Package: GJRM 0.2-6.5
GJRM: Generalised Joint Regression Modelling
Routines for fitting various joint (and univariate) regression models, with several types of covariate effects, in the presence of equations' errors association, endogeneity, non-random sample selection or partial observability.
Authors:
GJRM_0.2-6.5.tar.gz
GJRM_0.2-6.5.zip(r-4.5)GJRM_0.2-6.5.zip(r-4.4)GJRM_0.2-6.5.zip(r-4.3)
GJRM_0.2-6.5.tgz(r-4.4-any)GJRM_0.2-6.5.tgz(r-4.3-any)
GJRM_0.2-6.5.tar.gz(r-4.5-noble)GJRM_0.2-6.5.tar.gz(r-4.4-noble)
GJRM_0.2-6.5.tgz(r-4.4-emscripten)GJRM_0.2-6.5.tgz(r-4.3-emscripten)
GJRM.pdf |GJRM.html✨
GJRM/json (API)
# Install 'GJRM' in R: |
install.packages('GJRM', repos = c('https://giampmarra.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 8 months agofrom:e6fe1de223. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Aug 23 2024 |
R-4.5-win | OK | Aug 23 2024 |
R-4.5-linux | OK | Aug 23 2024 |
R-4.4-win | OK | Aug 23 2024 |
R-4.4-mac | OK | Aug 23 2024 |
R-4.3-win | OK | Aug 23 2024 |
R-4.3-mac | OK | Aug 23 2024 |
Exports:adjCovadjCovSDapprox.CLMass.dpass.msATBCDFbcontSurvG_extendedbcontSurvGuniv_ExcessHazardbcontSurvGunivI_ExcessHazardbcontSurvGunivInformbcontSurvGunivL_ExcessHazardbcontSurvGunivMIXED_ExcessHazardbcontSurvGunivMIXED_ExcessHazard_LeftTruncationbcontSurvGunivMIXED_LeftTruncationbCopulaCLMgHsContbCopulaCLMgHsOrdbcorrecbcorrecDiscrBiCDFbprobgHsbprobgHsBinROYbprobgHsCont2ROYbprobgHsCont3ROYbprobgHsContUnivbprobgHsDiscr1ROYbprobgHsDiscr2ROYbprobgHsPObprobgHsSSbprobgHstwoParCconv.checkcopgHscopgHs2copgHs3copgHsATcopgHsContcopula.probCopulaCLMcopulaReg.fit.postcopulaSampleSelcopulaSampleSel.fit.postcv.informdistrHsdistrHsATdistrHsAT1distrHsATDiscrdistrHsATDiscr2distrHsDiscrdof.trDpensDpens2edf.loopenu.tresp.treta.trform.checkform.eq12g.trig.triESSg.triSSgamlssgamlss.fit.postggm.Derivggm.DerivOPT1ggm.DerivOPT2ggmtrustggmtrust.pathgjrmgt.bpmH.trihazsurvimputeCounterimputeSSinform.setupint.postcheckintBllpsiLM.bpmlmclogLik.ggmtrustlogLik.lmclogLik.SemiParBIVmbmice.impute.copulaSSmmmmfnumchnumghORoverall.svoverall.svGPDefPEpenplot.SemiParBIVpolys.mappolys.setupPosDefCorpost.checkpostVbpppream.wmpred.gppred.mvtpred.varpredict.CopulaCLMpredict.SemiParBIVprevprint.ATprint.copulaSampleSelprint.gamlssprint.gjrmprint.mbprint.ORprint.PEprint.prevprint.RRprint.SemiParBIVprint.SemiParROYprint.SemiParTRIVprint.summary.copulaSampleSelprint.summary.gamlssprint.summary.gjrmprint.summary.SemiParBIVprint.summary.SemiParROYprint.summary.SemiParTRIVprobmprobmSpscrpscr0pTweedr.respresp.checkresp.CLMrICrMVNrob.constrob.intRRS.mSemiParBIVSemiParBIV.fitSemiParBIV.fit.postSemiParROYSemiParROY.fit.postSemiParTRIVSemiParTRIV.fit.postsim.respSSstartsnsummary.copulaSampleSelsummary.gamlsssummary.gjrmsummary.SemiParBIVsummary.SemiParROYsummary.SemiParTRIVsurvExcIndsusususutsnteta.trtriprobgHsvis.gjrmVuongClarkeworking.compXdpred
Dependencies:abindADGofTestclicolorspacecopulaDBIevdfansifarvergamlss.distggplot2gluegmpGPArotationgslgtableismevisobandlabelinglatticelifecyclemagicmagrittrMASSMatrixmatrixStatsmgcvminqamitoolsmnormtmunsellmvtnormnlmenumDerivpcaPPpillarpkgconfigpsplinepsychR6RColorBrewerRcppRcppArmadillorlangRmpfrscalesscamstabledistsurveysurvivaltibbletrustutf8vctrsVGAMVineCopulaviridisLitewithr