Log-likelihood for exponential k-out-of-n model

Returns a closure function(df, par) that computes the log-likelihood of exponential component rates given system-level data.

Usage

# S3 method for class 'exp_kofn'
loglik(model, ...)

Arguments

model

An exp_kofn object created by kofn().

...

Additional arguments (ignored).

Value

A function function(df, par) where df is a data frame with columns for lifetime, observation type, and (for interval-censored) upper bounds, and par is a numeric vector of m component rates.

Details

For parallel systems (k = m), the closed-form IE expansion is used, supporting all four observation types: exact, right, left, and interval censored. For general k-out-of-n systems, the per-observation contributions are computed via dist.structure::exp_kofn(k, par) and the algebraic.dist generics density, surv, and cdf.

Examples

model <- kofn(k = 3, m = 3, component = dfr_exponential())
#> Error in dfr_exponential(): could not find function "dfr_exponential"
ll <- loglik(model)
#> Error: object 'model' not found
set.seed(1)
df <- rdata(model)(c(1, 2, 3), n = 30)
#> Error: object 'model' not found
ll(df, c(1, 2, 3))
#> Error in ll(df, c(1, 2, 3)): could not find function "ll"