Man pages for wrbrooks/gwselect
Variable selection in Geographically Weighted Regression models

gwglmnetFit a GW-GLM model using the LASSO for variable selection.
gwglmnet.adaptive.fitUse the adaptive LASSO to fit a GLM in the GWR setting.
gwglmnet.adaptive.ssrGet the sum of squared residuals in for a...
gwglmnet.cv.fPerform cross-validation for bandwidth selection in a gw-glm...
gwglmnet.fitFit a gw-glm model using the LASSO for variable selection
gwglmnet.nenCreate a GW-GLM model using the LASSO for variable selection...
gwglmnet.nen.adaptive.fitFit a GW-GLM model using the LASSO for variable selection and...
gwglmnet.nen.adaptive.fit.parallelFit a GW-GLM model using the LASSO for variable selection and...
gwglmnet.nen.cv.fCross-validation for selection of tuning parameter in a...
gwglmnet.nen.fitFit a GW-GLM model using Nearest Effective Neighbors for...
gwglmnet.nen.fit.parallelMulticore-aware function to fit a GW-GLM model using the...
gwglmnet.nen.selBandwidth selection using Nearest Effective Neighbors in a...
gwglmnet.selBandwidth selection in a GW-GLM model (bandwidth in terms of...
gwlarsFit a GW-GLM model using the LASSO for variable selection.
gwlars.selFit a GW-GLM model using the LASSO for variable selection.
gwr.matplotHeatmap plotting function for gwrselect package
gwselect-packageVariable selection for a geographically weighted regression...
legendFit a GW-GLM model using the LASSO for variable selection.
registerCoresRegister multiple cores for parallelization via doMC
utilsutility functions for the gwselect package
wrbrooks/gwselect documentation built on May 4, 2019, 11:59 a.m.