autofitVariogram {AgePopDenom} | R Documentation |
Automatically Fit a Variogram Model
Description
This function was originally sourced from the 'automap' package (version 1.1-16), which is no longer available on CRAN. It is provided here with minimal modification for internal use in this package.
'autofitVariogram()' automates the fitting of a variogram model to spatial input data by testing a range of model types and kappa values (for Matern and Stein models), and selecting the best-fit model based on the sum of squared errors.
Dependencies from 'gstat', 'sp', and 'sf' are required for this function to operate correctly.
Usage
autofitVariogram(
formula,
input_data,
model = c("Sph", "Exp", "Gau", "Ste"),
kappa = c(0.05, seq(0.2, 2, 0.1), 5, 10),
fix.values = c(NA, NA, NA),
verbose = FALSE,
GLS.model = NA,
start_vals = c(NA, NA, NA),
miscFitOptions = list(),
...
)
Arguments
formula |
model formula for the variogram (e.g., 'z ~ 1') |
input_data |
an 'sf' or 'Spatial*' object containing the spatial data |
model |
a character vector of variogram model names (e.g., '"Sph"', '"Exp"') |
kappa |
vector of kappa values for Matern/Stein models |
fix.values |
optional vector of fixed values for nugget, range, sill |
verbose |
logical; if 'TRUE', prints additional output |
GLS.model |
optional variogram model for Generalized Least Squares |
start_vals |
optional vector of starting values for nugget, range, sill |
miscFitOptions |
named list of additional control options |
... |
additional arguments passed to 'gstat::variogram()' |
Value
a list with class '"autofitVariogram"' containing:
- exp_var
the empirical variogram
- var_model
the best-fit variogram model object
- sserr
sum of squared errors for the best model
Note
Original author: J. H. Hiemstra (2013), 'automap' package. License: GPL-2 | GPL-3.
Examples
## Not run:
result <- autofitVariogram(z ~ 1, input_data)
plot(result$exp_var)
plot(result$var_model)
## End(Not run)