0/bayesm/man/llnhlogit.Rd | 27 bayesm-3.0-0/bayesm/man/lndIChisq.Rd | 8 bayesm-3.0-0/bayesm/man/lndMvn.Rd | 2 bayesm-3.0-0/bayesm/man/lndMvst.Rd | 4 bayesm-3.0-0/bayesm/man/logMargDenNR.Rd | 70 +- bayesm-3.0-0/bayesm/man/margarine.Rd | 52 - bayesm-3.0-0/bayesm/man/mixDen.Rd | 4 bayesm-3.0-0/bayesm/man/mixDenBi.Rd | 4 bayesm-3.0-0/bayesm/man/mnlHess.Rd | 88 +- bayesm-3.0-0/bayesm/man/momMix.Rd | 2 bayesm-3.0-0/bayesm/man/orangeJuice.Rd | 68 +- bayesm-3.0-0/bayesm/man/plot.bayesm.hcoef.Rd | 2 bayesm-3.0-0/bayesm/man/plot.bayesm.mat.Rd | 10 bayesm-3.0-0/bayesm/man/plot.bayesm.nmix.Rd | 12 bayesm-3.0-0/bayesm/man/rDPGibbs.Rd | 79 +- bayesm-3.0-0/bayesm/man/rbayesBLP.Rd |only bayesm-3.0-0/bayesm/man/rbiNormGibbs.Rd | 2 bayesm-3.0-0/bayesm/man/rbprobitGibbs.Rd | 3 bayesm-3.0-0/bayesm/man/rhierBinLogit.Rd | 6 bayesm-3.0-0/bayesm/man/rhierLinearMixture.Rd | 308 +++++----- bayesm-3.0-0/bayesm/man/rhierLinearModel.Rd | 201 +++--- bayesm-3.0-0/bayesm/man/rhierMnlDP.Rd | 454 +++++++------- bayesm-3.0-0/bayesm/man/rhierMnlRwMixture.Rd | 366 ++++++------ bayesm-3.0-0/bayesm/man/rhierNegbinRw.Rd | 284 ++++----- bayesm-3.0-0/bayesm/man/rivDP.Rd | 64 +- bayesm-3.0-0/bayesm/man/rivGibbs.Rd | 197 +++--- bayesm-3.0-0/bayesm/man/rmixGibbs.Rd | 3 bayesm-3.0-0/bayesm/man/rmixture.Rd | 2 bayesm-3.0-0/bayesm/man/rmnlIndepMetrop.Rd | 187 +++--- bayesm-3.0-0/bayesm/man/rmnpGibbs.Rd | 239 +++---- bayesm-3.0-0/bayesm/man/rmultireg.Rd | 8 bayesm-3.0-0/bayesm/man/rmvpGibbs.Rd | 9 bayesm-3.0-0/bayesm/man/rnegbinRw.Rd | 13 bayesm-3.0-0/bayesm/man/rnmixGibbs.Rd | 13 bayesm-3.0-0/bayesm/man/rordprobitGibbs.Rd | 231 +++---- bayesm-3.0-0/bayesm/man/rscaleUsage.Rd | 4 bayesm-3.0-0/bayesm/man/rsurGibbs.Rd | 9 bayesm-3.0-0/bayesm/man/runireg.Rd | 11 bayesm-3.0-0/bayesm/man/runiregGibbs.Rd | 7 bayesm-3.0-0/bayesm/man/rwishart.Rd | 2 bayesm-3.0-0/bayesm/man/simnhlogit.Rd | 101 +-- bayesm-3.0-0/bayesm/man/summary.bayesm.mat.Rd | 9 bayesm-3.0-0/bayesm/man/summary.bayesm.nmix.Rd | 2 bayesm-3.0-0/bayesm/man/summary.bayesm.var.Rd | 4 bayesm-3.0-0/bayesm/man/tuna.Rd | 222 +++---- bayesm-3.0-0/bayesm/src/Makevars |only bayesm-3.0-0/bayesm/src/Makevars.win |only bayesm-3.0-0/bayesm/src/bayesBLP_rcpp_loop.cpp |only bayesm-3.0-0/bayesm/src/breg_rcpp.cpp |only bayesm-3.0-0/bayesm/src/cgetC_rcpp.cpp |only bayesm-3.0-0/bayesm/src/clusterMix_rcpp_loop.cpp |only bayesm-3.0-0/bayesm/src/functionTiming.cpp |only bayesm-3.0-0/bayesm/src/ghkvec_rcpp.cpp |only bayesm-3.0-0/bayesm/src/llmnl_rcpp.cpp |only bayesm-3.0-0/bayesm/src/lndIChisq_rcpp.cpp |only bayesm-3.0-0/bayesm/src/lndIWishart_rcpp.cpp |only bayesm-3.0-0/bayesm/src/lndMvn_rcpp.cpp |only bayesm-3.0-0/bayesm/src/lndMvst_rcpp.cpp |only bayesm-3.0-0/bayesm/src/rDPGibbs_rcpp_loop.cpp |only bayesm-3.0-0/bayesm/src/rbprobitGibbs_rcpp_loop.cpp |only bayesm-3.0-0/bayesm/src/rcppexports.cpp |only bayesm-3.0-0/bayesm/src/rdirichlet_rcpp.cpp |only bayesm-3.0-0/bayesm/src/rhierLinearMixture_rcpp_loop.cpp |only bayesm-3.0-0/bayesm/src/rhierLinearModel_rcpp_loop.cpp |only bayesm-3.0-0/bayesm/src/rhierMnlDP_rcpp_loop.cpp |only bayesm-3.0-0/bayesm/src/rhierMnlRwMixture_rcpp_loop.cpp |only bayesm-3.0-0/bayesm/src/rhierNegbinRw_rcpp_loop.cpp |only bayesm-3.0-0/bayesm/src/rivDP_rcpp_loop.cpp |only bayesm-3.0-0/bayesm/src/rivgibbs_rcpp_loop.cpp |only bayesm-3.0-0/bayesm/src/rmixGibbs_rcpp.cpp |only bayesm-3.0-0/bayesm/src/rmixture_rcpp.cpp |only bayesm-3.0-0/bayesm/src/rmnlIndepMetrop_rcpp_loop.cpp |only bayesm-3.0-0/bayesm/src/rmnpGibbs_rcpp_loop.cpp |only bayesm-3.0-0/bayesm/src/rmultireg_rcpp.cpp |only bayesm-3.0-0/bayesm/src/rmvpGibbs_rcpp_loop.cpp |only bayesm-3.0-0/bayesm/src/rmvst_rcpp.cpp |only bayesm-3.0-0/bayesm/src/rnegbinRw_rcpp_loop.cpp |only bayesm-3.0-0/bayesm/src/rnmixGibbs_rcpp_loop.cpp |only bayesm-3.0-0/bayesm/src/rordprobitGibbs_rcpp_loop.cpp |only bayesm-3.0-0/bayesm/src/rscaleUsage_rcpp_loop.cpp |only bayesm-3.0-0/bayesm/src/rsurGibbs_rcpp_loop.cpp |only bayesm-3.0-0/bayesm/src/rtrun_rcpp.cpp |only bayesm-3.0-0/bayesm/src/runiregGibbs_rcpp_loop.cpp |only bayesm-3.0-0/bayesm/src/runireg_rcpp_loop.cpp |only bayesm-3.0-0/bayesm/src/rwishart_rcpp.cpp |only bayesm-3.0-0/bayesm/src/utilityFunctions.cpp |only 182 files changed, 2871 insertions(+), 2762 deletions(-)
Title: Dirichlet Process Bayesian Clustering, Profile Regression
Description: Bayesian clustering using a Dirichlet process mixture model. This model is an alternative to regression models, non-parametrically linking a response vector to covariate data through cluster membership. The package allows Bernoulli, Binomial, Poisson, Normal, survival and categorical response, as well as Normal and discrete covariates. It also allows for fixed effects in the response model, where a spatial CAR (conditional autoregressive) term can be also included. Additionally, predictions may be made for the response, and missing values for the covariates are handled. Several samplers and label switching moves are implemented along with diagnostic tools to assess convergence. A number of R functions for post-processing of the output are also provided. In addition to fitting mixtures, it may additionally be of interest to determine which covariates actively drive the mixture components. This is implemented in the package as variable selection.
Author: David I. Hastie <david.hastie@rsimony.com>, Silvia Liverani <liveranis@gmail.com> and Sylvia Richardson <sylvia.richardson@mrc-bsu.cam.ac.uk> with contributions from Aurore J. Lavigne, Lucy Leigh, Lamiae Azizi
Maintainer: Silvia Liverani <liveranis@gmail.com>
Diff between PReMiuM versions 3.1.0 dated 2015-03-13 and 3.1.1 dated 2015-06-12
PReMiuM-3.1.0/PReMiuM/inst/citation |only PReMiuM-3.1.1/PReMiuM/ChangeLog | 8 + PReMiuM-3.1.1/PReMiuM/DESCRIPTION | 8 - PReMiuM-3.1.1/PReMiuM/MD5 | 26 +-- PReMiuM-3.1.1/PReMiuM/R/postProcess.R | 23 ++- PReMiuM-3.1.1/PReMiuM/inst/CITATION |only PReMiuM-3.1.1/PReMiuM/man/PReMiuM-package.Rd | 4 PReMiuM-3.1.1/PReMiuM/man/profRegr.Rd | 41 ++++- PReMiuM-3.1.1/PReMiuM/man/setHyperparams.Rd | 5 PReMiuM-3.1.1/PReMiuM/src/PReMiuM.cpp | 28 +++ PReMiuM-3.1.1/PReMiuM/src/include/PReMiuMIO.h | 12 + PReMiuM-3.1.1/PReMiuM/src/include/PReMiuMModel.h | 29 +++ PReMiuM-3.1.1/PReMiuM/src/include/PReMiuMOptions.h | 14 + PReMiuM-3.1.1/PReMiuM/src/include/PReMiuMProposals.h | 145 ++++++++++++++++++- PReMiuM-3.1.1/PReMiuM/src/postProcess.cpp | 4 15 files changed, 301 insertions(+), 46 deletions(-)
Title: Data Sets, Functions and Examples from the Book: "Modern
Industrial Statistics" by Kenett, Zacks and Amberti
Description: This R package is providing all the data sets and statistical analysis applications used in "Modern Industrial Statistics: with applications in R, MINITAB and JMP" by R.S. Kenett and S. Zacks with contributions by D. Amberti, John Wiley and Sons, 2013, which is a second revised and expanded revision of "Modern Industrial Statistics: Design and Control of Quality and Reliability", R. Kenett and S. Zacks, Duxbury/Wadsworth Publishing, 1998.
Author: Daniele Amberti
Maintainer: Daniele Amberti <daniele.amberti@gmail.com>
Diff between mistat versions 1.0-2 dated 2014-01-20 and 1.0-3 dated 2015-06-12
DESCRIPTION | 14 +++++++------- MD5 | 6 +++--- R/availDis.R | 5 ++--- R/randomizationTest.R | 3 +-- 4 files changed, 13 insertions(+), 15 deletions(-)
Title: Sensitivity Analysis
Description: A collection of functions for factor screening, global sensitivity analysis and reliability sensitivity analysis of model output.
Author: Gilles Pujol, Bertrand Iooss, Alexandre Janon with contributions from Sebastien Da Veiga, Jana Fruth, Laurent Gilquin, Joseph Guillaume, Loic Le Gratiet, Paul Lemaitre, Bernardo Ramos, Taieb Touati
Maintainer: Bertrand Iooss <biooss@yahoo.fr>
Diff between sensitivity versions 1.11 dated 2015-03-06 and 1.11.1 dated 2015-06-12
DESCRIPTION | 8 - MD5 | 26 +-- R/sobol.R | 352 +++++++++++++++++++++++++-------------------------- R/sobol2002.R | 238 +++++++++++++++++----------------- R/sobolMultOut.R | 9 - R/sobolmartinez.R | 23 +-- man/sobol.Rd | 4 man/sobol2002.Rd | 2 man/sobol2007.Rd | 2 man/sobolGP.Rd | 2 man/sobolMultOut.Rd | 11 - man/soboljansen.Rd | 2 man/sobolmara.Rd | 2 man/sobolmartinez.Rd | 11 + 14 files changed, 349 insertions(+), 343 deletions(-)
Title: Survival Analysis
Description: Contains the core survival analysis routines, including
definition of Surv objects,
Kaplan-Meier and Aalen-Johansen (multi-state) curves, Cox models,
and parametric accelerated failure time models.
Author: Terry M Therneau [aut, cre],
Thomas Lumley [ctb, trl] (original S->R port and maintainer until 2009)
Maintainer: Terry M Therneau <therneau.terry@mayo.edu>
Diff between survival versions 2.38-1 dated 2015-02-24 and 2.38-2 dated 2015-06-12
survival-2.38-1/survival/R/anova.coxmelist.R |only survival-2.38-1/survival/R/anova.coxph.S |only survival-2.38-1/survival/vignettes/figures |only survival-2.38-2/survival/DESCRIPTION | 6 survival-2.38-2/survival/MD5 | 154 ++++++++++---------- survival-2.38-2/survival/NAMESPACE | 1 survival-2.38-2/survival/R/agreg.fit.R | 3 survival-2.38-2/survival/R/anova.coxph.R |only survival-2.38-2/survival/R/anova.coxph.penal.R |only survival-2.38-2/survival/R/coxexact.fit.R | 38 ++++ survival-2.38-2/survival/R/coxph.R | 6 survival-2.38-2/survival/R/logLik.coxph.R | 9 - survival-2.38-2/survival/R/print.coxph.S | 18 +- survival-2.38-2/survival/R/print.coxph.penal.S | 22 +- survival-2.38-2/survival/R/print.survfit.S | 17 ++ survival-2.38-2/survival/R/pyears.R | 4 survival-2.38-2/survival/R/summary.pyears.S | 3 survival-2.38-2/survival/R/survexp.R | 3 survival-2.38-2/survival/R/survfit.coxph.R | 4 survival-2.38-2/survival/R/tmerge.R | 2 survival-2.38-2/survival/build/vignette.rds |binary survival-2.38-2/survival/data/kidney.rda |binary survival-2.38-2/survival/data/ovarian.rda |binary survival-2.38-2/survival/inst/NEWS.Rd | 53 ++++++ survival-2.38-2/survival/inst/NEWS.Rd.orig | 72 ++++++++- survival-2.38-2/survival/inst/doc/adjcurve.Rnw | 4 survival-2.38-2/survival/inst/doc/adjcurve.pdf |binary survival-2.38-2/survival/inst/doc/compete.R | 76 ++++++--- survival-2.38-2/survival/inst/doc/compete.Rnw | 106 ++++++++----- survival-2.38-2/survival/inst/doc/compete.pdf |binary survival-2.38-2/survival/inst/doc/splines.R | 33 +++- survival-2.38-2/survival/inst/doc/splines.Rnw | 65 +++++++- survival-2.38-2/survival/inst/doc/splines.pdf |binary survival-2.38-2/survival/inst/doc/tests.R | 13 - survival-2.38-2/survival/inst/doc/tests.Rnw | 9 - survival-2.38-2/survival/inst/doc/tests.pdf |binary survival-2.38-2/survival/inst/doc/timedep.R | 38 +++- survival-2.38-2/survival/inst/doc/timedep.Rnw | 61 ++++++- survival-2.38-2/survival/inst/doc/timedep.pdf |binary survival-2.38-2/survival/man/clogit.Rd | 17 +- survival-2.38-2/survival/man/coxph.Rd | 30 +++ survival-2.38-2/survival/man/logLik.coxph.Rd |only survival-2.38-2/survival/man/pyears.Rd | 3 survival-2.38-2/survival/man/survfit.coxph.Rd | 2 survival-2.38-2/survival/man/transplant.Rd | 2 survival-2.38-2/survival/noweb/Makefile | 3 survival-2.38-2/survival/noweb/Readme | 3 survival-2.38-2/survival/noweb/agreg.Rnw | 85 ++++++++--- survival-2.38-2/survival/noweb/all.pdf |only survival-2.38-2/survival/noweb/coxph.Rnw | 8 + survival-2.38-2/survival/noweb/coxsurv.Rnw | 4 survival-2.38-2/survival/noweb/exact.nw | 19 +- survival-2.38-2/survival/noweb/plot.Rnw | 2 survival-2.38-2/survival/noweb/pyears.Rnw | 1 survival-2.38-2/survival/noweb/survexp.Rnw | 7 survival-2.38-2/survival/noweb/survfitCI.Rnw | 13 - survival-2.38-2/survival/noweb/tmerge.Rnw | 2 survival-2.38-2/survival/src/agfit4.c | 104 ++++++++++--- survival-2.38-2/survival/src/coxexact.c | 14 + survival-2.38-2/survival/src/coxfit6.c | 2 survival-2.38-2/survival/src/init.c | 2 survival-2.38-2/survival/src/survproto.h | 3 survival-2.38-2/survival/tests/bladder.Rout.save | 86 +++++------ survival-2.38-2/survival/tests/book5.Rout.save | 18 +- survival-2.38-2/survival/tests/book6.Rout.save | 18 +- survival-2.38-2/survival/tests/book7.Rout.save | 8 - survival-2.38-2/survival/tests/cancer.Rout.save | 37 ++-- survival-2.38-2/survival/tests/doaml.Rout.save | 27 +-- survival-2.38-2/survival/tests/doweight.Rout.save | 32 ++-- survival-2.38-2/survival/tests/fr_cancer.Rout.save | 55 +++---- survival-2.38-2/survival/tests/fr_kidney.Rout.save | 118 +++++++-------- survival-2.38-2/survival/tests/fr_ovarian.Rout.save | 19 +- survival-2.38-2/survival/tests/fr_rat1.Rout.save | 22 +- survival-2.38-2/survival/tests/fr_rat2.Rout.save | 44 ++--- survival-2.38-2/survival/tests/fr_resid.Rout.save | 25 +-- survival-2.38-2/survival/tests/jasa.Rout.save | 65 ++++---- survival-2.38-2/survival/tests/ovarian.Rout.save | 85 +++++------ survival-2.38-2/survival/vignettes/adjcurve.Rnw | 4 survival-2.38-2/survival/vignettes/compete.Rnw | 106 ++++++++----- survival-2.38-2/survival/vignettes/splines.Rnw | 65 +++++++- survival-2.38-2/survival/vignettes/tests.Rnw | 9 - survival-2.38-2/survival/vignettes/timedep.Rnw | 61 ++++++- 82 files changed, 1361 insertions(+), 689 deletions(-)
Title: Neural Networks in R using the Stuttgart Neural Network
Simulator (SNNS)
Description: The Stuttgart Neural Network Simulator (SNNS) is a library
containing many standard implementations of neural networks. This
package wraps the SNNS functionality to make it available from
within R. Using the RSNNS low-level interface, all of the
algorithmic functionality and flexibility of SNNS can be accessed.
Furthermore, the package contains a convenient high-level
interface, so that the most common neural network topologies and
learning algorithms integrate seamlessly into R.
Author: Christoph Bergmeir and José M. BenÃtez
Maintainer: Christoph Bergmeir <c.bergmeir@decsai.ugr.es>
Diff between RSNNS versions 0.4-6 dated 2014-12-22 and 0.4-7 dated 2015-06-12
ChangeLog | 5 DESCRIPTION | 10 - MD5 | 162 ++++++++--------- NAMESPACE | 2 R/RSNNS-package.R | 3 R/SnnsR_patterns.R | 13 - man/RSNNS-package.Rd | 6 man/SnnsR-class.Rd | 3 man/SnnsRObject-createNet.Rd | 3 man/SnnsRObject-createPatSet.Rd | 3 man/SnnsRObject-extractNetInfo.Rd | 3 man/SnnsRObject-extractPatterns.Rd | 3 man/SnnsRObject-genericPredictCurrPatSet.Rd | 3 man/SnnsRObject-getAllHiddenUnits.Rd | 3 man/SnnsRObject-getAllInputUnits.Rd | 3 man/SnnsRObject-getAllOutputUnits.Rd | 3 man/SnnsRObject-getAllUnits.Rd | 3 man/SnnsRObject-getAllUnitsTType.Rd | 3 man/SnnsRObject-getCompleteWeightMatrix.Rd | 3 man/SnnsRObject-getInfoHeader.Rd | 3 man/SnnsRObject-getSiteDefinitions.Rd | 3 man/SnnsRObject-getTypeDefinitions.Rd | 3 man/SnnsRObject-getUnitDefinitions.Rd | 3 man/SnnsRObject-getUnitsByName.Rd | 3 man/SnnsRObject-getWeightMatrix.Rd | 3 man/SnnsRObject-initializeNet.Rd | 3 man/SnnsRObject-predictCurrPatSet.Rd | 3 man/SnnsRObject-resetRSNNS.Rd | 3 man/SnnsRObject-setTTypeUnitsActFunc.Rd | 3 man/SnnsRObject-setUnitDefaults.Rd | 3 man/SnnsRObject-somPredictComponentMaps.Rd | 3 man/SnnsRObject-somPredictCurrPatSetWinners.Rd | 3 man/SnnsRObject-somPredictCurrPatSetWinnersSpanTree.Rd | 3 man/SnnsRObject-train.Rd | 3 man/SnnsRObject-whereAreResults.Rd | 3 man/SnnsRObjectFactory.Rd | 3 man/SnnsRObjectMethodCaller.Rd | 3 man/analyzeClassification.Rd | 3 man/art1.Rd | 3 man/art2.Rd | 3 man/artmap.Rd | 3 man/assoz.Rd | 3 man/confusionMatrix.Rd | 3 man/decodeClassLabels.Rd | 3 man/denormalizeData.Rd | 3 man/dlvq.Rd | 3 man/elman.Rd | 3 man/encodeClassLabels.Rd | 3 man/exportToSnnsNetFile.Rd | 3 man/extractNetInfo.Rd | 3 man/getNormParameters.Rd | 3 man/getSnnsRDefine.Rd | 3 man/getSnnsRFunctionTable.Rd | 3 man/inputColumns.Rd | 3 man/jordan.Rd | 3 man/matrixToActMapList.Rd | 3 man/mlp.Rd | 3 man/normTrainingAndTestSet.Rd | 3 man/normalizeData.Rd | 3 man/outputColumns.Rd | 3 man/plotActMap.Rd | 3 man/plotIterativeError.Rd | 3 man/plotROC.Rd | 3 man/plotRegressionError.Rd | 3 man/predict.rsnns.Rd | 3 man/print.rsnns.Rd | 3 man/rbf.Rd | 3 man/rbfDDA.Rd | 3 man/readPatFile.Rd | 3 man/readResFile.Rd | 3 man/resolveSnnsRDefine.Rd | 3 man/rsnnsObjectFactory.Rd | 3 man/savePatFile.Rd | 3 man/setSnnsRSeedValue.Rd | 3 man/snnsData.Rd | 3 man/som.Rd | 3 man/splitForTrainingAndTest.Rd | 3 man/summary.rsnns.Rd | 3 man/toNumericClassLabels.Rd | 3 man/train.Rd | 3 man/vectorToActMap.Rd | 3 man/weightMatrix.Rd | 3 82 files changed, 258 insertions(+), 168 deletions(-)
Title: Empirical Orthogonal Teleconnections in R
Description:
Empirical orthogonal teleconnections in R.
'remote' is short for "R(-based) EMpirical Orthogonal TEleconnections".
It implements a collection of functions to facilitate empirical
orthogonal teleconnection analysis. Empirical Orthogonal Teleconnections
(EOTs) denote a regression based approach to decompose spatio-temporal
fields into a set of independent orthogonal patterns. They are quite
similar to Empirical Orthogonal Functions (EOFs) with EOTs producing
less abstract results. In contrast to EOFs, which are orthogonal in both
space and time, EOT analysis produces patterns that are orthogonal in
either space or time.
Author: Tim Appelhans, Florian Detsch, Thomas Nauss
Maintainer: Tim Appelhans <tim.appelhans@gmail.com>
Diff between remote versions 0.3.0 dated 2014-08-25 and 1.0.0 dated 2015-06-12
DESCRIPTION | 9 +-- MD5 | 89 +++++++++++++++--------------- NAMESPACE | 28 +++++---- R/EotCycle.R | 5 - R/RcppExports.R | 8 ++ R/denoise.R | 52 +++++++++++------ R/deseason.R | 27 ++++++--- R/eot.R | 6 -- R/getWeights.R | 2 R/nXplain.R | 6 +- R/names.R | 1 R/plot.R | 3 + R/subset.R | 1 README.md | 4 - data/australiaGPCP.RData |binary data/pacificSST.RData |binary data/vdendool.RData |binary inst |only man/EotCycle.Rd | 9 +-- man/EotMode-class.Rd | 3 - man/EotStack-class.Rd | 3 - man/anomalize.Rd | 3 - man/australiaGPCP.Rd | 3 - man/calcVar.Rd | 3 - man/covWeight.Rd | 3 - man/cutStack.Rd | 3 - man/deg2rad.Rd | 3 - man/denoise.Rd | 12 +++- man/deseason.Rd | 8 ++ man/eot.Rd | 3 - man/geoWeight.Rd | 3 - man/getWeights.Rd | 3 - man/lagalize.Rd | 3 - man/nXplain.Rd | 9 +-- man/names.Rd | 6 +- man/nmodes.Rd | 3 - man/pacificSST.Rd | 3 - man/plot.Rd | 6 +- man/predict.Rd | 3 - man/remote-package.Rd | 3 - man/subset.Rd | 26 +------- man/vdendool.Rd | 3 - man/writeEot.Rd | 3 - src/EotCppFun.cpp | 67 ++++++++++++++++++++++ src/RcppExports.cpp | 138 ++++++++++++++++++++++------------------------- vignettes |only 46 files changed, 347 insertions(+), 229 deletions(-)
Title: Tools for Splitting, Applying and Combining Data
Description: A set of tools that solves a common set of problems: you
need to break a big problem down into manageable pieces, operate on each
piece and then put all the pieces back together. For example, you might
want to fit a model to each spatial location or time point in your study,
summarise data by panels or collapse high-dimensional arrays to simpler
summary statistics. The development of 'plyr' has been generously supported
by 'Becton Dickinson'.
Author: Hadley Wickham [aut, cre]
Maintainer: Hadley Wickham <hadley@rstudio.com>
Diff between plyr versions 1.8.2 dated 2015-04-21 and 1.8.3 dated 2015-06-12
plyr-1.8.2/plyr/src/loop-apply.cpp |only plyr-1.8.3/plyr/DESCRIPTION | 8 - plyr-1.8.3/plyr/MD5 | 199 +++++++++++++------------- plyr-1.8.3/plyr/NAMESPACE | 2 plyr-1.8.3/plyr/R/RcppExports.R | 14 - plyr-1.8.3/plyr/R/loop_apply.R |only plyr-1.8.3/plyr/man/a_ply.Rd | 2 plyr-1.8.3/plyr/man/aaply.Rd | 2 plyr-1.8.3/plyr/man/adply.Rd | 2 plyr-1.8.3/plyr/man/alply.Rd | 2 plyr-1.8.3/plyr/man/amv_dim.Rd | 2 plyr-1.8.3/plyr/man/amv_dimnames.Rd | 2 plyr-1.8.3/plyr/man/arrange.Rd | 2 plyr-1.8.3/plyr/man/as.data.frame.function.Rd | 2 plyr-1.8.3/plyr/man/as.list.split.Rd | 2 plyr-1.8.3/plyr/man/as.quoted.Rd | 2 plyr-1.8.3/plyr/man/baseball.Rd | 2 plyr-1.8.3/plyr/man/colwise.Rd | 2 plyr-1.8.3/plyr/man/compact.Rd | 2 plyr-1.8.3/plyr/man/count.Rd | 2 plyr-1.8.3/plyr/man/create_progress_bar.Rd | 2 plyr-1.8.3/plyr/man/d_ply.Rd | 2 plyr-1.8.3/plyr/man/daply.Rd | 2 plyr-1.8.3/plyr/man/ddply.Rd | 2 plyr-1.8.3/plyr/man/defaults.Rd | 2 plyr-1.8.3/plyr/man/desc.Rd | 2 plyr-1.8.3/plyr/man/dims.Rd | 2 plyr-1.8.3/plyr/man/dlply.Rd | 2 plyr-1.8.3/plyr/man/each.Rd | 2 plyr-1.8.3/plyr/man/empty.Rd | 2 plyr-1.8.3/plyr/man/eval.quoted.Rd | 2 plyr-1.8.3/plyr/man/failwith.Rd | 2 plyr-1.8.3/plyr/man/get-split.Rd | 2 plyr-1.8.3/plyr/man/here.Rd | 2 plyr-1.8.3/plyr/man/id.Rd | 2 plyr-1.8.3/plyr/man/id_var.Rd | 2 plyr-1.8.3/plyr/man/idata.frame.Rd | 2 plyr-1.8.3/plyr/man/indexed_array.Rd | 2 plyr-1.8.3/plyr/man/indexed_df.Rd | 2 plyr-1.8.3/plyr/man/is.discrete.Rd | 2 plyr-1.8.3/plyr/man/is.formula.Rd | 2 plyr-1.8.3/plyr/man/isplit2.Rd | 2 plyr-1.8.3/plyr/man/join.Rd | 2 plyr-1.8.3/plyr/man/join.keys.Rd | 2 plyr-1.8.3/plyr/man/join_all.Rd | 2 plyr-1.8.3/plyr/man/l_ply.Rd | 2 plyr-1.8.3/plyr/man/laply.Rd | 2 plyr-1.8.3/plyr/man/ldply.Rd | 2 plyr-1.8.3/plyr/man/liply.Rd | 2 plyr-1.8.3/plyr/man/list_to_array.Rd | 2 plyr-1.8.3/plyr/man/list_to_dataframe.Rd | 2 plyr-1.8.3/plyr/man/list_to_vector.Rd | 2 plyr-1.8.3/plyr/man/llply.Rd | 2 plyr-1.8.3/plyr/man/loop_apply.Rd | 6 plyr-1.8.3/plyr/man/m_ply.Rd | 2 plyr-1.8.3/plyr/man/maply.Rd | 2 plyr-1.8.3/plyr/man/mapvalues.Rd | 2 plyr-1.8.3/plyr/man/match_df.Rd | 2 plyr-1.8.3/plyr/man/mdply.Rd | 2 plyr-1.8.3/plyr/man/mlply.Rd | 2 plyr-1.8.3/plyr/man/mutate.Rd | 2 plyr-1.8.3/plyr/man/name_rows.Rd | 2 plyr-1.8.3/plyr/man/names.quoted.Rd | 2 plyr-1.8.3/plyr/man/nunique.Rd | 2 plyr-1.8.3/plyr/man/ozone.Rd | 2 plyr-1.8.3/plyr/man/plyr-deprecated.Rd | 2 plyr-1.8.3/plyr/man/plyr.Rd | 2 plyr-1.8.3/plyr/man/print.quoted.Rd | 2 plyr-1.8.3/plyr/man/print.split.Rd | 2 plyr-1.8.3/plyr/man/progress_none.Rd | 2 plyr-1.8.3/plyr/man/progress_text.Rd | 2 plyr-1.8.3/plyr/man/progress_time.Rd | 2 plyr-1.8.3/plyr/man/progress_tk.Rd | 2 plyr-1.8.3/plyr/man/progress_win.Rd | 2 plyr-1.8.3/plyr/man/quickdf.Rd | 2 plyr-1.8.3/plyr/man/quoted.Rd | 2 plyr-1.8.3/plyr/man/r_ply.Rd | 2 plyr-1.8.3/plyr/man/raply.Rd | 2 plyr-1.8.3/plyr/man/rbind.fill.Rd | 2 plyr-1.8.3/plyr/man/rbind.fill.matrix.Rd | 2 plyr-1.8.3/plyr/man/rdply.Rd | 2 plyr-1.8.3/plyr/man/reduce_dim.Rd | 2 plyr-1.8.3/plyr/man/rename.Rd | 2 plyr-1.8.3/plyr/man/revalue.Rd | 2 plyr-1.8.3/plyr/man/rlply.Rd | 2 plyr-1.8.3/plyr/man/round_any.Rd | 2 plyr-1.8.3/plyr/man/splat.Rd | 2 plyr-1.8.3/plyr/man/split_indices.Rd | 2 plyr-1.8.3/plyr/man/split_labels.Rd | 2 plyr-1.8.3/plyr/man/splitter_a.Rd | 2 plyr-1.8.3/plyr/man/splitter_d.Rd | 2 plyr-1.8.3/plyr/man/strip_splits.Rd | 2 plyr-1.8.3/plyr/man/summarise.Rd | 2 plyr-1.8.3/plyr/man/take.Rd | 2 plyr-1.8.3/plyr/man/true.Rd | 2 plyr-1.8.3/plyr/man/try_default.Rd | 2 plyr-1.8.3/plyr/man/tryapply.Rd | 2 plyr-1.8.3/plyr/man/unrowname.Rd | 2 plyr-1.8.3/plyr/man/vaggregate.Rd | 2 plyr-1.8.3/plyr/src/RcppExports.cpp | 12 - plyr-1.8.3/plyr/src/loop_apply.c |only plyr-1.8.3/plyr/tests/testthat/test-rbind.r | 4 102 files changed, 202 insertions(+), 227 deletions(-)
Title: Discrete Laplace Mixture Inference using the EM Algorithm
Description: Make inference in a mixture of discrete Laplace distributions using the EM algorithm. This can e.g. be used for modelling the distribution of Y chromosomal haplotypes as described in [1, 2] (refer to the URL section).
Author: Mikkel Meyer Andersen and Poul Svante Eriksen
Maintainer: Mikkel Meyer Andersen <mikl@math.aau.dk>
Diff between disclapmix versions 1.6 dated 2015-01-16 and 1.6.1 dated 2015-06-12
DESCRIPTION | 12 +-- MD5 | 18 ++--- NAMESPACE | 5 + NEWS | 6 + R/RcppExports.R | 16 ++++ R/disclapmix.R | 2 R/helper.R | 177 +++++++++++++++++++++++++++++++++++++++++++--------- man/happrobsum.Rd |only src/RcppExports.cpp | 72 +++++++++++++++++++++ src/happrobsum.cpp |only src/helper.cpp | 65 +++++++++++++++++++ 11 files changed, 330 insertions(+), 43 deletions(-)
Title: Copula Mixed Effect Models for Bivariate and Trivariate
Meta-Analysis of Diagnostic Test Accuracy Studies
Description: It has functions to implement the copula mixed models for bivariate and trivariate meta-analysis of diagnostic test accuracy studies in Nikoloulopoulos, A.K. (2015a,b).
Author: Aristidis K. Nikoloulopoulos <A.Nikoloulopoulos@uea.ac.uk>
Maintainer: Aristidis K. Nikoloulopoulos <A.Nikoloulopoulos@uea.ac.uk>
Diff between CopulaREMADA versions 0.5-1 dated 2015-02-22 and 0.9 dated 2015-06-12
CopulaREMADA-0.5-1/CopulaREMADA/man/meshgrid.Rd |only CopulaREMADA-0.9/CopulaREMADA/DESCRIPTION | 16 +++--- CopulaREMADA-0.9/CopulaREMADA/INDEX | 17 ++++++- CopulaREMADA-0.9/CopulaREMADA/MD5 | 31 ++++++++----- CopulaREMADA-0.9/CopulaREMADA/NAMESPACE | 14 ++++- CopulaREMADA-0.9/CopulaREMADA/R/CopulaREMADA.R | 30 +++--------- CopulaREMADA-0.9/CopulaREMADA/R/MLest.R |only CopulaREMADA-0.9/CopulaREMADA/R/Vuong.R | 40 ++++++++--------- CopulaREMADA-0.9/CopulaREMADA/R/simFUN.R |only CopulaREMADA-0.9/CopulaREMADA/R/tMLest.R |only CopulaREMADA-0.9/CopulaREMADA/R/vine-vuong.R |only CopulaREMADA-0.9/CopulaREMADA/data/OGT.rda |only CopulaREMADA-0.9/CopulaREMADA/data/betaDG.rda |only CopulaREMADA-0.9/CopulaREMADA/man/CopulaREMADA.Rd | 7 +- CopulaREMADA-0.9/CopulaREMADA/man/OGT.Rd |only CopulaREMADA-0.9/CopulaREMADA/man/SROC.Rd | 3 - CopulaREMADA-0.9/CopulaREMADA/man/VineCopulaREMADA.Rd |only CopulaREMADA-0.9/CopulaREMADA/man/Vuong.Rd | 5 -- CopulaREMADA-0.9/CopulaREMADA/man/betaDG.Rd |only CopulaREMADA-0.9/CopulaREMADA/man/cvinesim.Rd |only CopulaREMADA-0.9/CopulaREMADA/man/rCopulaREMADA.Rd | 2 CopulaREMADA-0.9/CopulaREMADA/man/rVineCopulaREMADA.Rd |only CopulaREMADA-0.9/CopulaREMADA/man/vineVuong.Rd |only 23 files changed, 90 insertions(+), 75 deletions(-)
Title: STRUctural Modeling of Latent Variables for General Pedigree
Description: Implements a broad class of latent variable and structural equation models for general pedigree data.
Author: Nathan Morris [aut, cre],
Yeunjoo Song [aut],
Stephen Cahn [ctb]
Maintainer: Nathan Morris <nathan.morris@cwru.edu>
Diff between strum versions 0.6.1 dated 2015-05-11 and 0.6.2 dated 2015-06-12
ChangeLog | 8 ++++++++ DESCRIPTION | 10 +++++----- MD5 | 14 +++++++------- R/strum.R | 4 ++-- build/vignette.rds |binary inst/doc/strum-example.pdf |binary inst/doc/strum-intro.pdf |binary man/strum-package.Rd | 6 +++--- 8 files changed, 25 insertions(+), 17 deletions(-)
Title: Rcmdr Support for the HH package
Description: Rcmdr menu support for many of the functions in the HH package.
The focus is on menu items for functions we use in our introductory
courses.
Author: Richard M. Heiberger, with contributions from Burt Holland
Maintainer: Richard M. Heiberger <rmh@temple.edu>
Diff between RcmdrPlugin.HH versions 1.1-42 dated 2015-01-09 and 1.1-43 dated 2015-06-12
DESCRIPTION | 17 +++---- MD5 | 6 +- NAMESPACE | 86 +++++++++++++++++++++++++++++++++++--- R/bestSubsetsRegressionModel.HH.R | 14 +++--- 4 files changed, 97 insertions(+), 26 deletions(-)
More information about RcmdrPlugin.HH at CRAN
Permanent link
Title: Statistical Analysis and Data Display: Heiberger and Holland
Description: Support software for Statistical Analysis and Data Display (First Edition, Springer, ISBN 0-387-40270-5, 2004) and (Second Edition, Springer, ISBN 978-1-4939-2121-8, anticipated 2015) by Richard M. Heiberger and Burt Holland. This contemporary presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The second edition includes redesigned graphics and additional chapters. The authors emphasize how to construct and interpret graphs, discuss principles of graphical design, and show how accompanying traditional tabular results are used to confirm the visual impressions derived directly from the graphs. Many of the graphical formats are novel and appear here for the first time in print. All chapters have exercises. All functions introduced in the book are in the package. R code for all examples, both graphs and tables, in the book is included in the scripts directory of the package.
Author: Richard M. Heiberger
Maintainer: Richard M. Heiberger <rmh@temple.edu>
Diff between HH versions 3.1-15 dated 2015-02-16 and 3.1-19 dated 2015-06-12
HH-3.1-15/HH/data/nottem.rda |only HH-3.1-15/HH/demo/book.plots.r |only HH-3.1-19/HH/DESCRIPTION | 13 HH-3.1-19/HH/MD5 | 156 ++- HH-3.1-19/HH/NAMESPACE | 33 HH-3.1-19/HH/NEWS | 71 + HH-3.1-19/HH/R/F.curve.R | 4 HH-3.1-19/HH/R/HHscriptnames.R | 36 HH-3.1-19/HH/R/ae.dotplot.R | 46 - HH-3.1-19/HH/R/ancova.R | 11 HH-3.1-19/HH/R/ancovaplot.R | 5 HH-3.1-19/HH/R/as.matrix.listOfMatrices.R | 18 HH-3.1-19/HH/R/chisq.curve.R | 4 HH-3.1-19/HH/R/dstrplot.r |only HH-3.1-19/HH/R/hhpdf.R | 7 HH-3.1-19/HH/R/hovBF.R | 8 HH-3.1-19/HH/R/interaction2wt.R | 4 HH-3.1-19/HH/R/lmatPairwise.R |only HH-3.1-19/HH/R/lmplot.R | 20 HH-3.1-19/HH/R/mmcplot.R | 45 - HH-3.1-19/HH/R/normal.and.t.R | 26 HH-3.1-19/HH/R/normal.and.t.htest.R | 3 HH-3.1-19/HH/R/normal.and.t.shiny.R | 144 ++- HH-3.1-19/HH/R/panel.bwplot.intermediate.hh.R | 3 HH-3.1-19/HH/R/plotOddsRatio.R | 13 HH-3.1-19/HH/R/regrDiagn.R | 4 HH-3.1-19/HH/R/residual.plots.lattice.R | 5 HH-3.1-19/HH/R/showHex.R |only HH-3.1-19/HH/data/Discrete4.rda |only HH-3.1-19/HH/data/col3x2.rda |only HH-3.1-19/HH/data/wheat.rda |binary HH-3.1-19/HH/demo/00Index | 1 HH-3.1-19/HH/inst/scripts/hh2/HHApx.R | 6 HH-3.1-19/HH/inst/scripts/hh2/MSword.R |only HH-3.1-19/HH/inst/scripts/hh2/PrcnApx.R |only HH-3.1-19/HH/inst/scripts/hh2/RApx.R | 73 + HH-3.1-19/HH/inst/scripts/hh2/RExcelApx.R | 42 - HH-3.1-19/HH/inst/scripts/hh2/RcmdrApx.R | 6 HH-3.1-19/HH/inst/scripts/hh2/Rpack.R |only HH-3.1-19/HH/inst/scripts/hh2/ShinyApx.R |only HH-3.1-19/HH/inst/scripts/hh2/conc.R | 270 ++++-- HH-3.1-19/HH/inst/scripts/hh2/data.R |only HH-3.1-19/HH/inst/scripts/hh2/dsgn.R | 309 ++++--- HH-3.1-19/HH/inst/scripts/hh2/dsgntwo.R | 483 ++++++------ HH-3.1-19/HH/inst/scripts/hh2/dstr.R |only HH-3.1-19/HH/inst/scripts/hh2/edit.R |only HH-3.1-19/HH/inst/scripts/hh2/emcs.R |only HH-3.1-19/HH/inst/scripts/hh2/grap.R | 419 +++++++--- HH-3.1-19/HH/inst/scripts/hh2/iinf.R | 299 +++++-- HH-3.1-19/HH/inst/scripts/hh2/intr.R |only HH-3.1-19/HH/inst/scripts/hh2/latexApx.R |only HH-3.1-19/HH/inst/scripts/hh2/logi.R | 337 ++++---- HH-3.1-19/HH/inst/scripts/hh2/mcomp.R | 228 +++-- HH-3.1-19/HH/inst/scripts/hh2/mthp.R |only HH-3.1-19/HH/inst/scripts/hh2/npar.R | 126 +-- HH-3.1-19/HH/inst/scripts/hh2/otherApx.R |only HH-3.1-19/HH/inst/scripts/hh2/oway.R | 174 +++- HH-3.1-19/HH/inst/scripts/hh2/rega.R | 121 +-- HH-3.1-19/HH/inst/scripts/hh2/regb.R | 202 ++--- HH-3.1-19/HH/inst/scripts/hh2/regbb.R | 219 ++--- HH-3.1-19/HH/inst/scripts/hh2/regc.R | 183 ++-- HH-3.1-19/HH/inst/scripts/hh2/tser.R | 290 +++---- HH-3.1-19/HH/inst/scripts/hh2/tway.R | 296 ++++--- HH-3.1-19/HH/inst/scripts/hh2/twtb.R | 473 +++++++---- HH-3.1-19/HH/inst/scripts/hh2/typg.R |only HH-3.1-19/HH/inst/shiny/NormalAndTplot/ui.R | 16 HH-3.1-19/HH/inst/shiny/PopulationPyramid/ui.R | 2 HH-3.1-19/HH/inst/shiny/bivariateNormalScatterplot/server.R | 3 HH-3.1-19/HH/man/Discrete4.color.Rd |only HH-3.1-19/HH/man/F.curve.Rd | 6 HH-3.1-19/HH/man/HH.package.Rd | 57 - HH-3.1-19/HH/man/HHscriptnames.Rd | 6 HH-3.1-19/HH/man/NormalAndT.Rd | 5 HH-3.1-19/HH/man/ancova.Rd | 6 HH-3.1-19/HH/man/ancovaplot.Rd | 8 HH-3.1-19/HH/man/bivariateNormal.Rd | 11 HH-3.1-19/HH/man/col3x2.Rd |only HH-3.1-19/HH/man/datasets.Rd | 1 HH-3.1-19/HH/man/hhpdf.Rd | 18 HH-3.1-19/HH/man/hovBF.Rd | 7 HH-3.1-19/HH/man/interaction2wt.Rd | 69 - HH-3.1-19/HH/man/lmatPairwise.Rd |only HH-3.1-19/HH/man/lmplot.Rd | 15 HH-3.1-19/HH/man/mmc.Rd | 12 HH-3.1-19/HH/man/mmcisomeans.Rd | 13 HH-3.1-19/HH/man/mmcplot.Rd | 16 HH-3.1-19/HH/man/odds.ratio.Rd | 7 HH-3.1-19/HH/man/panel.confintMMC.Rd | 4 HH-3.1-19/HH/man/panel.isomeans.Rd | 4 HH-3.1-19/HH/man/residual.plots.lattice.Rd | 2 HH-3.1-19/HH/man/showHex.Rd |only 91 files changed, 3391 insertions(+), 2133 deletions(-)