Package: spldv 0.2.2

Mauricio Sarrias

spldv: Spatial Models for Limited Dependent Variables

The current version of this package estimates spatial autoregressive models for binary dependent variables using GMM estimators <doi:10.18637/jss.v107.i08> and RIS estimator <doi:10.1007/978-3-662-05617-2_8>. It supports one-step (Pinkse and Slade, 1998) <doi:10.1016/S0304-4076(97)00097-3> and two-step GMM estimator along with the linearized GMM estimator proposed by Klier and McMillen (2008) <doi:10.1198/073500107000000188>. It also allows for either Probit or Logit model and compute the average marginal effects. The RIS estimator allows to estimate the SAR and SEM model. All these models are presented in Sarrias and Piras (2023) <doi:10.1016/j.jocm.2023.100432>.

Authors:Mauricio Sarrias [aut, cre], Gianfranco Piras [aut], Daniel McMillen [ctb]

spldv_0.2.2.tar.gz
spldv_0.2.2.zip(r-4.7)spldv_0.2.2.zip(r-4.6)spldv_0.2.2.zip(r-4.5)
spldv_0.2.2.tgz(r-4.6-any)spldv_0.2.2.tgz(r-4.5-any)
spldv_0.2.2.tar.gz(r-4.7-any)spldv_0.2.2.tar.gz(r-4.6-any)
spldv_0.2.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
spldv/json (API)
NEWS

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

Bug tracker:https://github.com/gpiras/spldv/issues

On CRAN:

Conda:

2.78 score 1 stars 1 packages 1 scripts 228 downloads 7 exports 102 dependencies

Last updated from:2c46f99d6e. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK194
source / vignettesOK185
linux-release-x86_64OK170
macos-release-arm64OK220
macos-oldrel-arm64OK244
windows-develOK156
windows-releaseOK160
windows-oldrelOK124
wasm-releaseOK137

Exports:bread.binrisestfun.binrisimpactsmake.instrumentssbinaryGMMsbinaryLGMMsbinaryRis

Dependencies:abindbackportsbootbroomcarcarDatacheckmateclassclassIntclicodacodetoolscolorspacecowplotcpp11data.tableDBIdeldirDerivdigestdoBydplyre1071farverforecastFormulafracdiffgenericsggplot2gluegtableinsightisobandjsonliteKernSmoothlabelinglatticeLearnBayeslifecyclelme4lmtestmagrittrmarginaleffectsMASSMatrixMatrixModelsmaxLikmemiscmgcvmicrobenchmarkminqamiscToolsmodelrmultcompmvtnormnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigproxypurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangs2S7sandwichscalessfspSparseMspatialregspDataspdepsphetstringistringrsurvivalTH.datatibbletidyrtidyselecttimeDateunitsurcautf8vctrsviridisLitewithrwkyamlzoo

Readme and manuals

Help Manual

Help pageTopics
Get Model Summaries for use with "mtable" for objects of class bingmmgetSummary.bingmm
Get Model Summaries for use with "mtable" for objects of class binlgmmgetSummary.binlgmm
Get Model Summaries for use with "mtable" for objects of class binrisgetSummary.binris
Compute Marginal Effects for Spatial Binary Modelsimpacts impacts.bingmm impacts.binlgmm impacts.binris print.impacts.bingmm print.summary.impacts.bingmm summary.impacts.bingmm
Make instruments for spatial modelsmake.instruments
Predictions for Spatial Binary GMM Modelspredict.bingmm
Predictions for Spatial Binary LGMM Modelspredict.binlgmm
Predictions for Spatial Binary RIS Modelspredict.binris
GMM Estimation for Binary Spatial Autoregressive Models.coef.bingmm print.bingmm print.summary.bingmm sbinaryGMM summary.bingmm vcov.bingmm
Estimation of SAR for binary models using Linearized GMM.coef.binlgmm print.binlgmm print.summary.binlgmm sbinaryLGMM summary.binlgmm vcov.binlgmm
Estimation of spatial probit model for binary outcomes using RIS (GHK) simulatorbread.binris coef.binris df.residual.binris estfun.binris logLik.binris print.binris print.summary.binris sbinaryRis summary.binris terms.binris vcov.binris