gdm.cv.Rd

% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/gdm.cv.R
\name{gdm.cv}
\alias{gdm.cv}
\title{Performs n-fold cross-validation of GDM model}
\usage{
gdm.cv(spData, nfolds = 10, performance = "rmse", geo = F)
}
\arguments{
\item{spData}{Combined site pair dataset ("spData" format).}

\item{nfolds}{Number of folds for cross-validation. Default is 10 folds. If number of folds equals number of samples then leave-one-out cross-validation is performed.}

\item{performance}{Performance metric to be used for validation: \code{"rmse"} for root mean square error (RMSE) or \code{"r2"} for coefficient of determination (r2). Set as \code{"rmse"} per default.}

\item{geo}{Optional use of geographical distance as predictor in GDM model. set to \code{FALSE} per default.}
}
\value{
Returns model performance value.
}
\description{
This function performs n-fold cross-validation of a GDM model.

It requires a combined site pair ("spData" format) dataset, as well as the definition of the number of folds to be used in the cross-validation, the performance measure to be used and the optional use of geographical distance as predictor variable in the GDM.

For more details relating to "spData" data format, check \code{gdm} package.
}