flexCPH <-
function (formula = formula(data), data = parent.frame(), subset, na.action, init, control = list()) {
call <- match.call()
m <- match.call(expand.dots = FALSE)
temp <- c("", "formula", "data", "subset", "na.action")
m <- m[match(temp, names(m), nomatch = 0)]
Terms <- if (missing(data)) terms(formula) else terms(formula, data = data)
m$formula <- Terms
m[[1]] <- as.name("model.frame")
m <- eval(m, parent.frame())
if (NROW(m) == 0)
stop("No (non-missing) observations.\n")
con <- list(lng.in.kn = 3, ord = 4, knots = NULL, numeriDeriv = "fd", eps.Hes = 1e-06, parscale = NULL)
con[names(control)] <- control
Y <- model.extract(m, "response")
if (!inherits(Y, "Surv"))
stop("Response must be a survival object.\n")
logT <- log(Y[, 1])
d <- Y[, 2]
attr(Terms, "intercept") <- 1
X <- model.matrix(Terms, m)
X <- X[, -1, drop = FALSE]
type <- attr(Y, "type")
if (type != "right")
stop("flexCPH() supports currently only right-censored data.\n")
if (missing(init))
init <- NULL
out <- flexCPH.fit(logT, d, X, init, con)
out$control <- con
out$terms <- Terms
out$call <- call
class(out) <- "flexCPH"
out
}
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