Masked k-out-of-n log-likelihood — loglik

Computes the log-likelihood for a k-out-of-n system with candidate failed sets (generalized masking). The data frame must contain columns for system lifetime, observation type, and Boolean candidate set indicators (c1, c2, ..., cm).

Usage

loglik_masked(model, candset = "c", ...)

Arguments

model: A kofn model object.
candset: Prefix for candidate set columns (default "c").
...: Additional arguments (currently unused).

Value

A function function(df, par) returning a scalar log-likelihood.

Details

At system failure, k components have failed. The candidate set C_i is a superset of the true failed set. The likelihood marginalizes over all \(\binom{|C_i|}{k}\) possible k-subsets.

For series systems (k = 1), this reduces to the standard masked cause-of-failure likelihood \(\sum_{j \in C_i} w_j(t_i)\). For parallel systems (k = m), the candidate set must be {1, ..., m} and the likelihood equals the system density.

The function uses the exponential or Weibull distribution functions directly (not the IE expansion), so it works for any family supported by parse_params.

Examples

# 2-out-of-4 system with candidate failed sets
model <- kofn(k = 2, m = 4, component = dfr_exponential())
#> Error in dfr_exponential(): could not find function "dfr_exponential"
ll <- loglik_masked(model)
#> Error: object 'model' not found

# Manually construct masked data: k=2 failed, C = {1,2,3}
df <- data.frame(
  t = 1.5, omega = "exact",
  c1 = TRUE, c2 = TRUE, c3 = TRUE, c4 = FALSE
)
ll(df, c(1, 0.8, 0.6, 0.4))
#> Error in ll(df, c(1, 0.8, 0.6, 0.4)): could not find function "ll"