sim_igp: Simulation of Inverse Gaussian Process Degradation Paths

In IGPFrailty: Inverse Gaussian Process Degradation Models with Frailty

Simulation of Inverse Gaussian Process Degradation Paths

Description

Simulates longitudinal degradation measurements for multiple units under classical IGP, IGP-Gamma frailty, or IGP-IG frailty models.

Usage

sim_igp(
  n = 10,
  times = seq(0, 4, by = 0.25),
  theta = 2,
  eta = 15,
  xi = 0.2,
  frailty = c("none", "gamma", "ig"),
  mean_fun = "linear",
  seed = NULL
)

Arguments

n	Integer specifying the number of experimental units to simulate.
times	Numeric vector of inspection times (e.g. seq(0, 4, by = 0.25)). Must start at 0.
theta	Mean parameter \theta > 0 (or numeric vector for non-linear mean functions).
eta	Precision/scale parameter \eta > 0.
xi	Frailty variance parameter \xi > 0. Ignored if frailty = "none".
frailty	Frailty specification: "none" (default), "gamma", or "ig".
mean_fun	Mean degradation function "linear" (default), "power", "exponential", or a custom function.
seed	Optional integer random seed for reproducibility.

Value

A data frame containing simulated degradation paths:

unit

Integer unit identifier (1 to n).

t

Inspection time.

increment

Simulated degradation increment \Delta D(t).

degradation

Simulated cumulative degradation D(t).

frailty_z

Realized individual frailty multiplier z_i for unit i.

References

Morita, L. H. M., Tomazella, V. L. D., Balakrishnan, N., Ramos, P. L., Ferreira, P. H., & Louzada, F. (2021). Inverse Gaussian process model with frailty term in reliability analysis. Quality and Reliability Engineering International, 37(2), 763-784. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1002/qre.2762")}.

See Also

igp_fit, lifetime_dist

Examples

set.seed(42)
sim_data <- sim_igp(n = 5, times = seq(0, 2, by = 0.5), theta = 1.5,
                    eta = 10, xi = 0.3, frailty = "gamma")
head(sim_data)

IGPFrailty documentation built on Aug. 25, 2026, 9:08 a.m.