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#' Simulate `size` samples from a zero-truncated non homogeneous Poisson Point Process (zt-NHPPP) from
#' (t0, t_max) (thinning method)
#'
#' @description Sample zero-truncated NHPPP intensity times using the thinning method
#'
#' @param lambda (function) the instantaneous rate of the NHPPP.
#' @param majorizer_intercept (double) the intercept (`alpha`) of the [log]linear majorizer function.
#' @param majorizer_slope (double) the slope (`beta') of the [log]linear majorizer function.
#' @param t_min (double) the lower bound of the time interval.
#' @param t_max (double) the upper bound of the time interval.
#' @param majorizer_is_loglinear (boolean) if `TRUE` the majorizer is loglinear `exp(alpha + beta * t)`
#' @param atmost1 boolean, draw at most 1 event time
#'
#' @return a vector of at least 1 event times
#' @keywords internal
ztdraw_intensity_line <- function(lambda,
majorizer_intercept,
majorizer_slope,
t_min,
t_max,
majorizer_is_loglinear = FALSE,
atmost1 = FALSE) {
if (isTRUE(majorizer_is_loglinear)) {
ztnhppp_t <- ztdraw_sc_loglinear
link <- exp
} else {
ztnhppp_t <- ztdraw_sc_linear
link <- identity
}
while (TRUE) {
candidate_times <- ztnhppp_t(intercept = majorizer_intercept, slope = majorizer_slope, t_min = t_min, t_max = t_max, atmost1 = FALSE)
u <- stats::runif(n = length(candidate_times), min = 0, max = 1)
acceptance_prob <- lambda(candidate_times) / link(majorizer_intercept + majorizer_slope * candidate_times)
if (!all(acceptance_prob <= 1 + 10^-6)) stop("lambda > lambda_maj\n")
candidate_times <- candidate_times[u < acceptance_prob]
if (length(candidate_times) > 0) {
if (atmost1) {
return(candidate_times[1])
} else {
return(candidate_times)
}
}
}
}
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