Package: HeckmanEM 0.2-2

Marcos Prates

HeckmanEM: Fit Normal, Student-t or Contaminated Normal Heckman Selection Models

It performs maximum likelihood estimation for the Heckman selection model (Normal, Student-t or Contaminated normal) using an EM-algorithm <doi:10.1016/j.jmva.2021.104737>. It also performs influence diagnostic through global and local influence for four possible perturbation schema.

Authors:Marcos Prates [aut, cre, trl], Victor Lachos [aut], Dipak Dey [aut], Marcos Oliveira [aut, ctb], Christian Galarza [ctb], Katherine Loor [ctb], Alejandro Ordonez [ctb]

HeckmanEM_0.2-2.tar.gz
HeckmanEM_0.2-2.tar.gz(r-4.7-any)HeckmanEM_0.2-2.tar.gz(r-4.6-any)
HeckmanEM_0.2-2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
HeckmanEM/json (API)

# Install 'HeckmanEM' in R:
install.packages('HeckmanEM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 4 scripts 215 downloads 7 exports 87 dependencies

Last updated from:75854fa9bf. Checks:4 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK187
source / vignettesOK212
linux-release-x86_64OK180
wasm-releaseOK197

Exports:CaseDeletionHeckmanEMHeckmanEM.criteriaHeckmanEM.envelopeHeckmanEM.infomatInfluencerHeckman

Dependencies:abindbackportsBHbootbroomcarcarDataclicolorspacecontfraccowplotcpp11DerivdeSolvedigestdoBydplyrellipticfarverforecastFormulafracdiffgenericsggplot2gluegtablehypergeoisobandlabelinglatticelifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmaxLikmgcvmicrobenchmarkminqamiscToolsmodelrMomTruncmvtnormnlmenloptrnnetnumDerivpbkrtestPerformanceAnalyticspillarpkgconfigpurrrquadprogquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangS7sampleSelectionsandwichscalesSparseMstringistringrsurvivalsystemfittibbletidyrtidyselecttimeDatetlrmvnmvturcautf8vctrsVGAMviridisLitewithrxtszoo