smmR1.0.5 package

Simulation, Estimation and Reliability of Semi-Markov Models

availability

Availability Function

convolution

Discrete-time convolution product of ff and gg(See definition 2.2 p....

dot-failureRateBMP

BMP-Failure Rate Function

failureRate

Failure Rate Function

fitmm

Maximum Likelihood Estimation (MLE) of a k-th order Markov chain

fitsmm

Maximum Likelihood Estimation (MLE) of a semi-Markov chain

get.f

Method to get the conditional sojourn time distribution f

get.H

Function to compute the value of the sojourn time cumulative distribut...

get.Kpar

Method to get the number of parameters of a Markov or semi-Markov chai...

get.limitDistribution

Method to get the limit (stationary) distribution

get.Niuj

Function giving the value of the counting process Niuj used in the est...

get.P

Method to compute the value of PP

get.psi

Function to compute the value of the matrix-valued function ψ\psi

get.Py

Method to compute the value of PYP_{Y}

get.qy

Method to get the semi-Markov kernel qYq_{Y}

get.stationaryDistribution

Method to get the stationary distribution

getKernel

Method to get the semi-Markov kernel qq

getProcesses

Function to compute processes based on a list of sequences

is.mm

Function to check if an object is of class mm

is.mmfit

Function to check if an object is of class mmfit

is.smm

Function to check if an object is of class smm

is.smmfit

Function to check if an object is of class smmfit

is.smmnonparametric

Function to check if an object is of class smmnonparametric

is.smmparametric

Function to check if an object is of class smmparametric

maintainability

Maintainability Function

matrixConvolution

Discrete-time matrix convolution product (See definition 3.5 p. 48)

meanRecurrenceTimes

Method to get the mean recurrence times μ\mu

meanSojournTimes

Mean Sojourn Times Function

mm

Markov model specification

mttf

Mean Time To Failure (MTTF) Function

mttr

Mean Time To Repair (MTTR) Function

plot.smm

Plot function for an object of class smm

plot.smmfit

Plot function for an object of class smmfit

reliability

Reliability Function

setSeed

Set the RNG Seed from within Rcpp

simulate.mm

Simulates k-th order Markov chains

simulate.mmfit

Simulates Markov chains

simulate.smm

Simulates semi-Markov chains

simulate.smmfit

Simulates semi-Markov chains

smmnonparametric

Non-parametric semi-Markov model specification

smmparametric

Parametric semi-Markov model specification

smmR-package

smmR : Semi-Markov Models, Markov Models and Reliability

Performs parametric and non-parametric estimation and simulation for multi-state discrete-time semi-Markov processes. For the parametric estimation, several discrete distributions are considered for the sojourn times: Uniform, Geometric, Poisson, Discrete Weibull and Negative Binomial. The non-parametric estimation concerns the sojourn time distributions, where no assumptions are done on the shape of distributions. Moreover, the estimation can be done on the basis of one or several sample paths, with or without censoring at the beginning or/and at the end of the sample paths. Reliability indicators such as reliability, maintainability, availability, BMP-failure rate, RG-failure rate, mean time to failure and mean time to repair are available as well. The implemented methods are described in Barbu, V.S., Limnios, N. (2008) <doi:10.1007/978-0-387-73173-5>, Barbu, V.S., Limnios, N. (2008) <doi:10.1080/10485250701261913> and Trevezas, S., Limnios, N. (2011) <doi:10.1080/10485252.2011.555543>. Estimation and simulation of discrete-time k-th order Markov chains are also considered.

  • Maintainer: Nicolas Vergne
  • License: GPL-3
  • Last published: 2025-11-07