#############################################################
#Reference Class definition
#############################################################
#' @rdname displ
#' @aliases conexp-class conexp
#' @exportClass conexp
#' @importFrom methods new
#' @importFrom stats dexp pexp
#' @export conexp
conexp =
setRefClass("conexp",
contains = "ctn_distribution",
fields = list(
dat = function(x) {
if (!missing(x) && !is.null(x)) {
check_ctn_data(x)
d = sort(x)
internal[["cum_n"]] <<- rev(seq_along(d))
internal[["dat"]] <<- d
xmin <<- d[1]
} else internal[["dat"]]
},
xmin = function(x) {
if (!missing(x) && !is.null(x)) {
if ("estimate_xmin" %in% class(x)) {
pars <<- x$pars
x = x$xmin
}
internal[["xmin"]] <<- x
if (length(internal[["dat"]])) {
selection = min(which(internal[["dat"]] >= (x - .Machine$double.eps ^ 0.5)))
internal[["n"]] <<- internal[["cum_n"]][selection]
}
} else internal[["xmin"]]
},
pars = function(x) {
if (!missing(x) && !is.null(x)) {
if ("estimate_pars" %in% class(x)) x = x$pars
internal[["pars"]] <<- x
} else internal[["pars"]]
}
)
)
#############################################################
#Initialisation
#############################################################
conexp$methods(
list(
initialize = function(dat) {
no_pars <<- 1
##Use the internal attribute for copying
if (!missing(dat)) {
check_ctn_data(dat)
d = sort(dat)
internal[["cum_n"]] <<- rev(seq_along(d))
internal[["dat"]] <<- d
xmin <<- d[1]
}
}
)
)
#############################################################
#PDF method
#############################################################
#' @rdname dist_pdf-methods
#' @aliases dist_pdf,conexp-method
setMethod("dist_pdf",
signature = signature(m = "conexp"),
definition = function(m, q = NULL, log = FALSE) {
xmin = m$getXmin(); pars = m$getPars()
if (is.null(q)) q = m$dat
pdf = dexp(q, pars, log = TRUE) - pexp(xmin, pars, lower.tail = FALSE, log.p = TRUE)
if (!log) {
pdf = exp(pdf)
pdf[q < xmin] = 0
} else {
pdf[q < xmin] = -Inf
}
pdf
}
)
#############################################################
#CDF method
#############################################################
#' @rdname dist_cdf-methods
#' @aliases dist_cdf,conexp-method
setMethod("dist_cdf",
signature = signature(m = "conexp"),
definition = function(m, q = NULL, lower_tail = TRUE) {
pars = m$pars; xmin = m$xmin
if (is.null(pars)) stop("Model parameters not set.")
if (is.null(q)) q = m$dat
if (lower_tail) {
p = pexp(q, pars, lower.tail = lower_tail)
C = pexp(xmin, pars, lower.tail = FALSE)
cdf = (p / C - 1 / C + 1)
} else {
log_p = pexp(q, pars, lower.tail = FALSE, log.p = TRUE)
log_C = pexp(xmin, pars, lower.tail = FALSE, log.p = TRUE)
cdf = exp(log_p - log_C)
}
cdf[q < xmin] = 0
cdf
}
)
#' @rdname dist_cdf-methods
#' @aliases dist_all_cdf,conexo-method
setMethod("dist_all_cdf",
signature = signature(m = "conexp"),
definition = function(m, lower_tail = TRUE, xmax = 1e5) {
xmin = m$getXmin()
xmax = min(max(m$dat), xmax)
dist_cdf(m, q = xmin:xmax, lower_tail = lower_tail)
}
)
#############################################################
#ll method
#############################################################
#' @rdname dist_ll-methods
#' @aliases dist_ll,conexp-method
setMethod("dist_ll",
signature = signature(m = "conexp"),
definition = function(m) {
n = m$internal[["n"]]
q = m$dat
N = length(q)
q = q[(N - n + 1):N]
conexp_tail_ll(q, m$getPars(), m$getXmin())
}
)
########################################################
#Log-likelihood
########################################################
conexp_tail_ll = function(x, rate, xmin) {
n = length(x)
joint_prob = colSums(
matrix(## Needed for edge cases
sapply(rate, function(i) dexp(x, i, log = TRUE)), nrow = length(x)))
prob_over = sapply(rate,
function(i)
pexp(xmin, i,
lower.tail = FALSE, log.p = TRUE))
return(joint_prob - n * prob_over)
}
########################################################
#Rand number generator
########################################################
#' @rdname dist_rand-methods
#' @aliases dist_rand,conexp-method
setMethod("dist_rand",
signature = signature(m = "conexp"),
definition = function(m, n = "numeric") {
## Rearrange the usual formula for generating
## exp random numbers: -log(u)/lambda > xmin
u = runif(n, 0, exp(-m$pars * m$xmin))
-log(u) / m$pars
}
)
#############################################################
#MLE method
#############################################################
conexp$methods(
mle = function(set = TRUE, initialise = NULL) {
x = dat
x = x[x > xmin]
if (is.null(initialise))
theta_0 = mean(x)
else
theta_0 = initialise
# Chop off values below
negloglike = function(par) {
r = -conexp_tail_ll(x, par, xmin)
if (!is.finite(r)) r = 1e12
r
}
mle = suppressWarnings(optim(par = theta_0, fn = negloglike,
method = "L-BFGS-B", lower = 0))
if (set)
pars <<- mle$par
class(mle) = "estimate_pars"
names(mle)[1L] = "pars"
mle
}
)
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