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Geographically Weighted Lasso with R

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nibortolum/GWlasso

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R-CMD-checkLifecycle: stableCRAN statusDowloads

The goal of GWlasso is to provides a set of functions to performGeographically weighted lasso. It was originally thought to be used inpalaeoecological settings but can be used to other extents.

Installation

You can install the development version of GWlasso fromGitHub with:

# install.packages("devtools")devtools::install_github("nibortolum/GWlasso")

You can install the stable version directly from CRAN with

install.packages("GWlasso")

Example

This is a basic example on how to run a GWlasso pipeline:

library(GWlasso)## compute a distance matrix from a set of coordinatesdistance_matrix<-compute_distance_matrix<-function(coords,method="euclidean",add.noise=FALSE)## compute the optimal bandwidthmyst.est<- gwl_bw_estimation(x.var=predictors_df,y.var=y_vector,dist.mat=distance_matrix,adaptive=TRUE,adptbwd.thresh=0.1,kernel="bisquare",alpha=1,progress=TRUE,n=40,nfolds=5)## Compute the optimal modelmy.gwl.fit<- gwl_fit(myst.est$bw,x.var=data.sample[,-1],y.var=data.sample$WTD,kernel="bisquare",dist.mat=distance_matrix,alpha=1,adaptive=TRUE,progress=T)## make predictionspredicted_values<- predict(my.gwl.fit,newdata=new_data,newcoords=new_coords)

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