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##########################################################################
## SAVE structure class
##
## This software is distributed under the terms of the GNU GENERAL
## PUBLIC LICENSE Version 3, April 2013.
##
## Copyright (C) 2013-present Jesus Palomo, Gonzalo Garcia-Donato,
## and Rui Paulo
##
##########################################################################
## ----------------
## CLASS definition
## ----------------
## SAVE Class
setClass("SAVE",
representation(
#data
responsename="character", ##name of the response
controllablenames="character", ##names of the controllable inputs
constant.controllables="logical", ##whether the controllable inputs are constant T or not F. Default in the Code is F.
calibrationnames="character", ##names of the calibration inputs
df="matrix", ##field design (no replicates)
dm="matrix", ##model design
ym="numeric", ##model response associated with dm
yf="numeric", ##field response associated with df
#mle fit
meanformula="formula", ##linear model for the mean of the GP
mle="list", ##three components: thetaL, thetaM, thetaF
bestguess="numeric", ##bestguess
xm="matrix", ##design matrix associated with mean formula
xf="matrix", ##design matrix associated with
##=model.matrix(mean.formula,x.unique)
#bayesian options
prior="matrix",
method="numeric",
mcmcMultmle="numeric",
#bayesian fit
mcmcsample="matrix",
#other
wd="character",
call="call",
bayesfitcall="call"
)
)
validSAVEobject <- function(object) {
if (is.null(object@responsename) || length(object@responsename)==0)
{return("Response names are not provided\n")}
if (is.null(object@controllablenames) || length(object@controllablenames)==0)
{return("Controllable names are not provided\n")}
if (is.null(object@yf) || length(object@yf)==0)
{return("field data are not provided\n")}
if (is.null(object@ym) || length(object@ym)==0)
{return("Model data are not provided\n")}
TRUE
}
setValidity("SAVE",validSAVEobject)
setClass("summary.SAVE", representation(
#only STAGEI:
stage2 = "logical",
call = "call",
mle = "list",
#STAGEII also:
bayesfitcall = "call",
mcmcsum = "matrix"
)
)
setClass("predictcode.SAVE", representation(
predictcodecall = "call",
mle = "list",
samples = "data.frame",
newdesign = "data.frame",
modelmean = "vector",
covmat = "matrix"
)
)
setClass("summary.predictcode.SAVE", representation(
call = "call",
summariesmodelpred = "matrix",
modelmean = "vector"
)
)
setClass("predictreality.SAVE", representation(
#first half of samples is prediction and second half is bias
predictrealitycall = "call",
modelpred = "data.frame",
biaspred = "data.frame",
newdesign = "data.frame"
)
)
setClass("summary.predictreality.SAVE", representation(
call = "call",
biascorr = "matrix",
biaspred = "matrix"
)
)
setClass("validate.SAVE", representation(
call = "call",
bayesfitcall = "call",
validatecall = "call",
newdesign = "data.frame",
validate = "matrix"
)
)
setClass("summary.validate.SAVE", representation(
callSAVE = "call",
callbayes = "call",
callvalidate = "call",
summaries = "matrix"
)
)
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