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###########################################################################
## ##
## bootstrap() - Generic function to calculate bootstrap statistics for ##
## transfer function models - only a method for class mat ##
## currently available ##
## ##
## Created : 27-May-2006 ##
## Author : Gavin Simpson ##
## Version : 0.1 ##
## Last modified : 27-May-2006 ##
## ##
###########################################################################
summary.bootstrap.mat <- function(object, ...)
{
class(object) <- "summary.bootstrap.mat"
#class(object) <- "summary.bootstrap"
return(object)
}
print.summary.bootstrap.mat <- function(x,
#print.summary.bootstrap <- function(x,
digits = 3,
...)
{
print.bootstrap.mat(x, digits = digits, ...)
#print.bootstrap(x)
cat("\nBootstrap estimated values for training set:\n")
with(x$bootstrap, print(estimated[,k], digits = digits, ...))
if(!is.null(x$predictions)) {
cat(paste("\nPredicted values based on a",
ifelse(x$weighted, " weighted", ""),
" model with ", x$apparent$k,
"-closest analogues\n", sep = ""))
if(x$auto)
cat("(k chosen from model with lowest RMSEP)\n\n")
else
cat("\n")
with(x$predictions$model, print(predicted[k,], digits = digits, ...))
}
if(!is.null(x$predictions)) {
cat(paste("\nBoostrap predicted values based on a",
ifelse(x$weighted, " weighted", ""),
" model with ", x$bootstrap$k,
"-closest analogues\n", sep = ""))
if(x$auto)
cat("(k chosen from model with lowest RMSEP)\n\n")
else
cat("\n")
with(x$predictions$bootstrap, print(predicted[,k], digits = digits, ...))
}
cat("\nTraining set assessment:\n\n")
k.model <- x$model$k
k.boot <- x$bootstrap$k
dat <- data.frame(Obs = x$observed,
Est = x$model$estimated[k.model,],
Resid = x$model$residuals[k.model,],
Boot.Est = x$bootstrap$estimated[,k.boot],
Boot.Resid = x$bootstrap$residuals[,k.boot],
s1 = x$sample.errors$s1[,k.boot],
s2 = x$sample.errors$s2[,k.boot],
RMSEP = x$sample.errors$rmsep[,k.boot])
print(dat, digits = digits, ...)
invisible(x)
}
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