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step.glm.fit<-function(y, x.lin, Xtrue, PSI, ww, offs, opz, return.all.sol=FALSE){
#----------------------
search.min<-function(h, psi, psi.old, X, y, w, offs, id.fix.psi=NULL) {
psi.ok<- psi*h + psi.old*(1-h)
psi.ok[id.fix.psi]<- psi.old[id.fix.psi]
PSI <- matrix(rep(psi.ok, rep(n, length(psi.ok))), ncol = length(psi.ok))
U1 <- (Xtrue>PSI) #(Z - PSI) * (Z > PSI)
#if (pow[1] != 1) U1 <- U1^pow[1]
obj1 <- try(suppressWarnings(glm.fit(x = cbind(X, U1), y = y, offset = offs,
weights = w, family = fam, control = glm.control(maxit = maxit.glm1[i]), etastart = eta0)),
silent = TRUE)
L1 <- if (class(obj1)[1] == "try-error") L0 + 10 else obj1$dev
attr(L1, "eta") <- obj1$linear.predictor
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){
# x1<-x*sqrt(w)
# y<-y-offs
# y1<-y*sqrt(w)
# b<-drop(solve(crossprod(x1),crossprod(x1,y1)))
# fit<-drop(tcrossprod(x,t(b)))
# r<-y-fit
# o<-list(coefficients=b,fitted.values=fit,residuals=r, df.residual=length(y)-length(b))
# o
# }
#-----------
adj.psi <- function(psii, LIM) {
pmin(pmax(LIM[1, ], psii), LIM[2, ])
}
#------------
#-----------
fam<-opz$fam
maxit.glm<-opz$maxit.glm
#--------------
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
#limZ <- apply(Xtrue, 2, quantile, names = FALSE, probs = c(alpha[1], alpha[2]))
limZ <- if(is.null(opz$limZ)) apply(Xtrue, 2, quantile, names=FALSE, probs=alpha) else opz$limZ
fix.npsi<-opz$fix.npsi
agg<-opz$agg
hh <-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)
# 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()
psi.values[[length(psi.values) + 1]] <- NA
#PSI0<- matrix(psi0, n, npsi, byrow = TRUE)
XREG <- cbind(x.lin, Xtrue>PSI)
if(it.max==0){
obj <- suppressWarnings(glm.fit(x = XREG, y = y, offset = offs,
weights = ww, family = fam))
L1 <- obj$dev
obj$epsilon <- epsilon
idZ<-(plin+1):(plin+ncol(PSI))
b<- obj$coef[idZ]
obj <- list(obj = obj, psi = PSI[1,], psi.values = psi.values,
rangeZ = rangeZ, beta.c=b, epsilon = epsilon,
SumSquares.no.gap = L1,
id.warn = TRUE)
return(obj)
}
if(!opz$usestepreg){
dev.values[length(dev.values) + 1] <- opz$dev0 #modello senza psi
psi.values[[length(psi.values) + 1]] <- NA #nessun psi
}
if(is.null(opz$fit.psi0)){
obj <- suppressWarnings(glm.fit(x = XREG, y = y, offset = offs,
weights = ww, family = fam, etastart=opz$eta0))
L0 <- obj$dev
eta0 <- obj$linear.predictors
} else {
L0 <- opz$fit.psi0$L0
eta0 <- opz$fit.psi0$eta0
}
n.intDev0<-nchar(strsplit(as.character(L0),"\\.")[[1]][1])
#dev.values[length(dev.values) + 1] <- dev0#opz$dev0 #del modello iniziale (senza psi)
dev.values[length(dev.values) + 1] <- L0 #modello con psi iniziali
psi0<-PSI[1,]
psi.values[[length(psi.values) + 1]] <- psi0 #psi iniziali
if(is.null(maxit.glm)){
Nboot <- if(is.null(opz$Nboot)) 0 else opz$Nboot
maxit.glm1 <- rep(1:it.max + Nboot, 1:it.max+1) #2*rep(1:it.max, 1:it.max)
maxit.glm1 <- pmin(maxit.glm1, 25)
} else {
maxit.glm1 <- rep(maxit.glm, it.max)
}
#==============================================
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[,unique(colnames(Xtrue)),drop=FALSE], 2, min)
up <- apply(Xtrue[,unique(colnames(Xtrue)),drop=FALSE], 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$tol.opt, it.max)
#==============================================
idZ<-(plin+1):(plin+ncol(PSI))
idW<-(plin+ncol(PSI)+1): ( plin+2*ncol(PSI))
while (abs(epsilon) > tol) {
i <- i + 1
#if(i==1) browser()
xx <- Xtrue[,cumsum(npsii),drop=FALSE]
for (p in 1:P) {
psis <- sort(psi0[pos[[p]]])
gruppi <- cut(xx[,p], breaks = c(low[p] - 0.1, psis, up[p]), labels = FALSE)
if(any(is.na(gruppi))) stop(paste("too many breaks for step term #", p, "?"), call.=TRUE)
points <- c(low[p], psis, up[p])
right <- c(low[p], points[2:(npsii[p] + 1)] + agg[pos[[p]]][order(psi0[pos[[p]]])] * (points[3:(npsii[p] + 2)] - points[2:(npsii[p] + 1)]), NA)
left <- c(NA, points[2:(npsii[p] + 1)] - agg[pos[[p]]][order(psi0[pos[[p]]])] * (points[2:(npsii[p] + 1)] - points[1:npsii[p]]), up[p])
#if(any(is.na(left))| any(is.na(right))) stop(paste("too many breaks for step term #", p, "?"), call.=TRUE)
for (j in 1:(npsii[p] + 1)) {
xx.j <- xx[,p][gruppi == j]
xx[,p][gruppi == j] <- right[j] + (xx.j - points[j]) *
((left[j + 1] - right[j])/(points[j + 1] - points[j]))
}
}
XX<-toMatrix(xx, npsii)
PSI<- matrix(psi0, n, npsi, byrow = TRUE)
W <- (1/(2 * abs(XX - PSI)))
Z <- (XX * W + 1/2)
XREG <- cbind(x.lin, Z, W)
#obj<-try(mylm(XREG,y,w=ww,offs=offs), silent = TRUE)
#if(class(obj)[1]=="try-error")
# obj <- lm.wfit(y = y, x = XREG, offset = offs, w=ww )
#b <- obj$coef[(2:(sum(k) + 1))]
#g <- obj$coef[((sum(k) + 2):(2 * sum(k) + 1))]
obj <- suppressWarnings(glm.fit(x = XREG, y = y, offset = offs,
weights = ww, family = fam, control = glm.control(maxit = maxit.glm1[i]), etastart = eta0))
#idZ<-(plin+1):(plin+ncol(Z))
#idW<-(plin+ncol(Z)+1): ( plin+ncol(Z)+ncol(W))
b<- obj$coef[idZ]
g<- obj$coef[idW]
if(any(is.na(c(b, g)))){
if(return.all.sol) return(list(dev.values, psi.values)) else stop("breakpoint estimate too close or at the boundary causing NA estimates.. too many breakpoints being estimated?", call.=FALSE)
}
psi1 <- -g/b
psi1<- psi0+ opz$h*(psi1-psi0)
#aggiusta la stima di psi..
psi1<- adj.psi(psi1, limZ)
psi1<-unlist(tapply(psi1, opz$id.psi.group, sort), use.names =FALSE)
#if(i==1) browser()
#la f e' chiaramente a gradino per cui meglio dividere..
a0<-optimize(search.min, c(0,.5), psi=psi1, psi.old=psi0, X=x.lin, y=y, w=ww, offs=offs, tol=tolOp[i])
a1<-optimize(search.min, c(.5,1), psi=psi1, psi.old=psi0, X=x.lin, y=y, w=ww, offs=offs, tol=tolOp[i])
a <-if(a0$objective<=a1$objective) a0 else a1
#a0<-optimize(search.min, c(0,.33), psi=psi1, psi.old=psi0, X=x.lin, y=y, w=ww, offs=offs)
#a1<-optimize(search.min, c(.33,.66), psi=psi1, psi.old=psi0, X=x.lin, y=y, w=ww, offs=offs)
#a2<-optimize(search.min, c(.66,1), psi=psi1, psi.old=psi0, X=x.lin, y=y, w=ww, offs=offs)
#a<-if(a2$objective<=a$objective) a2 else a
if(a$objective<L0){
k.values[length(k.values) + 1] <- use.k <- a$minimum
L1<- a$objective
eta0<- attr(a$objective, "eta")
} else {
k.values[length(k.values) + 1] <- use.k <- 0
L1<- L0
}
if(use.k<=.01){
k.List<-j.List<-NULL
for(j in 1:length(psi1)){
a0<-optimize(search.min, c(0,.5), psi=psi1, psi.old=psi0, X=x.lin, y=y, w=ww, offs=offs, id.fix.psi=j, tol=tolOp[i])
a1<-optimize(search.min, c(.5,1), psi=psi1, psi.old=psi0, X=x.lin, y=y, w=ww, offs=offs, id.fix.psi=j, tol=tolOp[i])
a <-if(a0$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$minimum
} else {
j.List[[j]]<-NA
k.List[[j]]<-NA
}
}
id.to.be.changed<- unique(unlist(j.List[!sapply(k.List, is.na)]))
if(!is.null(id.to.be.changed)){
use.k<-rep(0,length(psi1))
use.k[id.to.be.changed] <-mean(unlist(k.List[!sapply(k.List, is.na)]))
psi1 <- psi1*use.k + psi0* (1-use.k)
use.k<-mean(use.k)
L1=search.min(1, psi=psi1, psi.old=psi0, X=x.lin, y=y, w=ww, offs=offs)
} else {
psi1<-psi0
}
} else {
psi1 <- psi1*use.k + psi0* (1-use.k)
}
if (!is.null(digits)) psi1 <- round(psi1, digits)
#PSI1 <- matrix(psi1, n, npsi, byrow = TRUE)
#XREG1 <- cbind(x.lin, Xtrue>PSI1)
#obj1 <- try(mylm(XREG1, y, ww, offs), silent = TRUE)
#if (class(obj1)[1] == "try-error") obj1 <- try(lm.wfit(XREG1, y, ww, offs), silent = TRUE)
delta<- psi1-psi0
if (display) {
flush.console()
#n.intDev0<-nchar(strsplit(as.character(dev.values[2]),"\\.")[[1]][1])
unlpsi<- unlist(psi1)
Lp<-length(unlpsi)
cat(paste("iter = ", sprintf("%2.0f",i),
#" dev = ", sprintf(paste("%", n.intDev0+6, ".5f",sep=""), L1), #formatC(L1,width=8, digits=5,format="f"), #era format="fg"
" dev = ", sprintf("%1.5f", as.numeric(strsplit(format(L1, scientific=TRUE), "e")[[1]][1])),
" k = ", sprintf("%2.3f", use.k),
" n.psi = ",formatC(Lp,digits=0,format="f"),
" est.psi = ",paste(formatC(unlpsi[1:min(Lp,5)],digits=3,format="f"), collapse=" "), #sprintf('%.2f',x)
sep=""), "\n")
}
epsilon <- (L0 - L1)/(abs(L0) + 0.1)
L0<-L1
k.values[length(k.values)+1]<-use.k
psi.values[[length(psi.values) + 1]] <- psi1
dev.values[length(dev.values) + 1] <- L0
if (i >= it.max) {
id.warn <- TRUE
break
}
psi0<-psi1
} #end while_it
#browser()
psi1 <-unlist(tapply(psi1, opz$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, eta0=eta0)
return(obj)
} #end jump.fit
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