Sat, 15 Jan 2022

Package OpenMx updated to version 2.20.0 with previous version 2.19.8 dated 2021-09-06

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

Diff between OpenMx versions 2.19.8 dated 2021-09-06 and 2.20.0 dated 2022-01-15

 OpenMx-2.19.8/OpenMx/tests/testthat/test-cor.R                                              |only
 OpenMx-2.20.0/OpenMx/DESCRIPTION                                                            |   16 
 OpenMx-2.20.0/OpenMx/MD5                                                                    |  439 ++--
 OpenMx-2.20.0/OpenMx/R/MxAlgebraFunctions.R                                                 |    2 
 OpenMx-2.20.0/OpenMx/R/MxApply.R                                                            |    2 
 OpenMx-2.20.0/OpenMx/R/MxAutoStart.R                                                        |    4 
 OpenMx-2.20.0/OpenMx/R/MxBaseNamed.R                                                        |   20 
 OpenMx-2.20.0/OpenMx/R/MxCompute.R                                                          |  211 +-
 OpenMx-2.20.0/OpenMx/R/MxData.R                                                             |   18 
 OpenMx-2.20.0/OpenMx/R/MxDataWLS.R                                                          |    8 
 OpenMx-2.20.0/OpenMx/R/MxEval.R                                                             |   66 
 OpenMx-2.20.0/OpenMx/R/MxExpectationLISREL.R                                                |    2 
 OpenMx-2.20.0/OpenMx/R/MxExpectationNormal.R                                                |   52 
 OpenMx-2.20.0/OpenMx/R/MxExpectationRAM.R                                                   |    4 
 OpenMx-2.20.0/OpenMx/R/MxExpectationStateSpace.R                                            |    2 
 OpenMx-2.20.0/OpenMx/R/MxFactorScores.R                                                     |    3 
 OpenMx-2.20.0/OpenMx/R/MxFitFunction.R                                                      |   54 
 OpenMx-2.20.0/OpenMx/R/MxFitFunctionAlgebra.R                                               |   30 
 OpenMx-2.20.0/OpenMx/R/MxFitFunctionGREML.R                                                 |   50 
 OpenMx-2.20.0/OpenMx/R/MxFitFunctionML.R                                                    |   33 
 OpenMx-2.20.0/OpenMx/R/MxFitFunctionMultigroup.R                                            |   20 
 OpenMx-2.20.0/OpenMx/R/MxFitFunctionR.R                                                     |   42 
 OpenMx-2.20.0/OpenMx/R/MxFitFunctionRow.R                                                   |  104 -
 OpenMx-2.20.0/OpenMx/R/MxFitFunctionWLS.R                                                   |   16 
 OpenMx-2.20.0/OpenMx/R/MxFlatSearchReplace.R                                                |   21 
 OpenMx-2.20.0/OpenMx/R/MxInterval.R                                                         |    2 
 OpenMx-2.20.0/OpenMx/R/MxModel.R                                                            |   70 
 OpenMx-2.20.0/OpenMx/R/MxModelDisplay.R                                                     |   21 
 OpenMx-2.20.0/OpenMx/R/MxModelFunctions.R                                                   |   10 
 OpenMx-2.20.0/OpenMx/R/MxModelParameters.R                                                  |   14 
 OpenMx-2.20.0/OpenMx/R/MxMultiModel.R                                                       |   27 
 OpenMx-2.20.0/OpenMx/R/MxNamespace.R                                                        |  111 -
 OpenMx-2.20.0/OpenMx/R/MxOptions.R                                                          |    2 
 OpenMx-2.20.0/OpenMx/R/MxPath.R                                                             |    2 
 OpenMx-2.20.0/OpenMx/R/MxPenalty.R                                                          |only
 OpenMx-2.20.0/OpenMx/R/MxRAMModel.R                                                         |   24 
 OpenMx-2.20.0/OpenMx/R/MxRename.R                                                           |    2 
 OpenMx-2.20.0/OpenMx/R/MxRestore.R                                                          |    2 
 OpenMx-2.20.0/OpenMx/R/MxRobustSE.R                                                         |   18 
 OpenMx-2.20.0/OpenMx/R/MxRun.R                                                              |   68 
 OpenMx-2.20.0/OpenMx/R/MxRunHelperFunctions.R                                               |    3 
 OpenMx-2.20.0/OpenMx/R/MxSearchReplace.R                                                    |   26 
 OpenMx-2.20.0/OpenMx/R/MxSummary.R                                                          |   18 
 OpenMx-2.20.0/OpenMx/R/MxThreshold.R                                                        |    2 
 OpenMx-2.20.0/OpenMx/R/MxUnitTesting.R                                                      |    2 
 OpenMx-2.20.0/OpenMx/R/MxVersion.R                                                          |    2 
 OpenMx-2.20.0/OpenMx/README.md                                                              |    2 
 OpenMx-2.20.0/OpenMx/build/OpenMx.pdf                                                       |binary
 OpenMx-2.20.0/OpenMx/build/vignette.rds                                                     |only
 OpenMx-2.20.0/OpenMx/demo/BivariateSaturated.R                                              |    2 
 OpenMx-2.20.0/OpenMx/demo/BivariateSaturated_MatrixRaw.R                                    |    2 
 OpenMx-2.20.0/OpenMx/inst/CITATION                                                          |    4 
 OpenMx-2.20.0/OpenMx/inst/WORDLIST                                                          |    1 
 OpenMx-2.20.0/OpenMx/inst/doc                                                               |only
 OpenMx-2.20.0/OpenMx/inst/models/nightly/CSOLNP_segfault_regression_test--unidentifed_EFA.R |    2 
 OpenMx-2.20.0/OpenMx/inst/models/nightly/LegacyContinuousOnlyWLSTest.R                      |    2 
 OpenMx-2.20.0/OpenMx/inst/models/nightly/MultigroupRobustSE_test.R                          |   36 
 OpenMx-2.20.0/OpenMx/inst/models/nightly/fm-example2-1.R                                    |    8 
 OpenMx-2.20.0/OpenMx/inst/models/nightly/startsTestMissing.R                                |    2 
 OpenMx-2.20.0/OpenMx/inst/models/passing/Acemix2.R                                          |   11 
 OpenMx-2.20.0/OpenMx/inst/models/passing/Autoregressive_PathRaw.R                           |    6 
 OpenMx-2.20.0/OpenMx/inst/models/passing/ContinuousOnlyWLSTest.R                            |    2 
 OpenMx-2.20.0/OpenMx/inst/models/passing/EvaluateOnGrid.R                                   |    2 
 OpenMx-2.20.0/OpenMx/inst/models/passing/IntroSEM-BivariateRaw.R                            |    2 
 OpenMx-2.20.0/OpenMx/inst/models/passing/IntroSEM-BivariateStd.R                            |    2 
 OpenMx-2.20.0/OpenMx/inst/models/passing/IntroSEM-MultivariateRegRaw.R                      |    2 
 OpenMx-2.20.0/OpenMx/inst/models/passing/IntroSEM-OneFactorCov.R                            |    2 
 OpenMx-2.20.0/OpenMx/inst/models/passing/JointFIMLRegressionTest.R                          |    2 
 OpenMx-2.20.0/OpenMx/inst/models/passing/MultipleGroupML.R                                  |    9 
 OpenMx-2.20.0/OpenMx/inst/models/passing/MultipleGroupWLS.R                                 |   26 
 OpenMx-2.20.0/OpenMx/inst/models/passing/NelderMeadTest.R                                   |    2 
 OpenMx-2.20.0/OpenMx/inst/models/passing/RemoveEntriesTest.R                                |    5 
 OpenMx-2.20.0/OpenMx/inst/models/passing/SaturatedWLSTest.R                                 |    4 
 OpenMx-2.20.0/OpenMx/inst/models/passing/WarmStartTest.R                                    |    2 
 OpenMx-2.20.0/OpenMx/inst/models/passing/WeightedWLS.R                                      |    2 
 OpenMx-2.20.0/OpenMx/inst/models/passing/acov_regression_test.R                             |    2 
 OpenMx-2.20.0/OpenMx/inst/models/passing/jointFactorWls.R                                   |   35 
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 OpenMx-2.20.0/OpenMx/inst/models/passing/startingValues2.R                                  |    4 
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 OpenMx-2.20.0/OpenMx/inst/models/passing/univACEP.R                                         |    2 
 OpenMx-2.20.0/OpenMx/inst/tools/updateCopyright.sh                                          |    4 
 OpenMx-2.20.0/OpenMx/man/MxAlgebra-class.Rd                                                 |    2 
 OpenMx-2.20.0/OpenMx/man/MxBounds-class.Rd                                                  |    2 
 OpenMx-2.20.0/OpenMx/man/MxCI-class.Rd                                                      |    2 
 OpenMx-2.20.0/OpenMx/man/MxConstraint-class.Rd                                              |    2 
 OpenMx-2.20.0/OpenMx/man/MxData-class.Rd                                                    |    2 
 OpenMx-2.20.0/OpenMx/man/MxMatrix-class.Rd                                                  |    2 
 OpenMx-2.20.0/OpenMx/man/MxModel-class.Rd                                                   |   13 
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 OpenMx-2.20.0/OpenMx/man/imxIsMultilevel.Rd                                                 |    2 
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 OpenMx-2.20.0/OpenMx/man/imxRobustSE.Rd                                                     |    7 
 OpenMx-2.20.0/OpenMx/man/imxRowGradients.Rd                                                 |    6 
 OpenMx-2.20.0/OpenMx/man/mxAlgebra.Rd                                                       |    2 
 OpenMx-2.20.0/OpenMx/man/mxAlgebraObjective.Rd                                              |    2 
 OpenMx-2.20.0/OpenMx/man/mxBootstrapEval.Rd                                                 |    2 
 OpenMx-2.20.0/OpenMx/man/mxBounds.Rd                                                        |    2 
 OpenMx-2.20.0/OpenMx/man/mxCI.Rd                                                            |    2 
 OpenMx-2.20.0/OpenMx/man/mxCompare.Rd                                                       |    2 
 OpenMx-2.20.0/OpenMx/man/mxComputeConfidenceInterval.Rd                                     |    4 
 OpenMx-2.20.0/OpenMx/man/mxComputeNewtonRaphson.Rd                                          |    2 
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 OpenMx-2.20.0/OpenMx/man/mxConstraint.Rd                                                    |    2 
 OpenMx-2.20.0/OpenMx/man/mxData.Rd                                                          |   20 
 OpenMx-2.20.0/OpenMx/man/mxDataWLS.Rd                                                       |    2 
 OpenMx-2.20.0/OpenMx/man/mxEval.Rd                                                          |    2 
 OpenMx-2.20.0/OpenMx/man/mxExpectationLISREL.Rd                                             |    2 
 OpenMx-2.20.0/OpenMx/man/mxExpectationNormal.Rd                                             |    2 
 OpenMx-2.20.0/OpenMx/man/mxExpectationRAM.Rd                                                |    2 
 OpenMx-2.20.0/OpenMx/man/mxExpectationStateSpace.Rd                                         |    2 
 OpenMx-2.20.0/OpenMx/man/mxExpectationStateSpaceContinuousTime.Rd                           |    2 
 OpenMx-2.20.0/OpenMx/man/mxFIMLObjective.Rd                                                 |    2 
 OpenMx-2.20.0/OpenMx/man/mxFactor.Rd                                                        |    2 
 OpenMx-2.20.0/OpenMx/man/mxFactorScores.Rd                                                  |    2 
 OpenMx-2.20.0/OpenMx/man/mxFitFunctionAlgebra.Rd                                            |    2 
 OpenMx-2.20.0/OpenMx/man/mxFitFunctionML.Rd                                                 |    2 
 OpenMx-2.20.0/OpenMx/man/mxFitFunctionR.Rd                                                  |    2 
 OpenMx-2.20.0/OpenMx/man/mxFitFunctionRow.Rd                                                |    2 
 OpenMx-2.20.0/OpenMx/man/mxFitFunctionWLS.Rd                                                |    2 
 OpenMx-2.20.0/OpenMx/man/mxGenerateData.Rd                                                  |    2 
 OpenMx-2.20.0/OpenMx/man/mxGetExpected.Rd                                                   |    2 
 OpenMx-2.20.0/OpenMx/man/mxKalmanScores.Rd                                                  |    2 
 OpenMx-2.20.0/OpenMx/man/mxLISRELObjective.Rd                                               |    2 
 OpenMx-2.20.0/OpenMx/man/mxMI.Rd                                                            |    2 
 OpenMx-2.20.0/OpenMx/man/mxMLObjective.Rd                                                   |    2 
 OpenMx-2.20.0/OpenMx/man/mxMatrix.Rd                                                        |    2 
 OpenMx-2.20.0/OpenMx/man/mxModel.Rd                                                         |    2 
 OpenMx-2.20.0/OpenMx/man/mxOption.Rd                                                        |    2 
 OpenMx-2.20.0/OpenMx/man/mxPath.Rd                                                          |    2 
 OpenMx-2.20.0/OpenMx/man/mxPenalty.Rd                                                       |only
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 OpenMx-2.20.0/OpenMx/man/mxRAMObjective.Rd                                                  |    2 
 OpenMx-2.20.0/OpenMx/man/mxRObjective.Rd                                                    |    2 
 OpenMx-2.20.0/OpenMx/man/mxRename.Rd                                                        |    2 
 OpenMx-2.20.0/OpenMx/man/mxRowObjective.Rd                                                  |    2 
 OpenMx-2.20.0/OpenMx/man/mxThreshold.Rd                                                     |    2 
 OpenMx-2.20.0/OpenMx/man/mxVersion.Rd                                                       |    2 
 OpenMx-2.20.0/OpenMx/man/omxBrownie.Rd                                                      |    2 
 OpenMx-2.20.0/OpenMx/man/omxCheckEquals.Rd                                                  |    2 
 OpenMx-2.20.0/OpenMx/man/omxCheckIdentical.Rd                                               |    2 
 OpenMx-2.20.0/OpenMx/man/omxCheckSetEquals.Rd                                               |    2 
 OpenMx-2.20.0/OpenMx/man/omxCheckTrue.Rd                                                    |    2 
 OpenMx-2.20.0/OpenMx/man/omxCheckWithinPercentError.Rd                                      |    2 
 OpenMx-2.20.0/OpenMx/man/omxDefaultComputePlan.Rd                                           |    6 
 OpenMx-2.20.0/OpenMx/man/omxGraphviz.Rd                                                     |    2 
 OpenMx-2.20.0/OpenMx/man/omxLocateParameters.Rd                                             |    2 
 OpenMx-2.20.0/OpenMx/man/omxSaturatedModel.Rd                                               |    2 
 OpenMx-2.20.0/OpenMx/man/omxSelectRowsAndCols.Rd                                            |    2 
 OpenMx-2.20.0/OpenMx/man/summary.MxModel.Rd                                                 |    2 
 OpenMx-2.20.0/OpenMx/src/AlgebraFunctions.h                                                 |    2 
 OpenMx-2.20.0/OpenMx/src/Compute.cpp                                                        |  268 ++
 OpenMx-2.20.0/OpenMx/src/Compute.h                                                          |   11 
 OpenMx-2.20.0/OpenMx/src/ComputeGD.cpp                                                      |  117 -
 OpenMx-2.20.0/OpenMx/src/ComputeGD.h                                                        |    4 
 OpenMx-2.20.0/OpenMx/src/ComputeNM.cpp                                                      |    6 
 OpenMx-2.20.0/OpenMx/src/ComputeNR.cpp                                                      |  117 -
 OpenMx-2.20.0/OpenMx/src/Connectedness.h                                                    |    2 
 OpenMx-2.20.0/OpenMx/src/FellnerFitFunction.cpp                                             |    4 
 OpenMx-2.20.0/OpenMx/src/MarkovExpectation.cpp                                              |    2 
 OpenMx-2.20.0/OpenMx/src/MarkovFF.cpp                                                       |    8 
 OpenMx-2.20.0/OpenMx/src/RAMInternal.h                                                      |    7 
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 OpenMx-2.20.0/OpenMx/src/Tridiagonalization34.h                                             |only
 OpenMx-2.20.0/OpenMx/src/fitMultigroup.cpp                                                  |   46 
 OpenMx-2.20.0/OpenMx/src/glue.cpp                                                           |   21 
 OpenMx-2.20.0/OpenMx/src/glue.h                                                             |    2 
 OpenMx-2.20.0/OpenMx/src/nr.h                                                               |   12 
 OpenMx-2.20.0/OpenMx/src/omxAlgebra.cpp                                                     |    2 
 OpenMx-2.20.0/OpenMx/src/omxAlgebra.h                                                       |    2 
 OpenMx-2.20.0/OpenMx/src/omxAlgebraFitFunction.cpp                                          |    6 
 OpenMx-2.20.0/OpenMx/src/omxCsolnp.h                                                        |    2 
 OpenMx-2.20.0/OpenMx/src/omxData.cpp                                                        |  100 -
 OpenMx-2.20.0/OpenMx/src/omxData.h                                                          |    9 
 OpenMx-2.20.0/OpenMx/src/omxDefines.h                                                       |    3 
 OpenMx-2.20.0/OpenMx/src/omxExpectation.cpp                                                 |   40 
 OpenMx-2.20.0/OpenMx/src/omxExpectation.h                                                   |   17 
 OpenMx-2.20.0/OpenMx/src/omxExportBackendState.cpp                                          |   11 
 OpenMx-2.20.0/OpenMx/src/omxFIMLFitFunction.cpp                                             |    4 
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 OpenMx-2.20.0/OpenMx/src/omxFitFunction.cpp                                                 |  159 -
 OpenMx-2.20.0/OpenMx/src/omxFitFunction.h                                                   |   24 
 OpenMx-2.20.0/OpenMx/src/omxFitFunctionBA81.cpp                                             |    4 
 OpenMx-2.20.0/OpenMx/src/omxGREMLExpectation.cpp                                            |   22 
 OpenMx-2.20.0/OpenMx/src/omxGREMLExpectation.h                                              |   30 
 OpenMx-2.20.0/OpenMx/src/omxGREMLfitfunction.cpp                                            |  920 ++++------
 OpenMx-2.20.0/OpenMx/src/omxHessianCalculation.cpp                                          |  156 -
 OpenMx-2.20.0/OpenMx/src/omxImportFrontendState.cpp                                         |   21 
 OpenMx-2.20.0/OpenMx/src/omxLISRELExpectation.cpp                                           |   14 
 OpenMx-2.20.0/OpenMx/src/omxLISRELExpectation.h                                             |    2 
 OpenMx-2.20.0/OpenMx/src/omxMLFitFunction.cpp                                               |    6 
 OpenMx-2.20.0/OpenMx/src/omxMatrix.cpp                                                      |    6 
 OpenMx-2.20.0/OpenMx/src/omxMatrix.h                                                        |   12 
 OpenMx-2.20.0/OpenMx/src/omxNPSOLSpecific.h                                                 |    2 
 OpenMx-2.20.0/OpenMx/src/omxNormalExpectation.cpp                                           |   66 
 OpenMx-2.20.0/OpenMx/src/omxRAMExpectation.cpp                                              |   30 
 OpenMx-2.20.0/OpenMx/src/omxRFitFunction.cpp                                                |    4 
 OpenMx-2.20.0/OpenMx/src/omxRFitFunction.h                                                  |    4 
 OpenMx-2.20.0/OpenMx/src/omxRowFitFunction.cpp                                              |    6 
 OpenMx-2.20.0/OpenMx/src/omxRowFitFunction.h                                                |    2 
 OpenMx-2.20.0/OpenMx/src/omxSadmvnWrapper.h                                                 |    2 
 OpenMx-2.20.0/OpenMx/src/omxState.cpp                                                       |    6 
 OpenMx-2.20.0/OpenMx/src/omxState.h                                                         |   11 
 OpenMx-2.20.0/OpenMx/src/omxStateSpaceExpectation.cpp                                       |    2 
 OpenMx-2.20.0/OpenMx/src/omxWLSFitFunction.cpp                                              |   15 
 OpenMx-2.20.0/OpenMx/src/penalty.cpp                                                        |only
 OpenMx-2.20.0/OpenMx/src/penalty.h                                                          |only
 OpenMx-2.20.0/OpenMx/src/ssMLFit.cpp                                                        |    6 
 OpenMx-2.20.0/OpenMx/tests/testthat/test-ACELRTCI20160808.R                                 |    4 
 OpenMx-2.20.0/OpenMx/tests/testthat/test-AlgebraComputePassing.R                            |    2 
 OpenMx-2.20.0/OpenMx/tests/testthat/test-LegacyMultipleGroupWLS.R                           |    2 
 OpenMx-2.20.0/OpenMx/tests/testthat/test-ModelIdentification.R                              |    2 
 OpenMx-2.20.0/OpenMx/tests/testthat/test-loadDataByRow.R                                    |   10 
 OpenMx-2.20.0/OpenMx/tests/testthat/test-mxsave.R                                           |    2 
 OpenMx-2.20.0/OpenMx/tools/wls-regression                                                   |   25 
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 222 files changed, 2682 insertions(+), 1878 deletions(-)

More information about OpenMx at CRAN
Permanent link

Package MSGARCH updated to version 2.50 with previous version 2.42 dated 2020-04-20

Title: Markov-Switching GARCH Models
Description: Fit (by Maximum Likelihood or MCMC/Bayesian), simulate, and forecast various Markov-Switching GARCH models as described in Ardia et al. (2019) <doi:10.18637/jss.v091.i04>.
Author: David Ardia [aut] (<https://orcid.org/0000-0003-2823-782X>), Keven Bluteau [aut, cre] (<https://orcid.org/0000-0003-2990-4807>), Kris Boudt [ctb] (<https://orcid.org/0000-0002-1000-5142>), Leopoldo Catania [aut] (<https://orcid.org/0000-0002-0981-1921>), Alexios Ghalanos [ctb], Brian Peterson [ctb], Denis-Alexandre Trottier [aut]
Maintainer: Keven Bluteau <Keven.Bluteau@usherbrooke.ca>

Diff between MSGARCH versions 2.42 dated 2020-04-20 and 2.50 dated 2022-01-15

 DESCRIPTION            |   15 ++++++++-------
 MD5                    |   37 +++++++++++++++++++------------------
 NEWS                   |    2 ++
 R/CreateSpec.R         |   14 +++++++-------
 R/DIC.R                |    2 +-
 R/FitMCMC.R            |    6 +++---
 R/FitML.R              |    2 +-
 R/MSGARCH.R            |   20 ++++++++++----------
 R/Transmat.R           |    1 +
 R/predict.R            |    1 -
 build                  |only
 man/CreateSpec.Rd      |   14 +++++++-------
 man/DIC.Rd             |    2 +-
 man/FitMCMC.Rd         |    6 +++---
 man/FitML.Rd           |    2 +-
 man/MSGARCH-package.Rd |   16 ++++++++--------
 man/SMI.Rd             |    2 +-
 man/dem2gbp.Rd         |    4 ++--
 src/RcppExports.cpp    |    5 +++++
 src/pdf_c.cpp          |    6 +++---
 20 files changed, 83 insertions(+), 74 deletions(-)

More information about MSGARCH at CRAN
Permanent link

Package impactr updated to version 0.4.0 with previous version 0.3.0 dated 2021-11-18

Title: Mechanical Loading Prediction Through Accelerometer Data
Description: Functions to read, process and analyse accelerometer data related to mechanical loading variables. This package is developed and tested for use with raw accelerometer data from triaxial 'ActiGraph' <https://actigraphcorp.com> accelerometers.
Author: Lucas Veras [aut, cre] (<https://orcid.org/0000-0003-0562-5803>)
Maintainer: Lucas Veras <lucasdsveras@gmail.com>

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Package eat updated to version 0.1.2 with previous version 0.1.1 dated 2022-01-14

Title: Efficiency Analysis Trees
Description: Functions are provided to determine production frontiers and technical efficiency measures through non-parametric techniques based upon regression trees. The package includes code for estimating radial input, output, directional and additive measures, plotting graphical representations of the scores and the production frontiers by means of trees, and determining rankings of importance of input variables in the analysis. Additionally, an adaptation of Random Forest by a set of individual Efficiency Analysis Trees for estimating technical efficiency is also included. More details in: <doi:10.1016/j.eswa.2020.113783>.
Author: Miriam Esteve [cre, aut] (<https://orcid.org/0000-0002-5908-0581>), Víctor España [aut] (<https://orcid.org/0000-0002-1807-6180>), Juan Aparicio [aut] (<https://orcid.org/0000-0002-0867-0004>), Xavier Barber [aut] (<https://orcid.org/0000-0003-3079-5855>)
Maintainer: Miriam Esteve <mestevecampello@gmail.com>

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Package DCEM updated to version 2.0.5 with previous version 2.0.4 dated 2020-08-02

Title: Clustering Big Data using Expectation Maximization Star (EM*) Algorithm
Description: Implements the Improved Expectation Maximisation EM* and the traditional EM algorithm for clustering big data (gaussian mixture models for both multivariate and univariate datasets). This version implements the faster alternative-EM* that expedites convergence via structure based data segregation. The implementation supports both random and K-means++ based initialization. Reference: Parichit Sharma, Hasan Kurban, Mehmet Dalkilic (2022) <doi:10.1016/j.softx.2021.100944>. Hasan Kurban, Mark Jenne, Mehmet Dalkilic (2016) <doi:10.1007/s41060-017-0062-1>.
Author: Sharma Parichit [aut, cre, ctb], Kurban Hasan [aut, ctb], Dalkilic Mehmet [aut]
Maintainer: Sharma Parichit <parishar@iu.edu>

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Package DiagrammeR updated to version 1.0.7 with previous version 1.0.6.1 dated 2020-05-08

Title: Graph/Network Visualization
Description: Build graph/network structures using functions for stepwise addition and deletion of nodes and edges. Work with data available in tables for bulk addition of nodes, edges, and associated metadata. Use graph selections and traversals to apply changes to specific nodes or edges. A wide selection of graph algorithms allow for the analysis of graphs. Visualize the graphs and take advantage of any aesthetic properties assigned to nodes and edges.
Author: Richard Iannone [aut, cre] (<https://orcid.org/0000-0003-3925-190X>)
Maintainer: Richard Iannone <riannone@me.com>

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Package spiralize updated to version 1.0.4 with previous version 1.0.3 dated 2021-10-12

Title: Visualize Data on Spirals
Description: It visualizes data along an Archimedean spiral <https://en.wikipedia.org/wiki/Archimedean_spiral>, makes so-called spiral graph or spiral chart. It has two major advantages for visualization: 1. It is able to visualize data with very long axis with high resolution. 2. It is efficient for time series data to reveal periodic patterns.
Author: Zuguang Gu [aut, cre] (<https://orcid.org/0000-0002-7395-8709>)
Maintainer: Zuguang Gu <z.gu@dkfz.de>

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Package sbfc updated to version 1.0.3 with previous version 1.0.2 dated 2020-06-23

Title: Selective Bayesian Forest Classifier
Description: An MCMC algorithm for simultaneous feature selection and classification, and visualization of the selected features and feature interactions. An implementation of SBFC by Krakovna, Du and Liu (2015), <arXiv:1506.02371>.
Author: Viktoriya Krakovna
Maintainer: Viktoriya Krakovna <vkrakovna@gmail.com>

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Package entcn updated to version 1.0.0 with previous version 0.1.0 dated 2020-02-21

Title: Translate English Words into Chinese Words
Description: If translate English words into Chinese, you might consider looking up a dictionary or online query, in fact, there is a faster way for R user. Ke-Hao Wu (2014) <RYoudaoTranslate: R package provide functions to translate English words into Chinese.> provides interface to Youdao translation open API for R user. But this software is not very friendly to use, I have made some improvements on the basis of this software. You can pass in a words or a vector consisting of multiple words, which will return the corresponding type of Chinese representation and be easy to reuse.
Author: Xinyuan Chu [aut, cre]
Maintainer: Xinyuan Chu <chuxinyuan@outlook.com>

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Package dbscan updated to version 1.1-10 with previous version 1.1-9 dated 2022-01-10

Title: Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Related Algorithms
Description: A fast reimplementation of several density-based algorithms of the DBSCAN family. Includes the clustering algorithms DBSCAN (density-based spatial clustering of applications with noise) and HDBSCAN (hierarchical DBSCAN), the ordering algorithm OPTICS (ordering points to identify the clustering structure), shared nearest neighbor clustering, and the outlier detection algorithms LOF (local outlier factor) and GLOSH (global-local outlier score from hierarchies). The implementations use the kd-tree data structure (from library ANN) for faster k-nearest neighbor search. An R interface to fast kNN and fixed-radius NN search is also provided. Hahsler, Piekenbrock and Doran (2019) <doi:10.18637/jss.v091.i01>.
Author: Michael Hahsler [aut, cre, cph], Matthew Piekenbrock [aut, cph], Sunil Arya [ctb, cph], David Mount [ctb, cph]
Maintainer: Michael Hahsler <mhahsler@lyle.smu.edu>

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Package spatPomp updated to version 0.29.0.0 with previous version 0.28.0.0 dated 2021-09-04

Title: Inference for Spatiotemporal Partially Observed Markov Processes
Description: Inference on panel data using spatiotemporal partially-observed Markov process (SpatPOMP) models. To do so, it relies on and extends a number of facilities that the 'pomp' package provides for inference on time series data using partially-observed Markov process (POMP) models. Implemented methods include filtering and inference methods in Park and Ionides (2020) <doi:10.1007/s11222-020-09957-3>, Rebeschini and van Handel (2015) <doi:10.1214/14-AAP1061>, Evensen and van Leeuwen (1996) <doi:10.1029/94JC00572> and Ionides et al. (2021) <arXiv:2002.05211v2>. Pre-print statistical software article: Asfaw et al. (2021) <arXiv:2101.01157>.
Author: Kidus Asfaw [aut, cre], Aaron A. King [aut], Edward Ionides [aut], Joonha Park [ctb], Allister Ho [ctb]
Maintainer: Kidus Asfaw <kasfaw@umich.edu>

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Package spatialprobit updated to version 1.0 with previous version 0.9-11 dated 2015-09-17

Title: Spatial Probit Models
Description: Bayesian Estimation of Spatial Probit and Tobit Models.
Author: Stefan Wilhelm <wilhelm@financial.com> and Miguel Godinho de Matos <miguelgodinhomatos@cmu.edu>
Maintainer: Stefan Wilhelm <wilhelm@financial.com>

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Package ggPMX updated to version 1.2.5 with previous version 1.2.4 dated 2021-09-20

Title: 'ggplot2' Based Tool to Facilitate Diagnostic Plots for NLME Models
Description: At Novartis, we aimed at standardizing the set of diagnostic plots used for modeling activities in order to reduce the overall effort required for generating such plots. For this, we developed a guidance that proposes an adequate set of diagnostics and a toolbox, called 'ggPMX' to execute them. 'ggPMX' is a toolbox that can generate all diagnostic plots at a quality sufficient for publication and submissions using few lines of code. This package focuses on plots recommended by ISoP <doi:10.1002/psp4.12161>.
Author: Amine Gassem [aut], Bruno Bieth [aut], Irina Baltcheva [aut], Thomas Dumortier [aut], Christian Bartels [aut], Souvik Bhattacharya [aut], Inga Ludwig [aut], Ines Paule [aut], Didier Renard [aut], Matthew Fidler [aut, cre] (<https://orcid.org/0000-0001-8538-6691>), Seid Hamzic [aut], Benjamin Guiastrennec [ctb], Kyle T Baron [ctb] (<https://orcid.org/0000-0001-7252-5656>), Qing Xi Ooi [ctb], Novartis Pharma AG [cph]
Maintainer: Matthew Fidler <matthew.fidler@gmail.com>

Diff between ggPMX versions 1.2.4 dated 2021-09-20 and 1.2.5 dated 2022-01-15

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 R/pmx-reader.R                                       |    2 
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Package dataprep updated to version 0.1.5 with previous version 0.1.4 dated 2021-07-04

Title: Efficient and Flexible Data Preprocessing Tools
Description: Efficiently and flexibly preprocess data using a set of data filtering, deletion, and interpolation tools. These data preprocessing methods are developed based on the principles of completeness, accuracy, threshold method, and linear interpolation and through the setting of constraint conditions, time completion & recovery, and fast & efficient calculation and grouping. Key preprocessing steps include deletions of variables and observations, outlier removal, and missing values (NA) interpolation, which are dependent on the incomplete and dispersed degrees of raw data. They clean data more accurately, keep more samples, and add no outliers after interpolation, compared with ordinary methods. Auto-identification of consecutive NA via run-length based grouping is used in observation deletion, outlier removal, and NA interpolation; thus, new outliers are not generated in interpolation. Conditional extremum is proposed to realize point-by-point weighed outlier removal that saves non-outliers from being removed. Plus, time series interpolation with values to refer to within short periods further ensures reliable interpolation. These methods are based on and improved from the reference: Liang, C.-S., Wu, H., Li, H.-Y., Zhang, Q., Li, Z. & He, K.-B. (2020) <doi:10.1016/j.scitotenv.2020.140923>.
Author: Chun-Sheng Liang <liangchunsheng@lzu.edu.cn>, Hao Wu, Hai-Yan Li, Qiang Zhang, Zhanqing Li, Ke-Bin He, Lanzhou University, Tsinghua University
Maintainer: Chun-Sheng Liang <liangchunsheng@lzu.edu.cn>

Diff between dataprep versions 0.1.4 dated 2021-07-04 and 0.1.5 dated 2022-01-15

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 6 files changed, 33 insertions(+), 32 deletions(-)

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Package rdomains updated to version 0.2.1 with previous version 0.2.0 dated 2021-11-04

Title: Get the Category of Content Hosted by a Domain
Description: Get the category of content hosted by a domain. Use Shallalist <http://shalla.de/>, Virustotal (which provides access to lots of services) <https://www.virustotal.com/>, Alexa <https://aws.amazon.com/awis/>, DMOZ <https://curlie.org/>, University Domain list <https://github.com/Hipo/university-domains-list> or validated machine learning classifiers based on Shallalist data to learn about the kind of content hosted by a domain.
Author: Gaurav Sood [aut, cre]
Maintainer: Gaurav Sood <gsood07@gmail.com>

Diff between rdomains versions 0.2.0 dated 2021-11-04 and 0.2.1 dated 2022-01-15

 DESCRIPTION            |    8 ++++----
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 R/rdomains.R           |    1 +
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 inst/doc/rdomains.html |    4 ++--
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 12 files changed, 34 insertions(+), 49 deletions(-)

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Package gpboost updated to version 0.7.1 with previous version 0.7.0 dated 2021-12-09

Title: Combining Tree-Boosting with Gaussian Process and Mixed Effects Models
Description: An R package that allows for combining tree-boosting with Gaussian process and mixed effects models. It also allows for independently doing tree-boosting as well as inference and prediction for Gaussian process and mixed effects models. See <https://github.com/fabsig/GPBoost> for more information on the software and Sigrist (2020) <arXiv:2004.02653> and Sigrist (2021) <arXiv:2105.08966> for more information on the methodology.
Author: Fabio Sigrist [aut, cre], Benoit Jacob [cph], Gael Guennebaud [cph], Nicolas Carre [cph], Pierre Zoppitelli [cph], Gauthier Brun [cph], Jean Ceccato [cph], Jitse Niesen [cph], Other authors of Eigen for the included version of Eigen [ctb, cph], Timothy A. Davis [cph], Guolin Ke [ctb], Damien Soukhavong [ctb], James Lamb [ctb], Other authors of LightGBM for the included version of LightGBM [ctb], Microsoft Corporation [cph], Dropbox, Inc. [cph], Jay Loden [cph], Dave Daeschler [cph], Giampaolo Rodola [cph], Alberto Ferreira [ctb], Daniel Lemire [ctb], Victor Zverovich [cph], IBM Corporation [ctb], Keith O'Hara [cph], Stephen L. Moshier [cph]
Maintainer: Fabio Sigrist <fabiosigrist@gmail.com>

Diff between gpboost versions 0.7.0 dated 2021-12-09 and 0.7.1 dated 2022-01-15

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 demo/generalized_linear_Gaussian_process_mixed_effects_models.R |    4 
 man/GPModel.Rd                                                  |   32 
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 man/fit.GPModel.Rd                                              |   20 
 man/fit.Rd                                                      |   20 
 man/fitGPModel.Rd                                               |   52 
 man/predict.GPModel.Rd                                          |   25 
 man/predict.gpb.Booster.Rd                                      |   22 
 man/set_prediction_data.GPModel.Rd                              |   19 
 man/set_prediction_data.Rd                                      |   19 
 src/gpboost_R.h                                                 |    2 
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 src/include/GPBoost/re_comp.h                                   |  254 +-
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 src/include/LightGBM/c_api.h                                    |    2 
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 src/include/unconstrained/nm.hpp                                |   14 
 src/network/socket_wrapper.hpp                                  |    4 
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 tests/testthat/test_GPBoost_algorithm_non_Gaussian_data.R       |   29 
 tests/testthat/test_GPModel_gaussian_process.R                  |   16 
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 tests/testthat/test_GPModel_non_Gaussian_data.R                 |   41 
 31 files changed, 1442 insertions(+), 793 deletions(-)

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Package UCSCXenaShiny updated to version 1.1.5 with previous version 1.1.4 dated 2021-12-13

Title: Interactive Analysis of UCSC Xena Data
Description: Provides functions and a Shiny application for downloading, analyzing and visualizing datasets from UCSC Xena (<http://xena.ucsc.edu/>), which is a collection of UCSC-hosted public databases such as TCGA, ICGC, TARGET, GTEx, CCLE, and others.
Author: Shixiang Wang [aut, cre] (<https://orcid.org/0000-0001-9855-7357>), Yi Xiong [aut] (<https://orcid.org/0000-0002-4370-9824>), Longfei Zhao [aut] (<https://orcid.org/0000-0002-6277-0137>), Kai Gu [aut] (<https://orcid.org/0000-0002-0177-0774>), Yin Li [aut], Fei Zhao [aut]
Maintainer: Shixiang Wang <w_shixiang@163.com>

Diff between UCSCXenaShiny versions 1.1.4 dated 2021-12-13 and 1.1.5 dated 2022-01-15

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 7 files changed, 30 insertions(+), 15 deletions(-)

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New package rccola with initial version 1.0
Package: rccola
Title: Safely Manage API Keys and Load Data from a REDCap or Other Source
Version: 1.0
Author: Shawn Garbett [aut, cre], Hui Wu [aut], Cole Beck [aut]
Maintainer: Shawn Garbett <Shawn.Garbett@vumc.org>
Description: The handling of an API key (misnomer for password) for protected data can be difficult. This package provides secure convenience functions for entering / handling API keys and pulling data directly into memory. By default it will load from REDCap instances, but other sources are injectable via inversion of control.
License: GPL-3
Encoding: UTF-8
Imports: redcapAPI, getPass, yaml, keyring
URL: https://github.com/spgarbet/rccola
NeedsCompilation: no
Packaged: 2022-01-13 16:43:37 UTC; garbetsp
Repository: CRAN
Date/Publication: 2022-01-15 09:02:41 UTC

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New package phecodemap with initial version 0.1.0
Package: phecodemap
Title: Visualization for PheCode Mapping with ICD-9 and ICD-10-CM Codes
Version: 0.1.0
Description: To build a shiny app for visualization of the hierarchy of PheCode Mapping with International Classification of Diseases (ICD). The same PheCode hierarchy is displayed in two ways: as a sunburst plot and as a tree.
License: GPL (>= 3)
Imports: collapsibleTree, config (>= 0.3.1), dplyr, DT, golem (>= 0.3.1), plotly, purrr, readr, rintrojs, shinycssloaders, shinydashboard, shinydashboardPlus
Depends: R (>= 3.5.0), shiny (>= 1.6.0), shinyBS
Encoding: UTF-8
LazyData: true
URL: https://github.com/celehs/phecodemap
BugReports: https://github.com/celehs/phecodemap/issues
Suggests: rmarkdown, knitr, shinytest, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2022-01-13 09:43:05 UTC; hui
Author: PARSE LTD [cre, aut]
Maintainer: PARSE LTD <software@parse-health.org>
Repository: CRAN
Date/Publication: 2022-01-15 09:02:44 UTC

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New package dTBM with initial version 1.0
Package: dTBM
Title: Multi-Way Spherical Clustering via Degree-Corrected Tensor Block Models
Version: 1.0
Date: 2022-01-10
Maintainer: Jiaxin Hu <jhu267@wisc.edu>
Description: Implement weighted higher-order initialization and angle-based iteration for multi-way spherical clustering under degree-corrected tensor block model.
Imports: tensorregress, WeightedCluster, EnvStats
License: GPL (>= 2)
Encoding: UTF-8
Author: Jiaxin Hu [aut, cre, cph], Miaoyan Wang [aut, cph]
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2022-01-13 23:32:35 UTC; michael
Repository: CRAN
Date/Publication: 2022-01-15 09:02:47 UTC

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New package bulkAnalyseR with initial version 0.1.1
Package: bulkAnalyseR
Title: Interactive Shiny App for Bulk Sequencing Data
Version: 0.1.1
Maintainer: Ilias Moutsopoulos <im383@cam.ac.uk>
Description: Given an expression matrix from a bulk RNA-Seq experiment, pre-processes it and creates a shiny app for interactive data analysis and visualisation. The app contains quality checks, differential expression analysis, volcano and cross plots, enrichment analysis and gene regulatory network inference, and can be customised to contain more panels by the user.
License: GPL-2
Encoding: UTF-8
URL: https://github.com/Core-Bioinformatics/bulkAnalyseR
BugReports: https://github.com/Core-Bioinformatics/bulkAnalyseR/issues
Depends: R (>= 4.0)
Imports: ggplot2, shinythemes, shiny, gprofiler2, edgeR, DESeq2, stats, ggrepel, utils, RColorBrewer, ComplexHeatmap, circlize, grid, shinyWidgets, shinyjqui, dplyr, magrittr, ggforce, rlang, glue, preprocessCore, matrixStats, noisyr, tibble, ggnewscale, ggrastr, GENIE3, visNetwork, DT, scales, shinyjs, tidyr
Suggests: rmarkdown, knitr, BiocManager, AnnotationDbi, org.Hs.eg.db, org.Mm.eg.db
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2022-01-13 20:05:51 UTC; emouts
Author: Ilias Moutsopoulos [aut, cre], Eleanor Williams [aut, ctb], Irina Mohorianu [aut, ctb]
Repository: CRAN
Date/Publication: 2022-01-15 09:02:49 UTC

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New package njgeo with initial version 0.1.0
Package: njgeo
Title: Tools for Geocoding Addresses in New Jersey using the 'NJOGIS' API
Version: 0.1.0
Description: Provides an R interface to free geocoding REST APIs maintained by the New Jersey Office of GIS <https://njgin.nj.gov/njgin/edata/geocoding/index.html#!/> and commonly used shapefiles.
License: GPL (>= 3)
Encoding: UTF-8
Imports: sf, jsonlite, httr, curl, dplyr
Suggests: knitr, rmarkdown, markdown
NeedsCompilation: no
Packaged: 2022-01-13 15:20:49 UTC; gavinrozzi
Author: Gavin Rozzi [aut, cre] (<https://orcid.org/0000-0002-9969-8175>)
Maintainer: Gavin Rozzi <gr@gavinrozzi.com>
Repository: CRAN
Date/Publication: 2022-01-15 08:52:42 UTC

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New package lglasso with initial version 0.1.0
Package: lglasso
Title: Longitudinal Graphical Lasso
Version: 0.1.0
Description: For high-dimensional correlated observations, this package carries out the L_1 penalized maximum likelihood estimation of the precision matrix (network) and the correlation parameters. The correlated data can be longitudinal data (may be irregularly spaced) with dampening correlation or clustered data with uniform correlation. For the details of the algorithms, please see the paper Jie Zhou et al. Identifying Microbial Interaction Networks Based on Irregularly Spaced Longitudinal 16S rRNA sequence data <doi:10.1101/2021.11.26.470159>.
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/jiezhou-2/lglasso
Suggests: knitr, rmarkdown
Imports: stats, glasso
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2022-01-13 16:54:06 UTC; jie
Author: Jie Zhou [aut, cre, cph], Jiang Gui [aut], Weston Viles [aut], Anne Hoen [aut]
Maintainer: Jie Zhou <chowstat@gmail.com>
Repository: CRAN
Date/Publication: 2022-01-15 08:52:46 UTC

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Package TiPS (with last version 1.1.0) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2021-11-12 1.1.0
2021-09-13 1.0

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