Log-likelihood for Scheme 1 (periodic inspection) parallel system

Returns a closure that computes the log-likelihood under Scheme 1 observation. The likelihood combines the system density at the exact system failure time with interval-censored component contributions.

Usage

loglik_scheme1(model, ...)

Arguments

model: A kofn model object (exponential or Weibull).
...: Additional arguments (currently unused).

Value

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

Details

The log-likelihood for observation i is: $$\log L_i(\theta) = \log f_{sys}(t_i) + \sum_j \log[F_j(a_{ij}^+) - F_j(a_{ij}^-)]$$

where $f_{sys}$ is the parallel system density and $[a_{ij}^-, a_{ij}^+)$ is the inspection interval containing component j's failure time.

Examples

model <- kofn(k = 2, m = 2, component = dfr_exponential())
#> Error in dfr_exponential(): could not find function "dfr_exponential"
ll <- loglik_scheme1(model)
#> Error: object 'model' not found
set.seed(1)
df <- rdata_scheme1(model)(c(1, 2), n = 30, delta = 1.0)
#> Error: object 'model' not found
ll(df, c(1, 2))
#> Error in ll(df, c(1, 2)): could not find function "ll"