This vignette is kept for backward compatibility with the original package article structure. New users should start with “Getting started with GLBFP”, then read “Package overview and workflow map”.
library(GLBFP)
data("ashua")
river_data <- ashua[, c("flow", "level")]
x0 <- c(mean(river_data$flow), mean(river_data$level))
b <- c(8, 0.4)
fit <- GLBFP(x0, river_data, b = b, m = c(1, 1))
fit
#> GLBFP Density Estimation:
#> Point: (249.0230, 30.4197)
#> Estimated density: 0.00377442
#> Estimated standard error: 0.000316735
#> 95% confidence interval: 0.00376918, 0.00377966
#> Bandwidths (b): 8.0, 0.4
#> Shifts (m): 1, 1
#> Relative grid coordinate (u): 0.690325, 0.224216
grid_fit <- GLBFP_estimate(
river_data,
b = b,
m = c(1, 1),
grid_size = 12
)
head(as.data.frame(grid_fit))
#> flow level density sd IC_lower IC_upper visited
#> 1 39.5 29.33 0.001085811 0.0006951193 0.001074315 0.001097307 4
#> 2 175.0 29.33 0.000000000 0.0000000000 0.000000000 0.000000000 2
#> 3 310.5 29.33 0.000000000 0.0000000000 0.000000000 0.000000000 0
#> 4 446.0 29.33 0.000000000 0.0000000000 0.000000000 0.000000000 0
#> 5 581.5 29.33 0.000000000 0.0000000000 0.000000000 0.000000000 0
#> 6 717.0 29.33 0.000000000 0.0000000000 0.000000000 0.000000000 0
#> prefix_nodes
#> 1 6
#> 2 6
#> 3 6
#> 4 6
#> 5 6
#> 6 6