reliability {drimmR}

Reliability function

Description

Reliability or the survival function of a system at time k \in N

Usage

reliability(
  x,
  k1 = 0L,
  k2,
  upstates,
  output_file = NULL,
  plot = FALSE,
  ncpu = 2
)

Arguments

x

An object of class dmm

k1

Start position (default value=0) : a positive integer giving the start position along the sequence from which the reliabilities of the DMM should be computed, such that k1<k2

k2

End position : a positive integer giving the end position along the sequence until which the reliabilities of the DMM should be computed, such that k2>k1

upstates

Character vector of the subspace working states among the state space vector such that upstates < s

output_file

(Optional) A file containing matrix of reliability probabilities (e.g, "C:/.../REL.txt")

plot

FALSE (default); TRUE (display a figure plot of reliability probabilities by position)

ncpu

Default=2. Represents the number of cores used to parallelized computation. If ncpu=-1, then it uses all available cores.

Details

The reliability at time k \in N is the probability that the system has functioned without failure in the period [0, k]

Value

A vector of length k + 1 giving the values of the reliability for the period [0 \ldots k]

Author(s)

Alexandre Seiller

References

Barbu VS, Vergne N (2018). “Reliability and survival analysis for drifting Markov models: modelling and estimation.” Methodology and Computing in Applied Probability, 1–33. doi: 10.1007/s11009-018-9682-8, https://doi.org/10.1007/s11009-018-9682-8.

See Also

fitdmm, getTransitionMatrix

Examples

data(lambda, package = "drimmR")
dmm <- fitdmm(lambda, 1, 1, c('a','c','g','t'), init.estim = "freq",
fit.method="sum")
k1 <- 1
k2 <- 200
upstates <- c("c","t")  # vector of working states
reliability(dmm,k1,k2,upstates,plot=TRUE)