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# SCCS @(#)coxph.fit.s 5.8 06/24/99
coxph.fit <- function(x, y, strata, offset, init, control,
weights, method, rownames)
{
n <- nrow(y)
if (is.matrix(x))
nvar <- ncol(x)
else
if (length(x)==0)
nvar <-0
else
nvar <-1
time <- y[,1]
status <- y[,2]
# Sort the data (or rather, get a list of sorted indices)
if (length(strata)==0) {
sorted <- order(time)
newstrat <- as.integer(rep(0,n))
}
else {
sorted <- order(strata, time)
strata <- (as.numeric(strata))[sorted]
newstrat <- as.integer(c(1*(diff(strata)!=0), 1))
}
if (missing(offset) || is.null(offset)) offset <- rep(0,n)
if (missing(weights)|| is.null(weights))weights<- rep(1,n)
else {
if (any(weights<=0)) stop("Invalid weights, must be >0")
weights <- weights[sorted]
}
stime <- as.double(time[sorted])
sstat <- as.integer(status[sorted])
if (nvar==0) {
# A special case: Null model.
# (This is why I need the rownames arg- can't use x' names)
# Set things up for 0 iterations on a dummy variable
x <- as.matrix(rep(1.0, n))
nullmodel <- TRUE
nvar <- 1
init <- 0
maxiter <- 0
}
else {
nullmodel <- FALSE
maxiter <- control$iter.max
if (!missing(init) && !is.null(init)) {
if (length(init) != nvar) stop("Wrong length for inital values")
}
else init <- rep(0,nvar)
}
print("before coxfit2:")
print(x);
coxfit <- .C("coxfit2", iter=as.integer(maxiter),
as.integer(n),
as.integer(nvar), stime,
sstat,
x= x[sorted,] ,
as.double(offset[sorted] - mean(offset)),
as.double(weights),
newstrat,
means= double(nvar),
coef= as.double(init),
u = double(nvar),
imat= double(nvar*nvar), loglik=double(2),
flag=integer(1),
double(2*n + 2*nvar*nvar + 3*nvar),
as.double(control$eps),
as.double(control$toler.chol),
sctest=as.double(method=="efron")
,PACKAGE="survival")
if (nullmodel) {
score <- exp(offset[sorted])
coxres <- .C("coxmart", as.integer(n),
as.integer(method=='efron'),
stime,
sstat,
newstrat,
as.double(score),
as.double(weights),
resid=double(n),
PACKAGE="survival")
resid <- double(n)
resid[sorted] <- coxres$resid
names(resid) <- rownames
list( loglik = coxfit$loglik[1],
linear.predictors = offset,
residuals = resid,
method= c('coxph.null', 'coxph') )
}
else {
var <- matrix(coxfit$imat,nvar,nvar)
coef <- coxfit$coef
if (coxfit$flag < nvar) which.sing <- diag(var)==0
else which.sing <- rep(FALSE,nvar)
infs <- abs(coxfit$u %*% var)
if (maxiter >1) {
if (coxfit$flag == 1000)
warning("Ran out of iterations and did not converge")
else {
infs <- ((infs > control$eps) &
infs > control$toler.inf*abs(coef))
if (any(infs))
warning(paste("Loglik converged before variable ",
paste((1:nvar)[infs],collapse=","),
"; beta may be infinite. "))
}
}
names(coef) <- dimnames(x)[[2]]
lp <- c(x %*% coef) + offset - sum(coef*coxfit$means)
score <- exp(lp[sorted])
coxres <- .C("coxmart", as.integer(n),
as.integer(method=='efron'),
stime,
sstat,
newstrat,
as.double(score),
as.double(weights),
resid=double(n),
PACKAGE="survival")
resid <- double(n)
resid[sorted] <- coxres$resid
names(resid) <- rownames
coef[which.sing] <- NA
list(coefficients = coef,
var = var,
loglik = coxfit$loglik,
score = coxfit$sctest,
iter = coxfit$iter,
linear.predictors = as.vector(lp),
residuals = resid,
means = coxfit$means,
method='coxph')
}
}
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