trend_test: Trend Tests for Repairable Systems Analysis

In jjw3952/mcotear: Contains helpful functions for use within MCOTEA

Trend Tests for Repairable Systems Analysis

Description

trend_test tests to distinguish between "no trend" and trends in Poisson Processes. a trend following the Nonhomogeneous.

Laplace Centroid Test: Optimal for distinguishing between "no trend" and a trend following the Nonhomogeneous Poisson Process (NHPP) Exponential Law model.

Military Handbook Test: From Mil-HDBK-189, is optimal for distinguishing between "no trend" and a trend following the NHPP Power Law or Duane model.

See: NIST Trend Tests

Usage

trend_test(t, T, fail.trunc = TRUE)

Arguments

t	A list of failure time vectors. Each vector should indicate a different system, i.e. if you have multiple systems each systems' failure times should be in it's own vector.
T	A list of Total Time on Test (TTT) (i.e. test duration) vectors. The vectors in the list should be of length 1, and each vector should indicate a different system, i.e. if you have multiple systems each systems' TTT should be in it's own vector.
fail.trunc	Logical indicating if the test was failure terminated.

Value

The output will be a list identifying the tests, test statistics, degrees of freedom (where applicable), and p-values.

See Also

power_law_process, power_law_mcf, mcf, ttt, common_beta

Examples

data(amsaa)

# Three systems all time truncated at 200 hours
trend_test(
  t = split(amsaa$Time, amsaa$System),
  T = list(200,200,200),
  fail.trunc = FALSE)

# Three systems all failure truncated
trend_test(
  t = split(amsaa$Time, amsaa$System),
  T = list(197.2,190.8,195.8),
  fail.trunc = TRUE)

# One system, time truncated
trend_test(
  t = list(subset(amsaa$Time, amsaa$System == "S1")),
  T = list(200),
  fail.trunc = FALSE)

# One system, failure truncated
trend_test(
  t = list(subset(amsaa$Time, amsaa$System == "S1")),
  T = list(197.2),
  fail.trunc = TRUE)

 rm(list = c("amsaa"))

jjw3952/mcotear documentation built on Sept. 2, 2023, 10:30 a.m.