Title: The YUIMA Project Package for SDEs
Description: Simulation and Inference for Stochastic Differential Equations.
Author: YUIMA Project Team
Maintainer: Stefano M. Iacus <stefano.iacus@unimi.it>
Diff between yuima versions 1.0.73 dated 2015-07-15 and 1.0.77 dated 2015-11-20
DESCRIPTION | 6 MD5 | 32 - NAMESPACE | 388 ++++++++-------- NEWS | 7 R/ClassCogarch.R | 2 R/PseudoLogLikCOGARCH.R |only R/llag.R | 528 ++++++++++++++++++++++ R/mllag.R |only R/qmle.R | 1088 +++++++++++++++++++++++----------------------- R/simulate.R | 488 ++++++++++---------- R/spectralcov.R |only man/cce.Rd | 66 ++ man/llag.Rd | 120 ++++- man/mllag.Rd |only man/mpv.Rd | 234 ++++----- man/noisy.sampling.Rd | 320 ++++++------- man/qmle.Rd | 154 +++++- man/spectralcov.Rd |only src/PseudoLoglikCOGARCH.c |only src/cce_functions.c | 188 +++++++ 20 files changed, 2301 insertions(+), 1320 deletions(-)
Title: Access Vegetation Databases and Treat Taxonomy
Description: Handling of vegetation data from Turboveg (<http://www.synbiosys.alterra.nl/turboveg/>) and other sources (<http://www.vegetweb.de>). Taxonomic harmonization given appropriate taxonomic lists (e.g. the German taxonomical standard list "GermanSL", <http://www.botanik.uni-greifswald.de/GermanSL.html>).
Author: Florian Jansen <jansen@uni-greifswald.de>
Maintainer: Florian Jansen <jansen@uni-greifswald.de>
Diff between vegdata versions 0.8.5 dated 2015-11-06 and 0.8.6 dated 2015-11-20
vegdata-0.8.5/vegdata/R/vw.site.r |only vegdata-0.8.5/vegdata/R/vw.veg.r |only vegdata-0.8.6/vegdata/DESCRIPTION | 6 vegdata-0.8.6/vegdata/MD5 | 36 ++-- vegdata-0.8.6/vegdata/NAMESPACE | 4 vegdata-0.8.6/vegdata/R/child.r | 2 vegdata-0.8.6/vegdata/R/reflist.r | 7 vegdata-0.8.6/vegdata/R/tax.r | 11 - vegdata-0.8.6/vegdata/R/tax_add.r | 43 ++--- vegdata-0.8.6/vegdata/R/taxval.r | 16 + vegdata-0.8.6/vegdata/R/tv.compRefl.r | 71 ++++---- vegdata-0.8.6/vegdata/R/tv.home.r | 2 vegdata-0.8.6/vegdata/R/vegetweb.r | 108 +++++++++++-- vegdata-0.8.6/vegdata/inst/ChangeLog | 3 vegdata-0.8.6/vegdata/inst/doc/vegdata.pdf |binary vegdata-0.8.6/vegdata/inst/tvdata/Data/elbaue/TvAdmin.dbf |binary vegdata-0.8.6/vegdata/inst/tvdata/Data/elbaue/metadata.txt | 12 - vegdata-0.8.6/vegdata/man/vegetweb.Rd | 13 + vegdata-0.8.6/vegdata/tests/testthat/obs.rds |binary vegdata-0.8.6/vegdata/tests/testthat/test.R | 19 +- 20 files changed, 232 insertions(+), 121 deletions(-)
Title: Geostatistical Modelling of Spatially Referenced Prevalence Data
Description: It provides functions for both likelihood-based
and Bayesian analysis of spatially referenced prevalence data, and is
also an extension of the 'geoR' package.
Author: Emanuele Giorgi, Peter J. Diggle
Maintainer: Emanuele Giorgi <e.giorgi@lancaster.ac.uk>
Diff between PrevMap versions 1.2.3 dated 2015-09-17 and 1.3 dated 2015-11-20
DESCRIPTION | 9 MD5 | 80 NAMESPACE | 98 R/foo.R |13264 +++++++++++++++++++------------------ man/Laplace.sampling.Rd | 141 man/Laplace.sampling.lr.Rd | 109 man/adjust.sigma2.Rd | 98 man/autocor.plot.Rd | 51 man/binary.probit.Bayes.Rd | 179 man/binomial.logistic.Bayes.Rd | 263 man/binomial.logistic.MCML.Rd | 264 man/coef.PrevMap.Rd | 49 man/continuous.sample.Rd | 118 man/contour.pred.PrevMap.Rd | 51 man/control.mcmc.Bayes.Rd | 133 man/control.mcmc.MCML.Rd | 73 man/control.prior.Rd | 97 man/control.profile.Rd | 73 man/create.ID.coords.Rd | 64 man/data_sim.Rd | 47 man/dens.plot.Rd | 61 man/discrete.sample.Rd | 142 man/linear.model.Bayes.Rd | 207 man/linear.model.MLE.Rd | 215 man/loaloa.Rd | 67 man/loglik.ci.Rd | 53 man/loglik.linear.model.Rd | 83 man/matern.kernel.Rd | 67 man/plot.pred.PrevMap.Rd | 51 man/plot.profile.PrevMap.Rd | 59 man/plot.shape.matern.Rd | 59 man/poisson.log.MCML.Rd |only man/shape.matern.Rd | 91 man/spatial.pred.binomial.Bayes.Rd | 101 man/spatial.pred.binomial.MCML.Rd | 109 man/spatial.pred.linear.Bayes.Rd | 101 man/spatial.pred.linear.MLE.Rd | 105 man/spatial.pred.poisson.MCML.Rd |only man/summary.Bayes.PrevMap.Rd | 93 man/summary.PrevMap.Rd | 87 man/trace.plot.MCML.Rd | 47 man/trace.plot.Rd | 55 42 files changed, 8796 insertions(+), 8318 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 2.4 dated 2015-06-12 and 2.5 dated 2015-11-20
mlr-2.4/mlr/R/CostSensWeightedPairsLearner.R |only mlr-2.4/mlr/R/RLearner_classif_LiblineaRBinary.R |only mlr-2.4/mlr/R/RLearner_classif_LiblineaRLogReg.R |only mlr-2.4/mlr/R/RLearner_classif_LiblineaRMultiClass.R |only mlr-2.4/mlr/R/checkTaskCreation.R |only mlr-2.4/mlr/R/fixupData.R |only mlr-2.4/mlr/tests/testthat/test_classif_LiblineaRBinary.R |only mlr-2.4/mlr/tests/testthat/test_classif_LiblineaRLogReg.R |only mlr-2.4/mlr/tests/testthat/test_classif_LiblineaRMultiClass.R |only mlr-2.4/mlr/tests/testthat/test_learners_all.R |only mlr-2.5/mlr/DESCRIPTION | 41 mlr-2.5/mlr/MD5 | 1073 +++++----- mlr-2.5/mlr/NAMESPACE | 184 + mlr-2.5/mlr/NEWS | 111 + mlr-2.5/mlr/R/Aggregation.R | 11 mlr-2.5/mlr/R/BaggingWrapper.R | 20 mlr-2.5/mlr/R/BaseEnsemble.R | 7 mlr-2.5/mlr/R/BaseWrapper.R | 21 mlr-2.5/mlr/R/BenchmarkResultOrderLevels.R |only mlr-2.5/mlr/R/BenchmarkResult_operators.R | 94 mlr-2.5/mlr/R/ChainModel.R | 12 mlr-2.5/mlr/R/ClassifTask.R | 47 mlr-2.5/mlr/R/ClusterTask.R | 24 mlr-2.5/mlr/R/CostSensClassifWrapper.R | 15 mlr-2.5/mlr/R/CostSensRegrWrapper.R | 17 mlr-2.5/mlr/R/CostSensTask.R | 55 mlr-2.5/mlr/R/CostSensWeightedPairsWrapper.R |only mlr-2.5/mlr/R/FeatSelControl.R | 3 mlr-2.5/mlr/R/FeatSelWrapper.R | 2 mlr-2.5/mlr/R/Filter.R | 43 mlr-2.5/mlr/R/HomogeneousEnsemble.R | 28 mlr-2.5/mlr/R/ImputeMethods.R | 2 mlr-2.5/mlr/R/ImputeWrapper.R | 7 mlr-2.5/mlr/R/Learner.R | 94 mlr-2.5/mlr/R/Learner_properties.R | 39 mlr-2.5/mlr/R/Measure.R | 42 mlr-2.5/mlr/R/Measure_custom_resampled.R | 63 mlr-2.5/mlr/R/Measure_make_cost.R | 15 mlr-2.5/mlr/R/ModelMultiplexer.R | 14 mlr-2.5/mlr/R/ModelMultiplexerParamSet.R | 2 mlr-2.5/mlr/R/MulticlassWrapper.R | 24 mlr-2.5/mlr/R/MultilabelBinaryRelevanceWrapper.R |only mlr-2.5/mlr/R/MultilabelTask.R |only mlr-2.5/mlr/R/OptControl.R | 3 mlr-2.5/mlr/R/OptResult.R | 8 mlr-2.5/mlr/R/OverBaggingWrapper.R | 9 mlr-2.5/mlr/R/Prediction.R | 30 mlr-2.5/mlr/R/Prediction_operators.R | 115 - mlr-2.5/mlr/R/PreprocWrapper.R | 2 mlr-2.5/mlr/R/PreprocWrapperCaret.R | 19 mlr-2.5/mlr/R/RLearner.R | 55 mlr-2.5/mlr/R/RLearner_classif_IBk.R | 3 mlr-2.5/mlr/R/RLearner_classif_J48.R | 8 mlr-2.5/mlr/R/RLearner_classif_JRip.R | 5 mlr-2.5/mlr/R/RLearner_classif_LiblineaRL1L2SVC.R |only mlr-2.5/mlr/R/RLearner_classif_LiblineaRL1LogReg.R |only mlr-2.5/mlr/R/RLearner_classif_LiblineaRL2L1SVC.R |only mlr-2.5/mlr/R/RLearner_classif_LiblineaRL2LogReg.R |only mlr-2.5/mlr/R/RLearner_classif_LiblineaRL2SVC.R |only mlr-2.5/mlr/R/RLearner_classif_LiblineaRMultiClassSVC.R |only mlr-2.5/mlr/R/RLearner_classif_OneR.R | 3 mlr-2.5/mlr/R/RLearner_classif_PART.R | 4 mlr-2.5/mlr/R/RLearner_classif_ada.R | 1 mlr-2.5/mlr/R/RLearner_classif_avNNet.R |only mlr-2.5/mlr/R/RLearner_classif_bartMachine.R | 12 mlr-2.5/mlr/R/RLearner_classif_bdk.R | 5 mlr-2.5/mlr/R/RLearner_classif_binomial.R | 3 mlr-2.5/mlr/R/RLearner_classif_blackboost.R | 4 mlr-2.5/mlr/R/RLearner_classif_boosting.R | 2 mlr-2.5/mlr/R/RLearner_classif_bst.R | 2 mlr-2.5/mlr/R/RLearner_classif_cforest.R | 22 mlr-2.5/mlr/R/RLearner_classif_clusterSVM.R |only mlr-2.5/mlr/R/RLearner_classif_ctree.R | 4 mlr-2.5/mlr/R/RLearner_classif_dbnDNN.R |only mlr-2.5/mlr/R/RLearner_classif_dcSVM.R |only mlr-2.5/mlr/R/RLearner_classif_extraTrees.R | 4 mlr-2.5/mlr/R/RLearner_classif_fnn.R | 4 mlr-2.5/mlr/R/RLearner_classif_gaterSVM.R |only mlr-2.5/mlr/R/RLearner_classif_gbm.R | 19 mlr-2.5/mlr/R/RLearner_classif_geoDA.R | 4 mlr-2.5/mlr/R/RLearner_classif_glmboost.R | 14 mlr-2.5/mlr/R/RLearner_classif_glmnet.R | 11 mlr-2.5/mlr/R/RLearner_classif_hdrda.R | 3 mlr-2.5/mlr/R/RLearner_classif_kknn.R | 5 mlr-2.5/mlr/R/RLearner_classif_knn.R | 1 mlr-2.5/mlr/R/RLearner_classif_ksvm.R | 22 mlr-2.5/mlr/R/RLearner_classif_lda.R | 5 mlr-2.5/mlr/R/RLearner_classif_linDA.R | 1 mlr-2.5/mlr/R/RLearner_classif_lqa.R | 14 mlr-2.5/mlr/R/RLearner_classif_lssvm.R | 10 mlr-2.5/mlr/R/RLearner_classif_mda.R | 3 mlr-2.5/mlr/R/RLearner_classif_mlp.R |only mlr-2.5/mlr/R/RLearner_classif_multinom.R | 9 mlr-2.5/mlr/R/RLearner_classif_neuralnet.R |only mlr-2.5/mlr/R/RLearner_classif_nnTrain.R |only mlr-2.5/mlr/R/RLearner_classif_nnet.R | 13 mlr-2.5/mlr/R/RLearner_classif_nodeHarvest.R | 2 mlr-2.5/mlr/R/RLearner_classif_qda.R | 2 mlr-2.5/mlr/R/RLearner_classif_quaDA.R | 1 mlr-2.5/mlr/R/RLearner_classif_rFerns.R | 6 mlr-2.5/mlr/R/RLearner_classif_randomForest.R | 10 mlr-2.5/mlr/R/RLearner_classif_randomForestSRC.R | 15 mlr-2.5/mlr/R/RLearner_classif_ranger.R |only mlr-2.5/mlr/R/RLearner_classif_rda.R | 13 mlr-2.5/mlr/R/RLearner_classif_rknn.R |only mlr-2.5/mlr/R/RLearner_classif_rotationForest.R |only mlr-2.5/mlr/R/RLearner_classif_rpart.R | 2 mlr-2.5/mlr/R/RLearner_classif_saeDNN.R |only mlr-2.5/mlr/R/RLearner_classif_sda.R | 2 mlr-2.5/mlr/R/RLearner_classif_sparseLDA.R | 2 mlr-2.5/mlr/R/RLearner_classif_svm.R | 20 mlr-2.5/mlr/R/RLearner_classif_xgboost.R |only mlr-2.5/mlr/R/RLearner_classif_xyf.R | 2 mlr-2.5/mlr/R/RLearner_cluster_EM.R | 6 mlr-2.5/mlr/R/RLearner_cluster_FarthestFirst.R | 5 mlr-2.5/mlr/R/RLearner_cluster_SimpleKMeans.R | 5 mlr-2.5/mlr/R/RLearner_cluster_XMeans.R | 8 mlr-2.5/mlr/R/RLearner_cluster_cmeans.R | 6 mlr-2.5/mlr/R/RLearner_cluster_kmeans.R | 2 mlr-2.5/mlr/R/RLearner_multilabel_rFerns.R |only mlr-2.5/mlr/R/RLearner_regr_IBk.R | 3 mlr-2.5/mlr/R/RLearner_regr_LiblineaRL2L1SVR.R |only mlr-2.5/mlr/R/RLearner_regr_LiblineaRL2L2SVR.R |only mlr-2.5/mlr/R/RLearner_regr_avNNet.R |only mlr-2.5/mlr/R/RLearner_regr_bartMachine.R | 8 mlr-2.5/mlr/R/RLearner_regr_bcart.R | 8 mlr-2.5/mlr/R/RLearner_regr_bdk.R | 5 mlr-2.5/mlr/R/RLearner_regr_bgp.R | 8 mlr-2.5/mlr/R/RLearner_regr_bgpllm.R | 8 mlr-2.5/mlr/R/RLearner_regr_blackBoost.R | 4 mlr-2.5/mlr/R/RLearner_regr_blm.R | 8 mlr-2.5/mlr/R/RLearner_regr_brnn.R | 2 mlr-2.5/mlr/R/RLearner_regr_bst.R | 8 mlr-2.5/mlr/R/RLearner_regr_btgp.R | 12 mlr-2.5/mlr/R/RLearner_regr_btgpllm.R | 10 mlr-2.5/mlr/R/RLearner_regr_btlm.R | 8 mlr-2.5/mlr/R/RLearner_regr_cforest.R | 4 mlr-2.5/mlr/R/RLearner_regr_crs.R | 13 mlr-2.5/mlr/R/RLearner_regr_ctree.R | 4 mlr-2.5/mlr/R/RLearner_regr_cubist.R | 2 mlr-2.5/mlr/R/RLearner_regr_earth.R | 13 mlr-2.5/mlr/R/RLearner_regr_extraTrees.R | 5 mlr-2.5/mlr/R/RLearner_regr_fnn.R | 4 mlr-2.5/mlr/R/RLearner_regr_frbs.R | 44 mlr-2.5/mlr/R/RLearner_regr_gbm.R | 7 mlr-2.5/mlr/R/RLearner_regr_glmnet.R | 3 mlr-2.5/mlr/R/RLearner_regr_kknn.R | 5 mlr-2.5/mlr/R/RLearner_regr_km.R | 6 mlr-2.5/mlr/R/RLearner_regr_ksvm.R | 20 mlr-2.5/mlr/R/RLearner_regr_laGP.R | 3 mlr-2.5/mlr/R/RLearner_regr_lm.R | 11 mlr-2.5/mlr/R/RLearner_regr_mars.R | 1 mlr-2.5/mlr/R/RLearner_regr_mob.R | 4 mlr-2.5/mlr/R/RLearner_regr_nnet.R | 13 mlr-2.5/mlr/R/RLearner_regr_nodeHarvest.R | 2 mlr-2.5/mlr/R/RLearner_regr_pcr.R | 9 mlr-2.5/mlr/R/RLearner_regr_penalized_lasso.R | 3 mlr-2.5/mlr/R/RLearner_regr_penalized_ridge.R | 3 mlr-2.5/mlr/R/RLearner_regr_plsr.R | 5 mlr-2.5/mlr/R/RLearner_regr_randomForest.R | 10 mlr-2.5/mlr/R/RLearner_regr_randomForestSRC.R | 15 mlr-2.5/mlr/R/RLearner_regr_ranger.R |only mlr-2.5/mlr/R/RLearner_regr_rknn.R |only mlr-2.5/mlr/R/RLearner_regr_rpart.R | 2 mlr-2.5/mlr/R/RLearner_regr_rsm.R | 2 mlr-2.5/mlr/R/RLearner_regr_rvm.R | 14 mlr-2.5/mlr/R/RLearner_regr_slim.R | 4 mlr-2.5/mlr/R/RLearner_regr_svm.R | 18 mlr-2.5/mlr/R/RLearner_regr_xgboost.R |only mlr-2.5/mlr/R/RLearner_surv_CoxBoost.R | 12 mlr-2.5/mlr/R/RLearner_surv_cforest.R | 27 mlr-2.5/mlr/R/RLearner_surv_coxph.R | 7 mlr-2.5/mlr/R/RLearner_surv_cvglmnet.R | 3 mlr-2.5/mlr/R/RLearner_surv_glmboost.R | 7 mlr-2.5/mlr/R/RLearner_surv_optimCoxBoostPenalty.R | 23 mlr-2.5/mlr/R/RLearner_surv_penalized.R | 3 mlr-2.5/mlr/R/RLearner_surv_randomForestSRC.R | 18 mlr-2.5/mlr/R/RLearner_surv_ranger.R |only mlr-2.5/mlr/R/RLearner_surv_rpart.R | 2 mlr-2.5/mlr/R/RegrTask.R | 38 mlr-2.5/mlr/R/ResampleDesc.R | 10 mlr-2.5/mlr/R/ResampleInstance.R | 23 mlr-2.5/mlr/R/ResampleInstances.R | 105 mlr-2.5/mlr/R/ResamplePrediction.R | 30 mlr-2.5/mlr/R/StackedLearner.R | 420 +++ mlr-2.5/mlr/R/SupervisedTask.R | 33 mlr-2.5/mlr/R/SurvTask.R | 105 mlr-2.5/mlr/R/Task.R | 105 mlr-2.5/mlr/R/TaskDesc.R | 2 mlr-2.5/mlr/R/Task_operators.R | 167 + mlr-2.5/mlr/R/TuneControl.R | 34 mlr-2.5/mlr/R/TuneControlCMAES.R | 14 mlr-2.5/mlr/R/TuneControlDesign.R | 9 mlr-2.5/mlr/R/TuneControlGenSA.R | 27 mlr-2.5/mlr/R/TuneControlGrid.R | 8 mlr-2.5/mlr/R/TuneControlIrace.R | 26 mlr-2.5/mlr/R/TuneControlMBO.R | 36 mlr-2.5/mlr/R/TuneControlRandom.R | 17 mlr-2.5/mlr/R/TuneMultiCritControl.R | 21 mlr-2.5/mlr/R/TuneMultiCritControlGrid.R | 8 mlr-2.5/mlr/R/TuneMultiCritControlNSGA2.R | 42 mlr-2.5/mlr/R/TuneMultiCritControlRandom.R | 15 mlr-2.5/mlr/R/TuneResult.R | 4 mlr-2.5/mlr/R/TuneWrapper.R | 19 mlr-2.5/mlr/R/UnsupervisedTask.R | 22 mlr-2.5/mlr/R/WeightedClassesWrapper.R | 37 mlr-2.5/mlr/R/WrappedModel.R | 12 mlr-2.5/mlr/R/aggregations.R | 32 mlr-2.5/mlr/R/asROCRPrediction.R | 4 mlr-2.5/mlr/R/aucc.R | 2 mlr-2.5/mlr/R/benchmark.R | 38 mlr-2.5/mlr/R/benchmarkResult_mergers.R |only mlr-2.5/mlr/R/benchmarkTest.R |only mlr-2.5/mlr/R/checkLearner.R | 2 mlr-2.5/mlr/R/checkLearnerBeforeTrain.R | 24 mlr-2.5/mlr/R/checkMeasures.R | 2 mlr-2.5/mlr/R/checkParamSet.R |only mlr-2.5/mlr/R/checkPrediction.R | 8 mlr-2.5/mlr/R/checkTask.R | 4 mlr-2.5/mlr/R/convertBMRToRankMatrix.R |only mlr-2.5/mlr/R/convertMLBenchObjToTask.R |only mlr-2.5/mlr/R/datasets.R | 13 mlr-2.5/mlr/R/evalOptimizationState.R | 9 mlr-2.5/mlr/R/generateBenchmarkSummary.R |only mlr-2.5/mlr/R/generateCalibration.R |only mlr-2.5/mlr/R/generateCritDifferences.R |only mlr-2.5/mlr/R/generateFilterValues.R | 104 mlr-2.5/mlr/R/generateLearningCurve.R | 53 mlr-2.5/mlr/R/generatePartialPrediction.R |only mlr-2.5/mlr/R/generateROCRCurves.R | 2 mlr-2.5/mlr/R/generateRankMatrixAsBar.R |only mlr-2.5/mlr/R/generateThreshVsPerf.R | 217 +- mlr-2.5/mlr/R/getCaretParamSet.R |only mlr-2.5/mlr/R/getClassWeightParam.R |only mlr-2.5/mlr/R/getHyperPars.R | 3 mlr-2.5/mlr/R/getMultilabelBinaryPerformances.R |only mlr-2.5/mlr/R/getNestedTuneResults.R | 4 mlr-2.5/mlr/R/getResampleExtract.R |only mlr-2.5/mlr/R/helpers.R | 33 mlr-2.5/mlr/R/learners.R | 2 mlr-2.5/mlr/R/listLearners.R | 83 mlr-2.5/mlr/R/listMeasures.R | 2 mlr-2.5/mlr/R/makeLearner.R |only mlr-2.5/mlr/R/measures.R | 59 mlr-2.5/mlr/R/mergeSmallFactorLevels.R | 3 mlr-2.5/mlr/R/options.R | 3 mlr-2.5/mlr/R/performance.R | 40 mlr-2.5/mlr/R/plotBenchmarkResult.R |only mlr-2.5/mlr/R/plotLearnerPrediction.R | 14 mlr-2.5/mlr/R/plotViperCharts.R | 2 mlr-2.5/mlr/R/predict.R | 18 mlr-2.5/mlr/R/predictLearner.R | 23 mlr-2.5/mlr/R/relativeOverfitting.R |only mlr-2.5/mlr/R/resample.R | 8 mlr-2.5/mlr/R/selectFeatures.R | 2 mlr-2.5/mlr/R/setPredictType.R | 5 mlr-2.5/mlr/R/setThreshold.R | 42 mlr-2.5/mlr/R/smote.R | 4 mlr-2.5/mlr/R/train.R | 18 mlr-2.5/mlr/R/trainLearner.R | 2 mlr-2.5/mlr/R/tuneCMAES.R | 23 mlr-2.5/mlr/R/tuneGenSA.R | 11 mlr-2.5/mlr/R/tuneGrid.R | 2 mlr-2.5/mlr/R/tuneIrace.R | 15 mlr-2.5/mlr/R/tuneMBO.R | 10 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mlr-2.5/mlr/tests/testthat/test_base_resample_dps.R |only mlr-2.5/mlr/tests/testthat/test_base_resample_stratify.R | 2 mlr-2.5/mlr/tests/testthat/test_base_selectFeatures.R | 2 mlr-2.5/mlr/tests/testthat/test_base_setPredictType.R | 4 mlr-2.5/mlr/tests/testthat/test_base_tuning.R | 47 mlr-2.5/mlr/tests/testthat/test_classif_LibLineaRMultiClassSVC.R |only mlr-2.5/mlr/tests/testthat/test_classif_LiblineaRL1L2SVC.R |only mlr-2.5/mlr/tests/testthat/test_classif_LiblineaRL1LogReg.R |only mlr-2.5/mlr/tests/testthat/test_classif_LiblineaRL2L1SVC.R |only mlr-2.5/mlr/tests/testthat/test_classif_LiblineaRL2LogReg.R |only mlr-2.5/mlr/tests/testthat/test_classif_LiblineaRL2SVC.R |only mlr-2.5/mlr/tests/testthat/test_classif_avNNet.R |only mlr-2.5/mlr/tests/testthat/test_classif_clusterSVM.R |only mlr-2.5/mlr/tests/testthat/test_classif_dbnDNN.R |only mlr-2.5/mlr/tests/testthat/test_classif_dcSVM.R |only mlr-2.5/mlr/tests/testthat/test_classif_gaterSVM.R |only mlr-2.5/mlr/tests/testthat/test_classif_gbm.R | 2 mlr-2.5/mlr/tests/testthat/test_classif_mlp.R |only mlr-2.5/mlr/tests/testthat/test_classif_multinom.R | 4 mlr-2.5/mlr/tests/testthat/test_classif_neuralnet.R |only mlr-2.5/mlr/tests/testthat/test_classif_nnTrain.R |only mlr-2.5/mlr/tests/testthat/test_classif_nnet.R | 28 mlr-2.5/mlr/tests/testthat/test_classif_ranger.R |only mlr-2.5/mlr/tests/testthat/test_classif_rknn.R |only mlr-2.5/mlr/tests/testthat/test_classif_rotationForest.R |only mlr-2.5/mlr/tests/testthat/test_classif_saeDNN.R |only mlr-2.5/mlr/tests/testthat/test_classif_svm.R | 9 mlr-2.5/mlr/tests/testthat/test_classif_xgboost.R |only mlr-2.5/mlr/tests/testthat/test_featsel_FilterWrapper.R | 1 mlr-2.5/mlr/tests/testthat/test_featsel_filterFeatures.R | 25 mlr-2.5/mlr/tests/testthat/test_learners_all_classif.R |only mlr-2.5/mlr/tests/testthat/test_learners_all_clusters.R |only mlr-2.5/mlr/tests/testthat/test_learners_all_general.R |only mlr-2.5/mlr/tests/testthat/test_learners_all_regr.R |only mlr-2.5/mlr/tests/testthat/test_learners_classiflabelswitch.R | 7 mlr-2.5/mlr/tests/testthat/test_parallel_all.R | 16 mlr-2.5/mlr/tests/testthat/test_regr_IBk.R |only mlr-2.5/mlr/tests/testthat/test_regr_LiblineaRL2L1SVR.R |only mlr-2.5/mlr/tests/testthat/test_regr_LiblineaRL2L2SVR.R |only mlr-2.5/mlr/tests/testthat/test_regr_avNNet.R |only mlr-2.5/mlr/tests/testthat/test_regr_bartMachine.R |only mlr-2.5/mlr/tests/testthat/test_regr_bcart.R |only mlr-2.5/mlr/tests/testthat/test_regr_bdk.R |only mlr-2.5/mlr/tests/testthat/test_regr_bgp.R |only mlr-2.5/mlr/tests/testthat/test_regr_bgpllm.R |only mlr-2.5/mlr/tests/testthat/test_regr_blackboost.R |only mlr-2.5/mlr/tests/testthat/test_regr_blm.R |only mlr-2.5/mlr/tests/testthat/test_regr_brnn.R |only mlr-2.5/mlr/tests/testthat/test_regr_bst.R |only mlr-2.5/mlr/tests/testthat/test_regr_btgp.R |only mlr-2.5/mlr/tests/testthat/test_regr_btgpllm.R |only mlr-2.5/mlr/tests/testthat/test_regr_btlm.R |only mlr-2.5/mlr/tests/testthat/test_regr_cforest.R |only mlr-2.5/mlr/tests/testthat/test_regr_crs.R |only mlr-2.5/mlr/tests/testthat/test_regr_ctree.R |only mlr-2.5/mlr/tests/testthat/test_regr_cubist.R |only mlr-2.5/mlr/tests/testthat/test_regr_earth.R |only mlr-2.5/mlr/tests/testthat/test_regr_elmNN.R |only mlr-2.5/mlr/tests/testthat/test_regr_extraTrees.R |only mlr-2.5/mlr/tests/testthat/test_regr_fnn.R |only mlr-2.5/mlr/tests/testthat/test_regr_frbs.R |only mlr-2.5/mlr/tests/testthat/test_regr_gbm.R |only mlr-2.5/mlr/tests/testthat/test_regr_glmnet.R |only mlr-2.5/mlr/tests/testthat/test_regr_kknn.R |only mlr-2.5/mlr/tests/testthat/test_regr_km.R |only mlr-2.5/mlr/tests/testthat/test_regr_ksvm.R |only mlr-2.5/mlr/tests/testthat/test_regr_laGP.R |only mlr-2.5/mlr/tests/testthat/test_regr_lm.R |only mlr-2.5/mlr/tests/testthat/test_regr_mob.R |only mlr-2.5/mlr/tests/testthat/test_regr_nnet.R |only mlr-2.5/mlr/tests/testthat/test_regr_nodeHarvest.R |only mlr-2.5/mlr/tests/testthat/test_regr_penalized_lasso.R |only mlr-2.5/mlr/tests/testthat/test_regr_penalized_ridge.R |only mlr-2.5/mlr/tests/testthat/test_regr_plsr.R |only mlr-2.5/mlr/tests/testthat/test_regr_randomForest.R |only mlr-2.5/mlr/tests/testthat/test_regr_randomForestSRC.R |only mlr-2.5/mlr/tests/testthat/test_regr_randomForest_se.R |only mlr-2.5/mlr/tests/testthat/test_regr_ranger.R |only mlr-2.5/mlr/tests/testthat/test_regr_rknn.R |only mlr-2.5/mlr/tests/testthat/test_regr_rpart.R |only mlr-2.5/mlr/tests/testthat/test_regr_rsm.R |only mlr-2.5/mlr/tests/testthat/test_regr_slim.R |only mlr-2.5/mlr/tests/testthat/test_regr_svm.R |only mlr-2.5/mlr/tests/testthat/test_regr_xgboost.R |only mlr-2.5/mlr/tests/testthat/test_regr_xyf.R |only mlr-2.5/mlr/tests/testthat/test_stack.R | 64 mlr-2.5/mlr/tests/testthat/test_surv_glmboost.R | 2 mlr-2.5/mlr/tests/testthat/test_surv_randomForestSRC.R | 2 mlr-2.5/mlr/tests/testthat/test_surv_ranger.R |only mlr-2.5/mlr/tests/testthat/test_surv_rpart.R |only mlr-2.5/mlr/tests/testthat/test_tune_ModelMultiplexer.R | 10 mlr-2.5/mlr/tests/testthat/test_tune_tuneCMAES.R | 21 mlr-2.5/mlr/tests/testthat/test_tune_tuneGenSA.R |only mlr-2.5/mlr/tests/testthat/test_tune_tuneGrid.R | 13 mlr-2.5/mlr/tests/testthat/test_tune_tuneIrace.R | 116 - mlr-2.5/mlr/tests/testthat/test_tune_tuneMBO.R | 35 mlr-2.5/mlr/tests/testthat/test_tune_tuneParamsMultiCrit.R | 48 mlr-2.5/mlr/tests/testthat/test_tune_tuneRandom.R | 15 mlr-2.5/mlr/tests/testthat/test_tune_tuneThreshold.R | 2 mlr-2.5/mlr/vignettes/mlr.Rmd | 57 629 files changed, 6860 insertions(+), 3810 deletions(-)
Title: A Modern and Flexible Web Client for R
Description: The curl() and curl_download() functions provide highly configurable
drop-in replacements for base url() and download.file() with better performance,
support for encryption (https://, ftps://), 'gzip' compression, authentication,
and other 'libcurl' goodies. The core of the package implements a framework for
performing fully customized requests where data can be processed either in memory,
on disk, or streaming via the callback or connection interfaces. Some knowledge of
'libcurl' is recommended; for a more-user-friendly web client see the 'httr' package
which builds on this package with HTTP specific tools and logic.
Author: Jeroen Ooms [cre, aut],
Hadley Wickham [ctb],
RStudio [cph]
Maintainer: Jeroen Ooms <jeroen.ooms@stat.ucla.edu>
Diff between curl versions 0.9.3 dated 2015-08-25 and 0.9.4 dated 2015-11-20
curl-0.9.3/curl/src/winhttp32.def |only curl-0.9.3/curl/src/winhttp64.def |only curl-0.9.3/curl/tools/options.R |only curl-0.9.4/curl/DESCRIPTION | 6 +++--- curl-0.9.4/curl/MD5 | 18 +++++++++--------- curl-0.9.4/curl/NEWS | 5 +++++ curl-0.9.4/curl/R/options.R |only curl-0.9.4/curl/R/utilities.R | 18 ------------------ curl-0.9.4/curl/man/curl_options.Rd | 22 ++++++++++++++-------- curl-0.9.4/curl/src/Makevars.in | 5 ----- curl-0.9.4/curl/src/Makevars.win | 20 ++++++++------------ curl-0.9.4/curl/src/winhttp32.def.in |only curl-0.9.4/curl/src/winhttp64.def.in |only 13 files changed, 39 insertions(+), 55 deletions(-)
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
Maintainer: Michael Sweeting <mjs212@medschl.cam.ac.uk>
Diff between bcrm versions 0.4.5 dated 2015-09-23 and 0.4.6 dated 2015-11-20
bcrm-0.4.5/bcrm/R/bcrm_0.4.5.R |only bcrm-0.4.6/bcrm/DESCRIPTION | 18 +++++++++++------- bcrm-0.4.6/bcrm/MD5 | 14 +++++++------- bcrm-0.4.6/bcrm/NAMESPACE | 4 ++-- bcrm-0.4.6/bcrm/NEWS | 7 +++++++ bcrm-0.4.6/bcrm/R/bcrm_0.4.6.R |only bcrm-0.4.6/bcrm/man/bcrm-package.Rd | 4 ++-- bcrm-0.4.6/bcrm/man/bcrm.Rd | 6 +++++- bcrm-0.4.6/bcrm/man/print.bcrm.Rd | 6 +++++- 9 files changed, 39 insertions(+), 20 deletions(-)
Title: UK National River Flow Archive Data from R
Description: Utility functions to retrieve data from the UK National River Flow
Archive. The package contains R wrappers to the UK NRFA data temporary-API.
There are functions to retrieve stations falling in a bounding box,
to generate a map and extracting time series and general information.
Author: Claudia Vitolo [aut, cre], Matthew Fry [ctb]
Maintainer: Claudia Vitolo <cvitolodev@gmail.com>
Diff between rnrfa versions 0.2.1 dated 2015-11-15 and 0.3.0 dated 2015-11-20
rnrfa-0.2.1/rnrfa/R/NRFA_TSdata.R |only rnrfa-0.2.1/rnrfa/R/NRFA_TSmetadata.R |only rnrfa-0.2.1/rnrfa/man/NRFA_TSdata.Rd |only rnrfa-0.2.1/rnrfa/man/NRFA_TSmetadata.Rd |only rnrfa-0.3.0/rnrfa/DESCRIPTION | 6 +++--- rnrfa-0.3.0/rnrfa/MD5 | 16 ++++++++++------ rnrfa-0.3.0/rnrfa/NAMESPACE | 6 ++++-- rnrfa-0.3.0/rnrfa/R/CMR.R |only rnrfa-0.3.0/rnrfa/R/CMRmeta.R |only rnrfa-0.3.0/rnrfa/R/GDF.R |only rnrfa-0.3.0/rnrfa/R/GDFmeta.R |only rnrfa-0.3.0/rnrfa/man/CMR.Rd |only rnrfa-0.3.0/rnrfa/man/CMRmeta.Rd |only rnrfa-0.3.0/rnrfa/man/GDF.Rd |only rnrfa-0.3.0/rnrfa/man/GDFmeta.Rd |only 15 files changed, 17 insertions(+), 11 deletions(-)
Title: Estimation of Diagonal Elements of Sparse Precision-Matrices
Description: Several estimators of the diagonal elements of a sparse precision
(inverse covariance) matrix from a sample of Gaussian vectors for a
given matrix of estimated marginal regression coefficients.
To install package 'gurobi', instructions at
http://user.gurobi.com/download/gurobi-optimizer and
http://www.gurobi.com/documentation/6.0/refman/r_api_overview.html.
Author: Arnak Dalalyan [aut], Samuel Balmand [aut, cre]
Maintainer: Samuel Balmand <Samuel.Balmand@ensg.eu>
Diff between DESP versions 0.1-4 dated 2015-10-23 and 0.1-5 dated 2015-11-20
ChangeLog | 5 + DESCRIPTION | 8 +- MD5 | 28 +++++----- NAMESPACE | 2 R/DESP_SRL_B.R | 38 ++++++++----- R/sqR_Lasso.R | 131 +++++++++++++---------------------------------- man/DESP-internal.Rd | 2 man/DESP-package.Rd | 4 - man/DESP_SRL_B.Rd | 9 ++- man/scsSOCP.Rd | 94 +++++++++++++++++++++++++++++++++ man/sqR_Lasso.Rd | 14 +++-- src/Makevars | 4 - src/scsSRL_B.c |only src/scsSolveSOCP.c | 24 ++++++-- src/scsSqR_Lasso.c |only src/scsSqR_Lasso_solve.c |only src/scsSqR_Lasso_solve.h |only 17 files changed, 224 insertions(+), 139 deletions(-)
Title: Model-Based Clustering and Classification with the Multivariate
t Distribution
Description: Fits mixtures of multivariate t-distributions (with eigen-decomposed covariance structure) via the expectation conditional-maximization algorithm under a clustering or classification paradigm.
Author: Jeffrey L. Andrews, Jaymeson R. Wickins, Nicholas M. Boers, Paul D. McNicholas
Maintainer: Jeffrey L. Andrews <jeff.andrews@ubc.ca>
Diff between teigen versions 2.0.81 dated 2015-05-27 and 2.1.0 dated 2015-11-20
teigen-2.0.81/teigen/R/deltaup.R |only teigen-2.0.81/teigen/R/estimateTime.R |only teigen-2.0.81/teigen/R/modelgen.R |only teigen-2.0.81/teigen/R/plot.teigen.R |only teigen-2.0.81/teigen/R/print.teigen.R |only teigen-2.0.81/teigen/R/summary.teigen.R |only teigen-2.0.81/teigen/R/tBICcalc.R |only teigen-2.0.81/teigen/R/tICLcalc.R |only teigen-2.0.81/teigen/R/taginit.R |only teigen-2.0.81/teigen/R/tagupdate.R |only teigen-2.0.81/teigen/R/tcontrandz.R |only teigen-2.0.81/teigen/R/tdginit.R |only teigen-2.0.81/teigen/R/tdgupdate.R |only teigen-2.0.81/teigen/R/tdiscrandz.R |only teigen-2.0.81/teigen/R/teigen.R |only teigen-2.0.81/teigen/R/teigen.parallel.R |only teigen-2.0.81/teigen/R/tfminup.R |only teigen-2.0.81/teigen/R/tft.R |only teigen-2.0.81/teigen/R/tgivenz.R |only teigen-2.0.81/teigen/R/tkmeansz.R |only teigen-2.0.81/teigen/R/tlambdaginit.R |only teigen-2.0.81/teigen/R/tlambdagupdate.R |only teigen-2.0.81/teigen/R/tmuginit.R |only teigen-2.0.81/teigen/R/tmugupdate.R |only teigen-2.0.81/teigen/R/tngupdate.R |only teigen-2.0.81/teigen/R/tpigupdate.R |only teigen-2.0.81/teigen/R/tsginit.R |only teigen-2.0.81/teigen/R/tsginitc.R |only teigen-2.0.81/teigen/R/tsgupdate.R |only teigen-2.0.81/teigen/R/tsigmainvup.R |only teigen-2.0.81/teigen/R/tsigmaup.R |only teigen-2.0.81/teigen/R/tuniformz.R |only teigen-2.0.81/teigen/R/tvginit.R |only teigen-2.0.81/teigen/R/twinit.R |only teigen-2.0.81/teigen/R/twupdate.R |only teigen-2.0.81/teigen/R/tzupdate.R |only teigen-2.0.81/teigen/R/yxf7.R |only teigen-2.0.81/teigen/R/yxf8.R |only teigen-2.0.81/teigen/man/teigen.parallel.Rd |only teigen-2.1.0/teigen/ChangeLog | 14 +++++ teigen-2.1.0/teigen/DESCRIPTION | 16 +++--- teigen-2.1.0/teigen/MD5 | 62 ++++++------------------- teigen-2.1.0/teigen/NAMESPACE | 8 ++- teigen-2.1.0/teigen/R/teigen.r |only teigen-2.1.0/teigen/data |only teigen-2.1.0/teigen/man/ckd.Rd |only teigen-2.1.0/teigen/man/plot.teigen.Rd | 59 +++++++++++++++++++---- teigen-2.1.0/teigen/man/print.teigen.Rd | 4 - teigen-2.1.0/teigen/man/summary.teigen.Rd | 13 ++++- teigen-2.1.0/teigen/man/teigen-package.Rd | 10 ++-- teigen-2.1.0/teigen/man/teigen.Rd | 69 ++++++++++++++++++---------- teigen-2.1.0/teigen/src |only 52 files changed, 154 insertions(+), 101 deletions(-)
Title: Variable Selection for Generalized Linear Mixed Models by
L1-Penalized Estimation
Description: A variable selection approach for generalized linear mixed models by L1-penalized estimation is provided.
Author: Andreas Groll
Maintainer: Andreas Groll <groll@mathematik.uni-muenchen.de>
Diff between glmmLasso versions 1.3.6 dated 2015-09-17 and 1.3.7 dated 2015-11-20
DESCRIPTION | 8 ++-- MD5 | 8 ++-- R/glmmLasso_noRE.R | 77 +++++++++++++++++++++++++++++---------------- R/glmm_final.smooth_noRE.R | 26 ++++----------- man/glmmLasso.rd | 4 +- 5 files changed, 68 insertions(+), 55 deletions(-)
Title: A Package for Bayesian Meta-Analysis and Meta-Regression
Description: Provides a collection of functions for conducting meta-analyses under Bayesian context in R. The package includes functions for computing various effect size or outcome measures (e.g. odds ratios, mean difference and incidence rate ratio) for different types of data based on MCMC simulations. Users are allowed to fit fixed- and random-effects models with different priors to the data. Meta-regression can be carried out if effects of additional covariates are observed. Furthermore, the package provides functions for creating posterior distribution plots and forest plot to display main model output. Traceplots and some other diagnostic plots are also available for assessing model fit and performance.
Author: Tao Ding, Gianluca Baio
Maintainer: Gianluca Baio <gianluca@stats.ucl.ac.uk>
Diff between bmeta versions 0.1 dated 2015-10-29 and 0.1.1 dated 2015-11-20
DESCRIPTION | 8 ++++---- MD5 | 6 +++--- R/bmeta.R | 44 ++++++++++++++++++++++++++------------------ man/bmeta-package.Rd | 4 ++-- 4 files changed, 35 insertions(+), 27 deletions(-)
Title: Tools to Create Gene Sets
Description: A set of functions to create SQL tables of gene and SNP information and compose them into a SNP Set, for example for use with the RSNPset package, or to export to a PLINK set.
Author: Chanhee Yi, Alexander Sibley, and Kouros Owzar
Maintainer: Alexander Sibley <alexander.sibley@dm.duke.edu>
Diff between snplist versions 0.14 dated 2015-09-21 and 0.15 dated 2015-11-20
DESCRIPTION | 8 ++++---- MD5 | 16 ++++++++-------- NEWS | 8 ++++++-- R/getBioMartData.R | 2 +- inst/doc/snplist.Rnw | 2 +- inst/doc/snplist.pdf |binary man/getBioMartData.Rd | 17 ++++++++++++++--- man/snplist-package.Rd | 4 ++-- vignettes/snplist.Rnw | 2 +- 9 files changed, 37 insertions(+), 22 deletions(-)
Title: Structure for Organizing Monte Carlo Simulation Designs
Description: Provides tools to help organize Monte Carlo simulations in R. The
tools provided control the structure and back-end of the Monte Carlo simulations
by utilizing a generate-analyse-summarise strategy. The functions control common
simulation issues such as re-simulating non-convergent results, support parallel
back-end computations, save and restore temporary files, aggregate results
across independent nodes, and provide native support for debugging.
Author: Phil Chalmers [aut, cre]
Maintainer: Phil Chalmers <rphilip.chalmers@gmail.com>
Diff between SimDesign versions 0.3 dated 2015-10-05 and 0.4.1 dated 2015-11-20
SimDesign-0.3/SimDesign/man/main.Rd |only SimDesign-0.4.1/SimDesign/DESCRIPTION | 23 +- SimDesign-0.4.1/SimDesign/MD5 | 51 ++--- SimDesign-0.4.1/SimDesign/NAMESPACE | 6 SimDesign-0.4.1/SimDesign/R/SimDesign.R | 3 SimDesign-0.4.1/SimDesign/R/SimDesign_functions.R | 48 +++- SimDesign-0.4.1/SimDesign/R/aggregate_simulations.R | 31 ++- SimDesign-0.4.1/SimDesign/R/analysis.R | 49 +++- SimDesign-0.4.1/SimDesign/R/functions.R | 116 ++++++----- SimDesign-0.4.1/SimDesign/R/runSimulation.R | 168 ++++++++++------- SimDesign-0.4.1/SimDesign/R/summary_functions.R | 160 +++++++++++----- SimDesign-0.4.1/SimDesign/R/util.R | 5 SimDesign-0.4.1/SimDesign/man/ECR.Rd | 9 SimDesign-0.4.1/SimDesign/man/EDR.Rd | 13 - SimDesign-0.4.1/SimDesign/man/MAE.Rd | 29 ++ SimDesign-0.4.1/SimDesign/man/RE.Rd | 10 - SimDesign-0.4.1/SimDesign/man/RMSE.Rd | 33 ++- SimDesign-0.4.1/SimDesign/man/SimDesign.Rd | 2 SimDesign-0.4.1/SimDesign/man/SimDesign_functions.Rd | 16 + SimDesign-0.4.1/SimDesign/man/aggregate_simulations.Rd | 12 - SimDesign-0.4.1/SimDesign/man/analyse.Rd | 21 +- SimDesign-0.4.1/SimDesign/man/bias.Rd | 30 ++- SimDesign-0.4.1/SimDesign/man/check_error.Rd | 6 SimDesign-0.4.1/SimDesign/man/generate.Rd | 13 - SimDesign-0.4.1/SimDesign/man/runSimulation.Rd | 163 +++++++++------- SimDesign-0.4.1/SimDesign/man/summarise.Rd | 17 + SimDesign-0.4.1/SimDesign/tests/tests/test-SimDesign.R | 58 +++++ 27 files changed, 696 insertions(+), 396 deletions(-)
Title: Efficient Score Statistics for Genome-Wide SNP Set Analysis
Description: An implementation of the use of efficient score statistics
in genome-wide SNP set analysis with complex traits. Three standard score statistics
(Cox, binomial, and Gaussian) are provided, but the package is easily extensible to
include others. Code implementing the inferential procedure is primarily written in C++ and
utilizes parallelization of the analysis to reduce runtime. A supporting function offers
simple computation of observed, permutation, and FWER and FDR adjusted p-values.
Author: Chanhee Yi, Alexander Sibley, and Kouros Owzar
Maintainer: Alexander Sibley <alexander.sibley@dm.duke.edu>
Diff between RSNPset versions 0.4 dated 2015-02-11 and 0.5 dated 2015-11-20
RSNPset-0.4/RSNPset/inst/doc/rsnpset.R |only RSNPset-0.4/RSNPset/inst/doc/rsnpset.Rnw |only RSNPset-0.4/RSNPset/inst/doc/rsnpset.pdf |only RSNPset-0.4/RSNPset/vignettes/rsnpset.Rnw |only RSNPset-0.5/RSNPset/DESCRIPTION | 18 +++++++++--------- RSNPset-0.5/RSNPset/MD5 | 22 +++++++++++----------- RSNPset-0.5/RSNPset/NAMESPACE | 1 + RSNPset-0.5/RSNPset/NEWS | 5 +++++ RSNPset-0.5/RSNPset/R/rsnpset.R | 2 +- RSNPset-0.5/RSNPset/build/vignette.rds |binary RSNPset-0.5/RSNPset/inst/doc/RSNPset.R |only RSNPset-0.5/RSNPset/inst/doc/RSNPset.Rnw |only RSNPset-0.5/RSNPset/inst/doc/RSNPset.pdf |only RSNPset-0.5/RSNPset/man/RSNPset-package.Rd | 6 +++--- RSNPset-0.5/RSNPset/man/rsnpset.Rd | 6 ++++-- RSNPset-0.5/RSNPset/vignettes/RSNPset.Rnw |only 16 files changed, 34 insertions(+), 26 deletions(-)
Title: PRIM Survival Regression Classification
Description: Performs a unified treatment of Bump Hunting by Patient Rule Induction Method (PRIM) in Survival, Regression and Classification settings (SRC). The current version is a development release that only implements the case of a survival response. New features will be added soon as they are available.
Author: Jean-Eudes Dazard [aut, cre], Michael Choe [ctb], Michael LeBlanc [ctb], Alberto Santana [ctb]
Maintainer: Jean-Eudes Dazard <jxd101@case.edu>
Diff between PRIMsrc versions 0.6.2 dated 2015-10-11 and 0.6.3 dated 2015-11-20
PRIMsrc-0.6.2/PRIMsrc/inst/doc/Abstract.JCB2016.pdf |only PRIMsrc-0.6.2/PRIMsrc/inst/doc/PRIMsrc_0.6.2.pdf |only PRIMsrc-0.6.3/PRIMsrc/DESCRIPTION | 8 PRIMsrc-0.6.3/PRIMsrc/MD5 | 51 PRIMsrc-0.6.3/PRIMsrc/NAMESPACE | 28 PRIMsrc-0.6.3/PRIMsrc/R/PRIMsrc.internal.r | 344 +- PRIMsrc-0.6.3/PRIMsrc/R/PRIMsrc.r | 3094 ++++++++++---------- PRIMsrc-0.6.3/PRIMsrc/inst/CITATION | 232 - PRIMsrc-0.6.3/PRIMsrc/inst/NEWS | 298 + PRIMsrc-0.6.3/PRIMsrc/inst/doc/PRIMsrc_0.6.3.pdf |only PRIMsrc-0.6.3/PRIMsrc/man/PrimSRC-package.Rd | 34 PRIMsrc-0.6.3/PRIMsrc/man/PrimSRC.news.Rd | 8 PRIMsrc-0.6.3/PRIMsrc/man/Real.1-data.Rd | 13 PRIMsrc-0.6.3/PRIMsrc/man/Real.2-data.Rd | 25 PRIMsrc-0.6.3/PRIMsrc/man/Synthetic.1-data.Rd | 8 PRIMsrc-0.6.3/PRIMsrc/man/Synthetic.1b-data.Rd | 8 PRIMsrc-0.6.3/PRIMsrc/man/Synthetic.2-data.Rd | 8 PRIMsrc-0.6.3/PRIMsrc/man/Synthetic.3-data.Rd | 8 PRIMsrc-0.6.3/PRIMsrc/man/Synthetic.4-data.Rd | 8 PRIMsrc-0.6.3/PRIMsrc/man/plot.Rd | 80 PRIMsrc-0.6.3/PRIMsrc/man/plot_boxkm.Rd | 42 PRIMsrc-0.6.3/PRIMsrc/man/plot_boxtrace.Rd | 38 PRIMsrc-0.6.3/PRIMsrc/man/plot_boxtraj.Rd | 62 PRIMsrc-0.6.3/PRIMsrc/man/plot_profile.Rd | 48 PRIMsrc-0.6.3/PRIMsrc/man/predict.Rd | 83 PRIMsrc-0.6.3/PRIMsrc/man/print.Rd | 54 PRIMsrc-0.6.3/PRIMsrc/man/sbh.Rd | 184 - PRIMsrc-0.6.3/PRIMsrc/man/summary.Rd | 54 28 files changed, 2509 insertions(+), 2311 deletions(-)
Title: Nested Association Mapping Analysis
Description: Designed for association studies in nested association mapping (NAM) panels, also handling biparental and random panels. It includes functions for genome-wide associations mapping of multiple populations, marker quality control, solving mixed models and finding variance components through REML and Gibbs sampling.
Author: Alencar Xavier, William Muir, Katy Rainey, Shizhong Xu.
Maintainer: Alencar Xavier <xaviera@purdue.edu>
Diff between NAM versions 1.4.1 dated 2015-10-16 and 1.4.2 dated 2015-11-20
DESCRIPTION | 6 MD5 | 20 - R/gwas.R | 1 R/gwas2.R | 1 R/wgr.R | 4 build/vignette.rds |binary inst/CITATION | 1 inst/doc/vignette.Rmd | 428 +++++++++++-------------- inst/doc/vignette.html | 838 +++++++++++++++++++------------------------------ man/NAM-package.Rd | 2 vignettes/vignette.Rmd | 428 +++++++++++-------------- 11 files changed, 738 insertions(+), 991 deletions(-)
Title: Influential Case Detection Methods for Factor Analysis and
Structural Equation Models
Description: Tools for detecting and summarize influential cases that
can affect exploratory and confirmatory factor analysis models as well as
structural equation models more generally.
Author: Phil Chalmers [aut, cre]
Maintainer: Phil Chalmers <rphilip.chalmers@gmail.com>
Diff between faoutlier versions 0.5 dated 2015-04-27 and 0.6.1 dated 2015-11-20
faoutlier-0.5/faoutlier/inst/doc |only faoutlier-0.6.1/faoutlier/DESCRIPTION | 11 ++--- faoutlier-0.6.1/faoutlier/MD5 | 40 +++++++++--------- faoutlier-0.6.1/faoutlier/NAMESPACE | 6 ++ faoutlier-0.6.1/faoutlier/R/GOF.R | 37 ++++++++++++---- faoutlier-0.6.1/faoutlier/R/LD.R | 32 +++++++------- faoutlier-0.6.1/faoutlier/R/faoutlier.R | 34 ++++++++------- faoutlier-0.6.1/faoutlier/R/gCD.R | 44 ++++++++++++++++---- faoutlier-0.6.1/faoutlier/inst/CITATION |only faoutlier-0.6.1/faoutlier/man/GOF.Rd | 21 +++++++-- faoutlier-0.6.1/faoutlier/man/LD.Rd | 10 ++-- faoutlier-0.6.1/faoutlier/man/faoutlier.Rd | 2 faoutlier-0.6.1/faoutlier/man/forward.search.Rd | 7 +-- faoutlier-0.6.1/faoutlier/man/gCD.Rd | 18 +++++++- faoutlier-0.6.1/faoutlier/man/holzinger.Rd | 2 faoutlier-0.6.1/faoutlier/man/holzinger.outlier.Rd | 2 faoutlier-0.6.1/faoutlier/man/obs.resid.Rd | 5 +- faoutlier-0.6.1/faoutlier/man/robustMD.Rd | 3 - faoutlier-0.6.1/faoutlier/man/setCluster.Rd | 3 - faoutlier-0.6.1/faoutlier/tests/testthat/test-GOF.R | 2 faoutlier-0.6.1/faoutlier/tests/testthat/test-LD.R | 34 +++++++-------- faoutlier-0.6.1/faoutlier/tests/testthat/test-gCD.R | 6 ++ 22 files changed, 206 insertions(+), 113 deletions(-)