Package: EMSS 1.1.1

Sang Kyu Lee

EMSS: Some EM-Type Estimation Methods for the Heckman Selection Model

Some EM-type algorithms to estimate parameters for the well-known Heckman selection model are provided in the package. Such algorithms are as follow: ECM(Expectation/Conditional Maximization), ECM(NR)(the Newton-Raphson method is adapted to the ECM) and ECME(Expectation/Conditional Maximization Either). Since the algorithms are based on the EM algorithm, they also have EM’s main advantages, namely, stability and ease of implementation. Further details and explanations of the algorithms can be found in Zhao et al. (2020) <doi:10.1016/j.csda.2020.106930>.

Authors:Kexuan Yang <[email protected]>, Sang Kyu Lee <[email protected]>, Jun Zhao <[email protected]>, and Hyoung-Moon Kim <[email protected] >

EMSS_1.1.1.tar.gz
EMSS_1.1.1.zip(r-4.5)EMSS_1.1.1.zip(r-4.4)EMSS_1.1.1.zip(r-4.3)
EMSS_1.1.1.tgz(r-4.4-any)EMSS_1.1.1.tgz(r-4.3-any)
EMSS_1.1.1.tar.gz(r-4.5-noble)EMSS_1.1.1.tar.gz(r-4.4-noble)
EMSS_1.1.1.tgz(r-4.4-emscripten)EMSS_1.1.1.tgz(r-4.3-emscripten)
EMSS.pdf |EMSS.html✨
EMSS/json (API)
NEWS

Peer review:

Bug tracker:https://github.com/sangkyustat/emss/issues

On CRAN:

1 exports 1.40 score 70 dependencies 3 mentions 1 scripts 208 downloads

Last updated 3 years agofrom:d7a3e1724c. Checks:OK: 7. Indexed: yes.

Exports:EMSS

Dependencies:abindbackportsbootbroomcarcarDataclicolorspacecowplotcpp11DerivdigestdoBydplyrfansifarverFormulagenericsggplot2gluegtableisobandlabelinglatticelifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmaxLikmgcvmicrobenchmarkminqamiscToolsmodelrmunsellmvtnormnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpurrrquantregR6RColorBrewerRcppRcppEigenrlangsampleSelectionsandwichscalesSparseMstringistringrsurvivalsystemfittibbletidyrtidyselectutf8vctrsVGAMviridisLitewithrzoo