The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
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 6These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.