Nothing
#******************************************************************************
#* +------------------------------------------------------------------------+ *
#* | R M E | *
#* | Function 'dfr.rhetro', MM robust estimate of a nonlinear function. | *
#* | with hetro variance model function. derivative free. | *
#* | generalized | *
#* | Note: becarefull to using this function when there is not outlier, it | *
#* | may not work witout outlier, in this case better to use nlmest | *
#* | the problem is in part of two (p2) in hessian its big here. | *
#* | argumnts: | *
#* | formula: 'nl.form' object, the function mode. | *
#* | data: data, contains dependents and independents, | *
#* | data.frame, list or named matrix it can be. | *
#* | start: starting values, it must contains 'sigma', selstart | *
#* | for nl.form object is not created yet, take cre of it. | *
#* | varmodel: var function, it must be nl.form of variance models | *
#* | tau: starting value of tau. if is null the stored value in | *
#* | vardnc object of nl.form will be stored. | *
#* | ...: can be entries for robust loss function parameters. | *
#* | Method: is to control when error happens and need control | *
#* | manually, program try to control errors but other | *
#* | un predicted error like log(0) may happens. | *
#* | | *
#* | Important Note: variance must be a product function in sigma, i.e. | *
#* | varfunc = sigma^2 * h(f,tau) | *
#* | in feature the general form will be added. | *
#* | | *
#* +------------------------------------------------------------------------+ *
#******************************************************************************
dfr.robhetro <- function(formula, data, start=getInitial(formula,data),
control=nlr.control(tolerance=1e-5, minlanda=1 / 2 ^ 10, maxiter=100 * length(start)),
robfunc,varmodel,tau=NULL,method="NLM",...){
tolerance <- control$tolerance
maxiter <- control$maxiter
minlanda <- control$minlanda
trace <- control$trace
FT <- NULL
switch(method,
"NLM"={
stage1 <- dfrmest.NLM(formula, data=data, start=start,control=control,robfunc=robfunc,...)
if(is.Fault(stage1)){
print("nl.robhetro stoped at stage 1 with error.")
stage1 <- nlmest.NM(formula, data=data, start=start,control=control,robfunc=robfunc,...)
if(is.Fault(stage1)) return(stage1)
}
},
"NM"={
stage1 <- nlmest.NM(formula, data=data, start=start,control=control,robfunc=robfunc,...)
if(is.Fault(stage1)) return(stage1)
}
)
ri <- residuals(stage1)
nrp <- nonrepl(list(x=data[[formula$independent]],y=data[[formula$dependent]]))
z <- rzvalues(ri,nrp$ni,nrp$xo) #[nrp$xm] ## variance z=zi , si^2 ##
data2 <- NULL
data2[[varmodel$dependent]] <- z[nrp$xm] ## vr, (nonreplicate) ##
if(is.null(data[[varmodel$independent]])) {
t <- predict(stage1,newdata=stage1$data)
data2[[varmodel$independent]] <- t[nrp$xm] ## t=mu (nonreplicate) ##
}
else
data2[[varmodel$independent]] <- data[[varmodel$independent]][nrp$xm]
if(any(data2[[2]]<0)){
return(Fault(FN=20))
}
###### stage 2 ########################################################################
if(is.null(tau))
if(is.null(varmodel$selfStart)) start.tau <- varmodel$par
else{
data2 <- NULL
data2[[varmodel$dependent]] <- z[nrp$xm]
if(is.null(data[[varmodel$independent]]))
data2[[varmodel$independent]] <- predict(stage1,newdata=stage1$data)[nrp$xm]
else
data2[[varmodel$independent]] <- data[[varmodel$independent]][nrp$xm] # non replicated #
start.tau <- getInitial(varmodel,data2)
}
else start.tau <- tau
# print("start stage 2222--------------------------------------------------")
stage2<- optim.NM(objfnc=loss.robchis,data=data,start=start.tau,formula=formula,
theta=stage1$parameters,varmodel=varmodel,robfunc=robfunc,
control=control,...)
if(is.Fault(stage2)){
print("error at stage 2 robhetro")
return(stage2)
}
# if(stage2$parameters$sg < 0){
# result <- stage2
# result$Fault <- Fault(FN=19,FF="nl.robhetro")
# return(result)
#}
###### stage 3 ########################################################################
ps <- stage1$parameters[names(formula$par)]
vc <- as.numeric(stage2$objfnc$varcomp$predictor)
if(any(vc<0)) result$Fault <- Fault(FN=19,FF="nl.robhetro")
gvar <- vc#/stage2$parameters$sg^2
vmat <- diag(gvar)
rmat <- diag(1.0/sqrt(gvar))
switch(method,
"NLM"={
stage3 <- dfrmest.NLM(formula, data=data, start=ps,
control=nlr.control(maxiter=maxiter*20,tolerance=tolerance*10,trace=trace,minlanda=minlanda,robscale=control$robscale),vm=vmat,rm=rmat,robfunc=robfunc,...)
if(is.Fault(stage3)) return(stage3)
},
"NM"={
stage3 <- nlmest.NM(formula, data=data, start=ps,
control=nlr.control(maxiter=maxiter*20,tolerance=tolerance*10,trace=trace,minlanda=minlanda,robscale=control$robscale),vm=vmat,rm=rmat,robfunc=robfunc,...)
if(is.Fault(stage3)) return(stage3)
}
)
result <- stage3
htheta <- stage2$objfnc$value
result@method<- fittmethod(methodID=5,subroutine ="nl.robhetro",lossfunction="robloss.gn")
result@hetro<-nl.fitt.rob(
parameters= stage2$parameters,
form= varmodel,
predictor = stage2$objfnc$varcomp$predictor,
response = stage2$objfnc$zi,
history = stage2$history,
method = stage2$method,
data = stage2$objfnc$vcmdata,
sourcefnc = stage2$objfnc$sourcefnc,
Fault = Fault(FT=FT),
htheta = stage2$objfnc$value,
rho = stage2$objfnc$rho)
result@others=list(refvar=stage2$objfnc$refvar)
return(result)
}
#+#################################################################################+
#| |
#| End of the object 'drf.robhetro' |
#| |
#| 15 Aug 2013 |
#| |
#| Hossein Riazoshams, Stat Dep, Stockholm U |
#| |
#+#################################################################################+
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.