Package: HeckmanEM 0.2-1

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_0.2-1.tar.gz
HeckmanEM_0.2-1.tar.gz(r-4.5-noble)HeckmanEM_0.2-1.tar.gz(r-4.4-noble)
HeckmanEM_0.2-1.tgz(r-4.4-emscripten)HeckmanEM_0.2-1.tgz(r-4.3-emscripten)
HeckmanEM.pdf |HeckmanEM.html✨
HeckmanEM/json (API)

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

Peer review:

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

1.00 score 200 downloads 7 exports 81 dependencies

Last updated 8 months agofrom:8dea03d425. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 04 2024
R-4.5-linuxOKNov 04 2024

Exports:CaseDeletionHeckmanEMHeckmanEM.criteriaHeckmanEM.envelopeHeckmanEM.infomatInfluencerHeckman

Dependencies:abindbackportsBHbootbroomcarcarDataclicolorspacecontfraccowplotcpp11DerivdeSolvedigestdoBydplyrellipticfansifarverFormulagenericsggplot2gluegtablehypergeoisobandlabelinglatticelifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmaxLikmgcvmicrobenchmarkminqamiscToolsmodelrMomTruncmunsellmvtnormnlmenloptrnnetnumDerivpbkrtestPerformanceAnalyticspillarpkgconfigpurrrquadprogquantregR6RColorBrewerRcppRcppArmadilloRcppEigenrlangsampleSelectionsandwichscalesSparseMstringistringrsurvivalsystemfittibbletidyrtidyselecttlrmvnmvtutf8vctrsVGAMviridisLitewithrxtszoo