Sample component lifetimes from a system

Generates an \(n \times m\) matrix where column \(j\) contains independent samples from component \(j\)'s lifetime distribution. The system lifetime is the row-wise minimum.

Usage

sample_components(x, n, ...)

# S3 method for class 'dfr_dist_series'
sample_components(x, n, par = NULL, ...)

Arguments

x

A system object (e.g., dfr_dist_series).

n

Number of samples (rows).

...

Additional arguments passed to methods.

par

Optional parameter vector override.

Value

An \(n \times m\) numeric matrix of component lifetimes, with columns named comp1, comp2, etc.

Details

Each column is sampled independently using the component's own sampler. Since the series system fails when any component fails, the system lifetime for each observation is:

t_sys <- apply(mat, 1, min)

The failing component for each observation can be identified via:

failing <- apply(mat, 1, which.min)

This enables failure attribution analysis: what proportion of system failures are caused by each component?

Methods (by class)

• sample_components(dfr_dist_series): Sample component lifetimes from a series system. Returns an n x m matrix where column j holds samples from component j. The system lifetime is apply(mat, 1, min).

See also

sampler for system-level sampling, component to extract individual component objects, dfr_dist_series for the constructor

Other system introspection: component(), component_hazard(), ncomponents(), param_layout()

Examples

# \donttest{
library(flexhaz)

sys <- dfr_dist_series(list(
    dfr_exponential(0.1),
    dfr_exponential(0.2),
    dfr_exponential(0.3)
))

set.seed(42)
mat <- sample_components(sys, n = 1000)
dim(mat)  # 1000 x 3
#> [1] 1000    3

# System lifetimes
t_sys <- apply(mat, 1, min)

# Which component caused each failure?
failing <- apply(mat, 1, which.min)
table(failing) / 1000
#> failing
#>     1     2     3 
#> 0.173 0.345 0.482 
# Proportions ~= c(1/6, 2/6, 3/6) for rates (0.1, 0.2, 0.3)
# }