Package: WALS 0.2.6

WALS: Weighted-Average Least Squares Model Averaging

Implements Weighted-Average Least Squares model averaging for negative binomial regression models of Huynh (2024) <doi:10.48550/arXiv.2404.11324>, generalized linear models of De Luca, Magnus, Peracchi (2018) <doi:10.1016/j.jeconom.2017.12.007> and linear regression models of Magnus, Powell, Pruefer (2010) <doi:10.1016/j.jeconom.2009.07.004>, see also Magnus, De Luca (2016) <doi:10.1111/joes.12094>. Weighted-Average Least Squares for the linear regression model is based on the original 'MATLAB' code by Magnus and De Luca <https://www.janmagnus.nl/items/WALS.pdf>, see also Kumar, Magnus (2013) <doi:10.1007/s13571-013-0060-9> and De Luca, Magnus (2011) <doi:10.1177/1536867X1201100402>.

Authors:Kevin Huynh [aut, cre]

WALS_0.2.6.tar.gz
WALS_0.2.6.zip(r-4.7)WALS_0.2.6.zip(r-4.6)WALS_0.2.6.zip(r-4.5)
WALS_0.2.6.tgz(r-4.6-any)WALS_0.2.6.tgz(r-4.5-any)
WALS_0.2.6.tar.gz(r-4.7-any)WALS_0.2.6.tar.gz(r-4.6-any)
WALS_0.2.6.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
WALS/json (API)
NEWS

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

Bug tracker:https://github.com/kevhuy/wals/issues

Datasets:
  • GrowthMP - Determinants of Economic Growth
  • GrowthMPP - Determinants of Economic Growth

On CRAN:

Conda:

2.70 score 1 stars 6 scripts 139 downloads 19 exports 4 dependencies

Last updated from:7dbc8c4495. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK144
source / vignettesOK194
linux-release-x86_64OK165
macos-release-arm64OK133
macos-oldrel-arm64OK168
windows-develOK120
windows-releaseOK105
windows-oldrelOK86
wasm-releaseOK112

Exports:binomialWALScontrolGLMcontrolNBfamilyPriorfamilyWALSlaplacenegbinFixedWALSnegbinWALSpoissonWALSsubbotinwalswalsFitwalsGLMwalsGLMfitwalsGLMfitIteratewalsNBwalsNBfitwalsNBfitIterateweibull

Dependencies:FormulaMASSrbibutilsRdpack

Readme and manuals

Help Manual

Help pageTopics
Internal function: Check singularity of SVDed matrixcheckSingularitySVD
Internal function: Compute model-averaged estimator of focus regressors in walsNBcomputeGamma1
Internal function: Computes fully restricted one-step ML estimator for transformed regressors in walsNBcomputeGamma1r
Internal function: Computes unrestricted one-step ML estimator for transformed regressors in walsNBcomputeGammaUnSVD
Internal function: Compute posterior mean and variance of normal location problemcomputePosterior computePosterior.familyPrior computePosterior.familyPrior_laplace
Internal function: Computes X2M1X2 for walsNB when SVD is applied to Z1computeX2M1X2
Control function for initial GLM fitcontrolGLM
Control function for initial NB fitcontrolNB
Internal function: double (reflected) Weibull densityddweibull
Internal function: Laplace densitydlaplace
Internal function: Subbotin densitydsubbotin
Family Objects for Prior Distributions in WALSfamilyPrior familyPrior.wals familyPrior_laplace laplace print.familyPrior subbotin weibull
Extended Family Objects for ModelsbinomialWALS familyNBWALS familyWALS familyWALS.walsGLM familyWALScount negbinFixedWALS negbinWALS poissonWALS
Internal function: Fits a NB2 regression via maximum likelihood with log-link for mean and dispersion parameter.fitNB2
Internal function: Transform gammas back to betasgammaToBeta
Determinants of Economic GrowthGrowthMP
Determinants of Economic GrowthGrowthMPP
Negative binomial familynegativeBinomial
Methods for wals and walsMatrix Objectscoef.wals fitted.wals model.matrix.wals nobs.wals predict.wals predict.walsMatrix print.summary.wals print.wals residuals.wals summary.wals terms.wals vcov.wals
Methods for walsGLM, walsGLMmatrix, walsNB and walsNBmatrix ObjectslogLik.walsGLM predict.walsGLM predict.walsGLMmatrix print.summary.walsGLM print.summary.walsNB print.walsGLM residuals.walsGLM summary.walsGLM summary.walsNB
Internal methods: Predict probability for countspredictCounts predictCounts.familyWALScount
Internal function: Semiorthogonal-type transformation of X2 to Z2semiorthogonalize
Internal function: first derivatives of NB2 PMFsnbinom
Internal function: Uses SVD components to compute final estimate via Sherman-Morrison-Woodbury formula.svdLSplus
Calculate Variance-Covariance Matrix for a '"walsNB"' objectvcov.walsNB
Weighted-Average Least Squares for linear regression modelswals wals.default wals.formula wals.matrix
Fitter function for Weighted Average Least Squares estimationwalsFit
Weighted Average Least Squares for Generalized Linear ModelswalsGLM walsGLM.default walsGLM.formula walsGLM.matrix walsGLMmatrix
Fitter function for Weighted Average Least Squares estimation of GLMswalsGLMfit
Iteratively fitting walsGLM, internal function for walsGLM.formula and walsGLM.matrix.walsGLMfitIterate
Weighted-Average Least Squares for Negative Binomial RegressionwalsNB walsNB.default walsNB.formula walsNB.matrix walsNBmatrix
Fitter function for Weighted Average Least Squares estimation of NB2 regression modelwalsNBfit
Iteratively fitting walsNB, internal function for walsNB.formula and walsNB.matrix.walsNBfitIterate