Forecast Cumulative Failures from a Reliability Growth Model

Takes a fitted rga object and a vector of cumulative times, returning predicted cumulative failures with confidence bounds as an rga_predict S3 object.

Usage

predict_rga(object, times, conf_level = 0.95)

Arguments

object

An object of class rga returned by rga().

times

A numeric vector of cumulative times at which to forecast. All values must be finite and > 0. A warning is issued if any value is at or below the maximum observed cumulative time (hindcasting).

conf_level

The desired confidence level (default 0.95). Must be a single finite numeric in (0, 1).

Value

An object of class rga_predict containing:

times

The forecast cumulative times.

cum_failures

Predicted cumulative failures.

lower_bounds

Lower confidence bounds.

upper_bounds

Upper confidence bounds.

conf_level

The confidence level used.

model_type

Either "Crow-AMSAA" or "Piecewise NHPP".

rga_object

The original rga object (used by the plot method).

See also

Other Reliability Growth Analysis: plot.rga(), plot.rga_predict(), print.rga(), print.rga_predict(), rga()

Examples

times <- c(100, 200, 300, 400, 500)
failures <- c(1, 2, 1, 3, 2)
fit <- rga(times, failures)
fc <- predict_rga(fit, times = c(1500, 2000))
#> Warning: Some 'times' values are <= the maximum observed cumulative time. Hindcasting is allowed but may not be meaningful.
print(fc)
#> Reliability Growth Forecast (Crow-AMSAA) 
#> ----------------------------------------- 
#>  Time Cum.Failures Lower (95%) Upper (95%)
#>  1500          9.3         7.1        12.1
#>  2000         11.7         8.6        15.8