1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
|
broken.line<-function(ogg, term=NULL, link=TRUE, interc=TRUE, se.fit=TRUE, isV=FALSE, .vcov=NULL, .coef=NULL, ...){
#ogg: l'oggetto segmented
#term: una lista *nominata* con i valori rispetto a cui calcolare i fitted
# OPPURE una stringa per indicare la variabile segmented OPPURE NULL (se c'e' solo una variabile)
#is: 2 valori T/F per indicare se le variabili U e V nella matrice X, andrebbero sostituite con le versioni ind-smooth prima di calcolare var(X\hat\beta)
#...: argomenti da passare a vcov.segmented(): per esempio var.diff, is, p.df
if(length(isV)==1) isV<-c(FALSE,isV)
dummy.matrix<-NULL
dummy.matrix<-function(x.values, x.name, obj.seg, psi.est=TRUE, isV=FALSE, .coef=NULL){
#given the segmented fit 'obj.seg' and a segmented variable x.name with corresponding values x.values,
#this function simply returns a matrix with columns (x, (x-psi)_+, -b*I(x>psi))
#or ((x-psi)_+, -b*I(x>psi)) if obj.seg does not include the coef for the linear "x"
f.U<-function(nomiU, term=NULL){
#trasforma i nomi dei coeff U (o V) nei nomi delle variabili corrispondenti
#and if 'term' is provided (i.e. it differs from NULL) the index of nomiU matching term are returned
k<-length(nomiU)
nomiUsenzaU<-strsplit(nomiU, "\\.")
nomiU.ok<-vector(length=k)
for(i in 1:k){
nomi.i<-nomiUsenzaU[[i]][-1]
if(length(nomi.i)>1) nomi.i<-paste(nomi.i,collapse=".")
nomiU.ok[i]<-nomi.i
}
if(!is.null(term)) nomiU.ok<-(1:k)[nomiU.ok%in%term]
return(nomiU.ok)
}
estcoef <- if(is.null(.coef)) coef(obj.seg) else .coef
if(length(isV)==1) isV<-c(FALSE,isV)
n<-length(x.values)
#le seguenti righe selezionavano (ERRONEAMENTE) sia "U1.x" sia "U1.neg.x" (se "x" e "neg.x" erano segmented covariates)
#nameU<- grep(paste("\\.",x.name,"$", sep=""), obj.seg$nameUV$U, value = TRUE)
#nameV<- grep(paste("\\.",x.name,"$", sep=""), obj.seg$nameUV$V, value = TRUE)
nameU<-obj.seg$nameUV$U[f.U(obj.seg$nameUV$U,x.name)]
nameV<-obj.seg$nameUV$V[f.U(obj.seg$nameUV$V,x.name)]
#browser()
if(is.null(obj.seg$constr)){
diffSlope<-estcoef[nameU]
} else {
diffSlope<-drop(obj.seg$constr$invA.RList[[match(x.name, obj.seg$nameUV$Z)]]%*%estcoef[nameU])[-1]
}
est.psi<-obj.seg$psi[nameV, "Est."]
se.psi<-obj.seg$psi[nameV, "St.Err"]
if(any(is.na(se.psi))) stop("The St.Err. of psi is NA", call. = FALSE)
k<-length(est.psi)
PSI <- matrix(rep(est.psi, rep(n, k)), ncol = k)
SE.PSI <- matrix(rep(se.psi, rep(n, k)), ncol = k)
newZ<-matrix(x.values, nrow=n,ncol=k, byrow = FALSE)
dummy1<-if(isV[1]) (newZ-PSI)*pnorm((newZ-PSI)/SE.PSI) else (newZ-PSI)*(newZ>PSI) #pmax(newZ-PSI,0)
if(psi.est){
V<-if(isV[2]) -pnorm((newZ-PSI)/SE.PSI) else -(newZ>PSI) #ifelse(newZ>PSI,-1,0)
dummy2<- if(k==1) V*diffSlope else V%*%diag(diffSlope) #t(diffSlope*t(-I(newZ>PSI)))
colnames(dummy2)<- nameV
newd<-cbind(x.values,dummy1,dummy2)
colnames(newd)<-c(x.name,sub("psi","U", nameV), nameV)
#colnames(newd)[1]<- x.name
#colnames(newd)<-c(x.name,nameU, nameV)
} else {
newd<-cbind(x.values,dummy1)
colnames(newd)<-c(x.name, sub("psi","U", nameV))
#colnames(newd)[1]<- x.name
#colnames(newd)<-c(x.name,nameU)
}
#if(!x.name%in%names(estcoef)) newd<-newd[,-1,drop=FALSE]
#aggiungi (eventualmente) le colonne relative ai psi noti
all.psi<-obj.seg$indexU[[x.name]]
if(length(all.psi)!=k){
nomi.psi.noti<-setdiff(names(all.psi),nameU)
psi.noti<-setdiff(all.psi, est.psi)
PSI.noti <- matrix(rep(psi.noti, rep(n, length(psi.noti))), ncol = length(psi.noti))
nomi<-c(colnames(newd),nomi.psi.noti)
newZ<-matrix(newZ, nrow=nrow(newZ), ncol=length(psi.noti))
newd<-cbind(newd, (newZ-PSI.noti)*(newZ>PSI.noti))
colnames(newd)<-nomi
}
rownames(newd)<-NULL
return(newd)
} #end dummy.matrix()
#--------------
blockdiag <- function(...) {
args <- list(...)
nc <- sapply(args,ncol)
cumnc <- cumsum(nc)
## nr <- sapply(args,nrow)
## NR <- sum(nr)
NC <- sum(nc)
rowfun <- function(m,zbefore,zafter) {
cbind(matrix(0,ncol=zbefore,nrow=nrow(m)),m,
matrix(0,ncol=zafter,nrow=nrow(m)))
}
ret <- rowfun(args[[1]],0,NC-ncol(args[[1]]))
for (i in 2:length(args)) {
ret <- rbind(ret,rowfun(args[[i]],cumnc[i-1],NC-cumnc[i]))
}
ret
}
#--------------
f.U<-function(nomiU, term=NULL){
#trasforma i nomi dei coeff U (o V) nei nomi delle variabili corrispondenti
#and if 'term' is provided (i.e. it differs from NULL) the index of nomiU matching term are returned
k<-length(nomiU)
nomiUsenzaU<-strsplit(nomiU, "\\.")
nomiU.ok<-vector(length=k)
for(i in 1:k){
nomi.i<-nomiUsenzaU[[i]][-1]
if(length(nomi.i)>1) nomi.i<-paste(nomi.i,collapse=".")
nomiU.ok[i]<-nomi.i
}
if(!is.null(term)) nomiU.ok<-(1:k)[nomiU.ok%in%term]
return(nomiU.ok)
}
#-------------
estcoef<- if(is.null(.coef)) coef(ogg) else .coef
if(se.fit) {
covv<- if(is.null(.vcov)) vcov.segmented(ogg, ...) else .vcov
#---Dalla versione 1.2.0 (20/06/20) ho eliminato il controllo sotto per consentire l'utilizzo
#----di modelli che restituivano una cov con dimensione diversa dal numero dei coeff lineari (ad es., censReg)
#if(!all(dim(.vcov)==c(length(ogg$coef), length(ogg$coef)))) stop("Incorrect dimension of cov matrix", call. = FALSE)
if(!all(dim(covv)==c(length(estcoef), length(estcoef)))) stop("dimension of cov matrix and estimated coeffs do not match", call. = FALSE)
}
#browser()
nomeZ <- ogg$nameUV$Z
if(is.null(term)){
term <- nomeZ[1]
xvalues<-ogg$model[term]
} else {
if(is.character(term)) term<- ogg$model[term]
if(!is.list(term)) stop("term should be a named list")
if(!names(term)%in%nomeZ) stop("term is not a segmented variable")
xvalues<-term
term<-names(term)
}
n.seg<-1
# if(is.null(xvalues)){
# if(n.seg>1) stop("there are multiple segmented covariates. Please specify one.")
# xvalues<-ogg$model[nomeZ]
# }
# if(is.character(xvalues)){
# if(!xvalues %in% nomeZ) stop("'xvalues' is not a segmented covariate")
# xvalues<-ogg$model[xvalues]
# }
# nomeOK<-names(xvalues)
# if(length(nomeOK)>1) stop("Please specify one variable")
# if(!nomeOK %in% nomeZ) stop("'names(xvalues)' is not a segmented covariate")
nomi <- names(estcoef)
#nomiSenzaV <- nomiSenzaU <- nomi
#nomiSenzaU[match(nomeU, nomi)] <- ""
#nomiSenzaV[match(nomeV, nomi)] <- ""
idInterc<-grep("ntercept",names(estcoef))
ste.fit<-fit <- vector(mode = "list", length = 1)
n.seg<-1
#browser()
ind <- match(c(term,ogg$nameUV$U[grep(term, ogg$nameUV$U)]), nomi, 0)
ind<-ind[ind!=0]
indV <- match(c(ogg$nameUV$V[grep(term, ogg$nameUV$V)]), nomi, 0)
#Xfit<-dummy.matrix(unlist(xvalues), term, ogg, isV=FALSE, .coef=estcoef)
#if(se.fit)
X<-dummy.matrix(unlist(xvalues), term, ogg, isV=isV, .coef=estcoef)
#browser()
if(is.null(ogg$constr)){
cof <- estcoef[ind]
if(!term%in%names(estcoef)) X <-X[,-1,drop=FALSE]
} else {
#idU.i <- match(nomeU.i, names(estcoef))
cof<-drop(ogg$constr$invA.RList[[match(term, ogg$nameUV$Z)]]%*%estcoef[ind])
names(cof)<-c(term, paste("U",1:(length(cof)-1),".",term,sep="" ))
#estcoef<-append(estcoef[-ind], cof, after=ind[1]-1)
}
idV <- match(grep(term, ogg$nameUV$V, value = TRUE),colnames(X))
Xfit <- X[, -idV, drop=FALSE]
fit<-drop(Xfit%*%cof)
if(interc && length(idInterc)==1){
fit <- fit + estcoef[idInterc]
#if(se.fit)
X<-cbind(1,X)
ind <- c(idInterc, ind)
}
#browser()
if(se.fit) {
V <- covv[c(ind, indV), c(ind, indV)]
if(!is.null(ogg$constr)){
B <- ogg$constr$invA.RList[[match(term, ogg$nameUV$Z)]]
B <- do.call(blockdiag, list(diag(interc), B, diag(length(indV))))
V <- B %*% V %*% t(B)
}
#else {
# V <- vcov(object)
# X <- X[,colnames(V)]
#}
ste.fit <- sqrt(rowSums((X %*% V) * X)) #sqrt(diag(X%*%Var%*%t(X)))
if(inherits(ogg, what = "glm", FALSE) && !link) {
ste.fit <- ogg$family$mu.eta(fit)*ste.fit
fit <- ogg$family$linkinv(fit)
}
fit<-list(fit=fit, se.fit=ste.fit)
} else {
if(inherits(ogg, what = "glm", FALSE) && !link) fit <- ogg$family$linkinv(fit)
fit<-list(fit=fit)
}
return(fit)
}
|
