## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

## ----setup--------------------------------------------------------------------
library(GWlasso)

## ----Amesbury-----------------------------------------------------------------

data(Amesbury)

## ----getbw, eval = FALSE, include = TRUE--------------------------------------
# 
# # compute the distance matrix
# distance_matrix <- compute_distance_matrix(Amesbury$coords, add.noise = TRUE)
# 
# # run the bw selection algorithm
# bw_choice <- gwl_bw_estimation(x.var = Amesbury$spe.df,
#                       y.var = Amesbury$WTD,
#                       dist.mat = distance_matrix,
#                       adaptive = TRUE,
#                       adptbwd.thresh = 0.1,
#                       kernel = "bisquare",
#                       alpha = 1,
#                       progress = TRUE,
#                       n = 100)
# 

## ----fitgwl, eval = FALSE, include = TRUE-------------------------------------
# 
# # compute the distance matrix
# distance_matrix <- compute_distance_matrix(Amesbury$coords, add.noise = TRUE)
# 
# my.gwl.fit <- gwl_fit(bw= 120,
#                      x.var = Amesbury$spe.df,
#                       y.var = Amesbury$WTD,
#                       dist.mat = distance_matrix,
#                       adaptive = TRUE,
#                       kernel = "bisquare",
#                       alpha = 1,
#                       progress = TRUE)
# 
# plot(my.gwl.fit)

## ----pred, include = TRUE, eval=FALSE-----------------------------------------
# 
# my_predicted_values <- predict(my.gwl.fit, newdata = Amesbury$spe.df, newcoords = Amesbury$coords)
# 
# plot( my_predicted_values ~Amesbury$WTD)
# abline(0,1, col="red")