#' Binomial mass (univariate, discrete, bounded space)
#'
#' @inherit Density
#' @param theta Either a fixed value or a prior density for the success proportion parameter.
#' @param N An integer with the number of trials (fixed quantity).
#' @family Density
#' @examples
#' # With fixed values for the parameters
#' Binomial(0.5, 10)
#'
#' # With priors for the parameters
#' Binomial(
#' Beta(1, 1), 10
#' )
Binomial <- function(theta = NULL, N = NULL, ordered = NULL, equal = NULL, bounds = list(NULL, NULL),
trunc = list(NULL, NULL), k = NULL, r = NULL, param = NULL) {
DiscreteDensity("Binomial", ordered, equal, bounds, trunc, k, r, param, theta = theta, N = N)
}
#' @keywords internal
#' @inherit constants
constants.Binomial <- function(x) {
sprintf(
"int<lower = 1> N = %s; // number of trials",
x$N
)
}
#' @keywords internal
#' @inherit freeParameters
freeParameters.Binomial <- function(x) {
thetaStr <-
if (is.Density(x$theta)) {
thetaBoundsStr <- make_bounds(x, "theta")
sprintf(
"real%s theta%s%s;",
thetaBoundsStr, get_k(x, "theta"), get_r(x, "theta")
)
} else {
""
}
thetaStr
}
#' @keywords internal
#' @inherit fixedParameters
fixedParameters.Binomial <- function(x) {
thetaStr <-
if (is.Density(x$theta)) {
""
} else {
if (!check_scalar(x$theta)) {
stop("If fixed, theta must be a scalar.")
}
sprintf(
"real theta%s%s = %s;",
get_k(x, "theta"), get_r(x, "theta"), x$theta
)
}
thetaStr
}
#' @keywords internal
#' @inherit generated
generated.Binomial <- function(x) {
sprintf(
"if(zpred[t] == %s) ypred[t][%s] = binomial_rng(N, theta%s%s);",
x$k, x$r,
get_k(x, "theta"), get_r(x, "theta")
)
}
#' @keywords internal
#' @inherit getParameterNames
getParameterNames.Binomial <- function(x) {
return("theta")
}
#' @keywords internal
#' @inherit logLike
logLike.Binomial <- function(x) {
sprintf(
"loglike[%s][t] = binomial_lpmf(y[t] | N, theta%s%s);",
x$k,
get_k(x, "theta"), get_r(x, "theta")
)
}
#' @keywords internal
#' @inherit prior
prior.Binomial <- function(x) {
truncStr <- make_trunc(x, "")
rStr <- make_rsubindex(x)
sprintf(
"%s%s%s ~ binomial(N, %s) %s;",
x$param,
x$k, rStr,
x$theta,
truncStr
)
}
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