#' @title Summary of spatial cross correlation
#' @description summary method for class "cross.cor"
#'
#' @param object Object of class cross.cor
#' @param ... Ignored
#'
#'
#' @return
#' When not simulated k=0, prints functions list object containing:
#' * I - Global autocorrelation statistic
#' * SCI - - A data.frame with two columns representing the xy and yx autocorrelation
#' * nsim - value of NULL to represent p values were derived from observed data (k=0)
#' * p - Probability based observations above/below confidence interval
#' * t.test - Probability based on t-test
#'
#' When simulated (k>0), prints functions list object containing:
#' * I - Global autocorrelation statistic
#' * SCI - A data.frame with two columns representing the xy and yx autocorrelation
#' * nsim - value representing number of simulations
#' * global.p - p-value of global autocorrelation statistic
#' * local.p - Probability based simulated data using successful rejection of t-test
#' * range.p - Probability based on range of probabilities resulting from paired t-test
#' @md
#'
#' @method summary cross.cor
#'
#' @export
summary.cross.cor <- function(object, ...) {
if(!is.null(object$nsim)) {
cat("Moran's-I under randomization assumptions...", "\n")
cat(" First-order Moran's-I: ", object$I, "\n")
cat(" First-order p-value: ", object$global.p, "\n")
cat("", "\n")
cat("Chen's SCI under randomization assumptions...", "\n")
cat("\n", "Summary statistics of local partial cross-correlation [xy]", "\n")
print( summary(object$SCI[,1]) )
cat("\n", "", "\n")
cat(" p-value based on 2-tailed t-test: ", object$local.p, "\n")
cat(" p-value based on 2-tailed t-test observations above/below CI: ", object$range.p, "\n")
if( exists(object$clusters) )
cat("\n", "Counts of cluster types")
print(table(object$cluster))
} else {
cat("Moran's-I...", "\n")
cat(" First-order Moran's-I: ", object$I, "\n")
cat(" First-order p-value: ", object$global.p, "\n")
cat("", "\n")
cat("Chen's SCI under randomization assumptions...", "\n")
cat("\n", "Summary statistics of local partial cross-correlation [xy]", "\n")
print( summary(object$SCI[,1]) )
cat("\n", "", "\n")
cat(" non-simulated second-order p-value based on 2-tailed t-test: ", object$t.test, "\n")
cat(" p-value based on 2-tailed t-test observations above/below CI: ", object$p, "\n")
if( exists(object$clusters) )
cat("\n", "Counts of cluster types")
print(table(object$cluster))
}
}
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