Legacy estimation example

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