#' Initialise tree options
#'
#' This function initialises tree options.
#' @param prune
#' @param nbcv
#' @param cvtype
#' @param sevalue
#' @param search
#' @param splitfrac
#' @param truncmeth
#' @param missregval
#' @param maxsplits
#' @param minnbnodes
#' @keywords GUIDE, tree, model, options
#' @export
#'
initTreeOptions <- function(
prune = "1", # 1=prune by CV, 2=no pruning
nbcv = 10, # Number of cross-validation steps (i.e. number of sub data spaces)
cvtype = "1", # 1=mean-based CV tree, 2=median-based CV tree
sevalue = 0.5, # Standard Error number for pruning [0..1]
search = "2", # 1=split point from quantiles, 2=use exhaustive search
quantile1 = 0.25, # Option for Quantile regression (with 1 quantile)
quantile2 = 0.75, # Option for Quantile regression (with 2 quantiles)
splitfrac = 1.00, # 1=accept default splitting fraction (i.e. frac, where #splits = max(9,fract*n), with n = #cases in node), 2=change it
truncmeth = "3", # Data truncation method (0=none, 1=node range, 2=+10% node range, 3=global range, 4=2-sided Winsorization)
missregval = "2", # missing regressor values: 1=separate models, 2=impute with means, 3=constant model
maxsplits = 10, # max. no. split levels
minnbnodes = 3 # min. node sample size
){
out <- data.frame(
prune = prune,
nbcv = nbcv,
cvtype = cvtype,
sevalue = sevalue,
truncmeth = truncmeth,
missregval = missregval,
splitfrac = splitfrac,
search = search,
maxsplits = maxsplits,
minnbnodes = minnbnodes,
quantile1 = quantile1,
quantile2 = quantile2
)
return(out)
}
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