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#' @title cumLexc_alphaweibull function
#'
#' @description calculates the cumulative excess hazard from a Weibull distribution
#'
#'
#' @param z_ucured covariates matrix acting on survival function of uncured
#'
#'
#' @param z_pcured covariates matrix acting on cure proportion.
#'
#'
#' @param x the time arguments at which to calculate the cumulative excess hazard
#'
#'
#' @param theta estimated parameters of the cumulative excess hazard from a mixture
#' model using curesurv and uncured survival following a Weibull distribution
#'
#' @param sign_delta only used for mixture cure rate models to specify if the
#' effects or minus the effects of covariates acting on uncured survival to be
#' considered. Default will be sign_delta = "1". The alternative is
#' sign_delta = "-1".
#'
#'
#' @keywords cumLexc_alphaweibull
#'
#' @return This object is a list containing the following components:
#'
#'
#' \item{cumhaz}{cumulative excess hazard estimates}
#' \item{usurv}{survival of uncured}
#' \item{SurvE}{net survival estimates}
#' \item{cured}{cure fraction}
#' \item{ptcure}{the probability Pi(t) of being cured at a given time t after diagnosis knowing that he/she was alive up to time t.}
#'
#' @author Juste Goungounga, Judith Breaud, Olayide Boussari, Laura Botta, Valerie Jooste
#'
#' @keywords internal
cumLexc_alphaweibull <- function(z_ucured = z_ucured, z_pcured = z_pcured,
x = x, theta = theta, sign_delta = 1) {
n_z_pcured <- ncol(z_pcured)
n_z_ucured <- ncol(z_ucured)
if (n_z_pcured > 0 & n_z_ucured > 0 ) {
beta0 <- theta[1]
betak <- theta[2:(1 + n_z_pcured)]
lambda <- theta[(1 + n_z_pcured + 1)]
gamma <- theta[(1 + n_z_pcured + 2)]
delta <-sign_delta*theta[(1 + n_z_pcured + 3):(1 + n_z_pcured + 2 + n_z_ucured)]
pcure <- beta0 + z_pcured %*% betak
cured <- 1/(1 + exp(-pcure))
usurv <- (exp(-exp(lambda)*(x)^exp(gamma)))^exp(z_ucured %*% delta)
uhaz <- exp(gamma)*exp(lambda)*((x)^(exp(gamma) - 1)) * exp(z_ucured %*% delta)
u_f <- uhaz*usurv
SurvE <- cured + (1 - cured)*usurv #SE=cured +(1-cured)Su
cumHazE <- -log(SurvE)
#Excess_haz=[(1-cured)fu(t)]/[cured+(1-cured)Su]
#avec fu = uhaz * usurv
#fu = gamma* lambda*time^(gamma- 1) * exp(-lambda*time^gamma)
#Su= exp(-lamda*time^gamma) et uhaz = gamma* lambda*time^(gamma- 1)
} else if (n_z_pcured > 0 & n_z_ucured == 0 ) {
beta0 <- theta[1]
betak <- theta[2:(1 + n_z_pcured)]
lambda <- theta[(1 + n_z_pcured + 1)]
gamma <- theta[(1 + n_z_pcured + 2)]
delta <-sign_delta*theta[(1 + n_z_pcured + 3):(1 + n_z_pcured + 2 + n_z_ucured)]
pcure <- beta0 + z_pcured %*% betak
cured <- 1/(1 + exp(-pcure))
usurv <- (exp(-exp(lambda)*(x)^exp(gamma)))
uhaz <- exp(gamma)*exp(lambda)*((x)^(exp(gamma) - 1))
u_f <- uhaz*usurv
SurvE <- cured + (1 - cured)*usurv #SE=cured +(1-cured)Su
cumHazE <- -log(SurvE)
#Excess_haz=[(1-cured)fu(t)]/[cured+(1-cured)Su]
#avec fu = uhaz * usurv
#fu = gamma* lambda*time^(gamma- 1) * exp(-lambda*time^gamma)
#Su= exp(-lamda*time^gamma) et uhaz = gamma* lambda*time^(gamma- 1)
} else if (n_z_pcured == 0 & n_z_ucured > 0 ) {
beta0 <- theta[1]
lambda <- theta[(1 + n_z_pcured + 1)]
gamma <- theta[(1 + n_z_pcured + 2)]
delta <-sign_delta* theta[(1 + n_z_pcured + 3):(1 + n_z_pcured + 2 + n_z_ucured)]
pcure <- beta0
cured <- 1/(1 + exp(-pcure))
usurv <- (exp(-exp(lambda)*(x)^exp(gamma)))^exp(z_ucured %*% delta)
uhaz <- exp(gamma)*exp(lambda)*((x)^(exp(gamma) - 1)) * exp(z_ucured %*% delta)
u_f <- uhaz*usurv
SurvE <- cured + (1 - cured)*usurv #SE=cured +(1-cured)Su
cumHazE <- -log(SurvE)
#Excess_haz=[(1-cured)fu(t)]/[cured+(1-cured)Su]
#avec fu = uhaz * usurv
#fu = gamma* lambda*time^(gamma- 1) * exp(-lambda*time^gamma)
#Su= exp(-lamda*time^gamma) et uhaz = gamma* lambda*time^(gamma- 1)
} else if (n_z_pcured == 0 & n_z_ucured == 0 ) {
beta0 <- theta[1]
lambda <- theta[2]
gamma <- theta[3]
pcure <- beta0
cured <- 1/(1 + exp(-pcure))
usurv <- (exp(-exp(lambda)*(x)^exp(gamma)))
uhaz <- exp(gamma)*exp(lambda)*((x)^(exp(gamma) - 1))
u_f <- uhaz*usurv
SurvE <- cured + (1 - cured)*usurv #SE=cured +(1-cured)Su
cumHazE <- -log(SurvE)
}
return(cumHazE)
}
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