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step.ts.fit<-function(y, x.lin, Xtrue, PSI, opz, return.all.sol=FALSE){
#----------------------
search.min<-function(h, psi, psi.old, X, y, id.fix.psi=NULL) {
psi.ok<- psi*h + psi.old*(1-h)
psi.ok[id.fix.psi]<- psi.old[id.fix.psi]
PSI <- matrix(psi.ok, n, ncol = length(psi.ok), byrow=TRUE)
U1 <- (Xtrue>PSI) #(Z - PSI) * (Z > PSI)
#if (pow[1] != 1) U1 <- U1^pow[1]
obj1 <- try(mylm(cbind(X, U1), y), silent = TRUE)
#if (class(obj1)[1] == "try-error") obj1 <- try(lm.wfit(cbind(X, U1), y, w, offs), silent = TRUE)
#if (class(obj1)[1] == "try-error") obj1 <- try(.lm.fit(cbind(X, U1), y), silent = TRUE)
L1 <- if (class(obj1)[1] == "try-error") L0 + 10 else obj1$L0
#r<-sum(obj1$residuals^2 * w)
L1
}
toMatrix<-function(.x, ki){
# ripete ogni .x[,j] ki[j] volte
if(ncol(.x)!=length(ki)) stop("It should be ncol(.x)==length(ki)")
if(all(ki==1)) return(.x)
M<-vector("list", length=length(ki))
for(j in 1:length(ki)) M[[j]]<-replicate(ki[[j]], cbind(.x[,j]), simplify=TRUE)
do.call(cbind, M)
}
### -----
mylm <-function(x,y){ #,w=1,offs=0 in step.st.fit() non ci sovrebbero essere w e offs
#x1<-x*sqrt(w)
#y<-y-offs
#y1<-y*sqrt(w)
#o<-.lm.fit(y=y,x=x)
#b<-o$coefficients
#fit<- o$fitted.values
#r<-o$residuals
b<-drop(solve(crossprod(x),crossprod(x,y))) #x<-x1
#b<-solve(crossprod(x),crossprod(x,y))
#browser()
#fit<- drop(tcrossprod(x,t(b)))
fit<- drop(x%*%b)
r<-y-fit
o<-list(coefficients=b, fitted.values=fit, residuals=r, L0=sum(r^2), df.residual=length(y)-length(b))
o
}
### -----
isZero <- function(v) sapply(v, function(.x) identical(.x,0))
###------
#-----------
adj.psi <- function(psii, LIM) {
pmin(pmax(LIM[1, ], psii), LIM[2, ])
}
#------------
tol<-opz$toll
display<-opz$display
it.max<-opz$it.max
dev0<-opz$dev0
#useExp.k<-opz$useExp.k
#min.step<- opz$min.step #=.0001
#conv.psi<-opz$conv.psi #=FALSE
alpha<-opz$alpha
#browser()
limZ <- apply(Xtrue, 2, quantile, names = FALSE, probs = c(alpha[1], alpha[2]))
#limZ <- apply(Xtrue, 2, quantile, names = FALSE, probs = c(alpha, 1 - alpha))
fix.npsi<-opz$fix.npsi
agg<-opz$agg
h<-opz$h
npsii<-opz$npsii
npsi<- sum(npsii) #opz$npsi
P<-length(npsii) #P<-opz$P
digits<-opz$digits
rangeZ<-opz$rangeZ
# pos.vec <- 1:npsi
# pos <- vector("list", P)
# ind <- 0
pos<- tapply(1:npsi, rep(1:P, npsii), list)
i <- 0
agg <- rep(agg, npsi)
#browser()
# direz <- matrix(NA, it.max, npsi)
# conv <- rep(FALSE, npsi)
# ind.conv <- NULL
n<-length(y)
plin<-ncol(x.lin)
epsilon<-10
k.values<-dev.values<- NULL
psi.values <-list()
dev.values[length(dev.values) + 1] <- opz$dev0 #modello senza psi
psi.values[[length(psi.values) + 1]] <- NA
#PSI0<- matrix(psi0, n, npsi, byrow = TRUE)
#XREG <- cbind(x.lin, Xtrue>PSI)
#obj0 <- .lm.fit(x=XREG, y=y) #try(mylm(XREG, y), silent = TRUE)
#L0 <- sum(obj0$residuals^2) #*ww
if(it.max==0){
obj <- lm.wfit(x = cbind(x.lin, Xtrue>PSI), y = y)
L1 <- sum(obj$residuals^2)
obj$epsilon <- epsilon
idZ<-(plin+1):(plin+ncol(PSI))
b<- obj$coef[idZ]
obj <- list(obj = obj, psi = PSI[1,], psi.values = psi.values,
rangeZ = rangeZ, beta.c=b, epsilon = epsilon,
SumSquares.no.gap = L1,
id.warn = TRUE)
return(obj)
}
L0<- mylm(cbind(x.lin, Xtrue>PSI),y)$L0 # valore con psi iniziale
n.intDev0<-nchar(strsplit(as.character(L0),"\\.")[[1]][1])
dev.values[length(dev.values) + 1] <- L0 #modello con psi iniziali
psi0<-PSI[1,]
psi.values[[length(psi.values) + 1]] <- psi0 #psi iniziali
#==============================================
if (display) {
unlpsi<- unlist(psi0)
Lp<-length(unlpsi)
cat(paste("iter = ", sprintf("%2.0f",0),
#" dev = ", sprintf(paste("%", n.intDev0+6, ".5f",sep=""), L0), #formatC(L1,width=8, digits=5,format="f"), #era format="fg"
" dev = ", sprintf("%1.5f", as.numeric(strsplit(format(L0, scientific=TRUE), "e")[[1]][1])),
" k = ", sprintf("%5.0f", NA),
" n.psi = ",formatC(Lp, digits=0,format="f"),
" ini.psi = ",paste(formatC(unlpsi[1:min(5,Lp)],digits=3,format="f"), collapse=" "), #sprintf('%.2f',x)
sep=""), "\n")
}
id.warn <- FALSE
low <- apply(Xtrue, 2, min)
up <- apply(Xtrue, 2, max)
#L1<-L0+10
tolOp<-if(is.null(opz$tol.opt)) seq(.001, .Machine$double.eps^0.25, l=it.max) else rep(opz$tol.opt, it.max)
idZ<-(plin+1):(plin+ncol(PSI))
idW<-(plin+ncol(PSI)+1): ( plin+2*ncol(PSI))
#==============================================
while (abs(epsilon) > tol) {
i <- i + 1
#if(i==1) browser()
xx <- Xtrue[,cumsum(npsii),drop=FALSE]
for (p in 1:P) {
psis <- sort(psi0[pos[[p]]])
gruppi <- cut(xx[,p], breaks = c(low[p] - 0.1, psis, up[p]), labels = FALSE)
if(any(is.na(gruppi))) stop(paste("too many breaks for step term #", p, "?"), call.=TRUE)
points <- c(low[p], psis, up[p])
right <- c(low[p], points[2:(npsii[p] + 1)] + agg[pos[[p]]][order(psi0[pos[[p]]])] * (points[3:(npsii[p] + 2)] - points[2:(npsii[p] + 1)]), NA)
left <- c(NA, points[2:(npsii[p] + 1)] - agg[pos[[p]]][order(psi0[pos[[p]]])] * (points[2:(npsii[p] + 1)] - points[1:npsii[p]]), up[p])
for (j in 1:(npsii[p] + 1)) {
xx.j <- xx[,p][gruppi == j]
xx[,p][gruppi == j] <- right[j] + (xx.j - points[j]) *
((left[j + 1] - right[j])/(points[j + 1] - points[j]))
}
}
XX<-toMatrix(xx, npsii)
PSI<- matrix(psi0, n, npsi, byrow = TRUE)
W <- (1/(2 * abs(XX - PSI)))
Z <- (XX * W + 1/2)
XREG <- cbind(x.lin, Z, W)
#obj<-try(mylm(XREG,y,w=ww,offs=offs), silent = TRUE)
#if(class(obj)[1]=="try-error")
obj <- .lm.fit(y = y, x = XREG) #obj <- lm.wfit(y = y, x = XREG, offset = offs, w=ww )
#b <- obj$coef[(2:(sum(k) + 1))]
#g <- obj$coef[((sum(k) + 2):(2 * sum(k) + 1))]
b<- obj$coef[idZ]
g<- obj$coef[idW]
#if(any(is.na(c(b, g)))){
if(any(isZero(c(b, g)))) {
if(return.all.sol) return(list(dev.values, psi.values)) else stop("breakpoint estimate too close or at the boundary causing NA estimates.. too many breakpoints being estimated?", call.=FALSE)
}
psi1 <- -g/b
psi1<- psi0+ h*(psi1-psi0)
psi1<- adj.psi(psi1, limZ) #limZ rangeZ
psi1<-unlist(tapply(psi1, opz$id.psi.group, sort), use.names =FALSE)
#la f e' chiaramente a gradino per cui meglio dividere..
a0<-optimize(search.min, c(0,.5), psi=psi1, psi.old=psi0, X=x.lin, y=y, tol=tolOp[i])
a1<-optimize(search.min, c(.5,1), psi=psi1, psi.old=psi0, X=x.lin, y=y, tol=tolOp[i])
a<-if(a0$objective<=a1$objective) a0 else a1
if(a$objective<L0){
k.values[length(k.values) + 1] <- use.k <- a$minimum
L1<- a$objective
} else {
k.values[length(k.values) + 1] <- use.k <- 0
L1<- L0
}
if(use.k<=.01){
k.List<-j.List<-NULL
for(j in 1:length(psi1)){
a0<-optimize(search.min, c(0,.5), psi=psi1, psi.old=psi0, X=x.lin, y=y, id.fix.psi=j, tol=tolOp[i])
a1<-optimize(search.min, c(.5,1), psi=psi1, psi.old=psi0, X=x.lin, y=y, id.fix.psi=j, tol=tolOp[i])
a <-if(a0$objective<=a1$objective) a0 else a1
if(a$objective<L1){
j.List[[j]]<-setdiff(1:length(psi1),j) #indici di psi che devono cambiare..
k.List[[j]]<-a$minimum
} else {
j.List[[j]]<-NA
k.List[[j]]<-NA
}
}
id.to.be.changed<- unique(unlist(j.List[!sapply(k.List, is.na)]))
if(!is.null(id.to.be.changed)){
use.k<-rep(0,length(psi1))
use.k[id.to.be.changed] <-mean(unlist(k.List[!sapply(k.List, is.na)]))
psi1 <- psi1*use.k + psi0* (1-use.k)
use.k<-mean(use.k)
L1=search.min(1, psi=psi1, psi.old=psi0, X=x.lin, y=y)
} else {
psi1<-psi0
}
} else {
psi1 <- psi1*use.k + psi0* (1-use.k)
}
if (!is.null(digits)) psi1 <- round(psi1, digits)
#PSI1 <- matrix(psi1, n, npsi, byrow = TRUE)
#XREG1 <- cbind(x.lin, Xtrue>PSI1)
#obj1 <- try(mylm(XREG1, y, ww, offs), silent = TRUE)
#if (class(obj1)[1] == "try-error") obj1 <- try(lm.wfit(XREG1, y, ww, offs), silent = TRUE)
delta<- psi1-psi0
if (display) {
flush.console()
#n.intDev0<-nchar(strsplit(as.character(dev.values[2]),"\\.")[[1]][1])
unlpsi<- unlist(psi1)
Lp<-length(unlpsi)
cat(paste("iter = ", sprintf("%2.0f",i),
#" dev = ", sprintf(paste("%", n.intDev0+6, ".5f",sep=""), L1), #formatC(L1,width=8, digits=5,format="f"), #era format="fg"
" dev = ", sprintf("%1.5f", as.numeric(strsplit(format(L1, scientific=TRUE), "e")[[1]][1])),
" k = ", sprintf("%2.3f", use.k),
" n.psi = ",formatC(Lp, digits=0, format="f"),
" est.psi = ",paste(formatC(unlpsi[1:min(Lp,5)],digits=3,format="f"), collapse=" "), #sprintf('%.2f',x)
sep=""), "\n")
}
epsilon <- (L0 - L1)/(abs(L0) + 0.1)
L0<-L1
k.values[length(k.values)+1]<-use.k
psi.values[[length(psi.values) + 1]] <- psi1
dev.values[length(dev.values) + 1] <- L0
if (i >= it.max) {
id.warn <- TRUE
break
}
psi0<-psi1
} #end while_it
psi1 <-unlist(tapply(psi1, opz$id.psi.group, sort))
PSI<- matrix(psi1, n, npsi, byrow = TRUE)
U <- 1*(Xtrue>PSI)
#ATTENZIONE .. Assume che obj sia stato stimato sempre!
obj<-list(obj=obj, psi=psi1, psi.values=psi.values, rangeZ=rangeZ, SumSquares.no.gap=L1, beta.c=b,
it=i, epsilon=epsilon, id.warn=id.warn, U=U)
return(obj)
} #end jump.fit
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