## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

## -----------------------------------------------------------------------------
library(UniLindleyApprox)

# Weibull PDF, CDF, Survival (theta = c(shape, scale))
dweibull_custom <- function(x, theta) dweibull(x, shape = theta[1], scale = theta[2])
pweibull_custom <- function(x, theta) pweibull(x, shape = theta[1], scale = theta[2])
sweibull_custom <- function(x, theta) 1 - pweibull(x, shape = theta[1], scale = theta[2])

# Independent Gamma log-prior for shape and scale
logprior_weibull <- function(theta) {
  if (theta[1] <= 0 || theta[2] <= 0) return(-Inf)
  dgamma(theta[1], shape = 2, rate = 1, log = TRUE) +
    dgamma(theta[2], shape = 2, rate = 1, log = TRUE)
}

# Simulated progressive Type-II data
obs <- c(0.5, 1.2, 1.8, 2.5, 3.1)
R <- c(2, 0, 1, 0, 2)
data_prog <- list(observed = obs, removal_scheme = R, n_total = 10)

fit_weibull <- lindley_fit(
  data = data_prog,
  pdf = dweibull_custom,
  cdf = pweibull_custom,
  survival = sweibull_custom,
  log_prior = logprior_weibull,
  theta0 = c(1.5, 2.0),
  scheme = "progressive_type2",
  loss = "SELF",
  control = lindley.control(verbose = FALSE)
)

summary(fit_weibull)

## -----------------------------------------------------------------------------
dlindley_custom <- function(x, theta) {
  th <- theta[1]
  if (th <= 0 || any(x <= 0)) return(rep(0, length(x)))
  (th^2 / (1 + th)) * (1 + x) * exp(-th * x)
}

plindley_custom <- function(x, theta) {
  th <- theta[1]
  1 - (1 + (th * x) / (1 + th)) * exp(-th * x)
}

slindley_custom <- function(x, theta) 1 - plindley_custom(x, theta)

set.seed(123)
x_lindley <- rexp(40, rate = 1.5)

fit_lindley <- lindley_fit(
  data = x_lindley,
  pdf = dlindley_custom,
  cdf = plindley_custom,
  survival = slindley_custom,
  log_prior = function(th) dgamma(th[1], 2, 1, log = TRUE),
  theta0 = c(1.0),
  scheme = "complete",
  loss = "LINEX",
  control = lindley.control(verbose = FALSE)
)

print(fit_lindley)