The goal of GWlasso is to provides a set of functions to perform Geographically weighted lasso. It was originally thought to be used in palaeoecological settings but can be used to other extents.
# install.packages("devtools")
devtools::install_github("nibortolum/GWlasso")library(GWlasso)
## compute a distance matrix from a set of coordinates
distance_matrix <- compute_distance_matrix <- function(coords, method = "euclidean", add.noise = FALSE)
## compute the optimal bandwidth
myst.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 model
my.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 predictions
predicted_values <- predict(my.gwl.fit, newdata = new_data, newcoords = new_coords)RetroSearch is an open source project built by @garambo | Open a GitHub Issue
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