inst/doc/drimmR.R

In drimmR: Estimation, Simulation and Reliability of Drifting Markov Models

## ----setup, include=FALSE-----------------------------------------------------
library(knitr)
knitr::opts_chunk$set(
    fig.align = "center",
    fig.height = 5.5,
    fig.width = 6,
    warning = FALSE,
    collapse = TRUE,
    dev.args = list(pointsize = 10),
    out.width = "65%"
)
# For reproductibility
set.seed(42)

## ----message = FALSE, echo = FALSE--------------------------------------------
library(drimmR)

## -----------------------------------------------------------------------------
data(lambda, package = "drimmR")
states <- c("a","c","g","t")
dmm <- fitdmm(lambda, 1, 1, states, init.estim="freq", fit.method="sum")
dmm

## -----------------------------------------------------------------------------
data(lambda, package = "drimmR")
sequence <- c("a","g","g","t","c","g","a","t","a","a","a")
dmm <-fitdmm(lambda, 1, 1, c('a','c','g','t'), init.estim = "freq")

loglik(dmm, sequence)

aic(dmm, sequence)

bic(dmm, sequence)

## -----------------------------------------------------------------------------
data(lambda)
dmm <- fitdmm(lambda, 1, 1, c('a','c','g','t'),init.estim = "freq")
t <- 10
getTransitionMatrix(dmm,pos=t)

## -----------------------------------------------------------------------------
data(lambda, package = "drimmR")
sequence <- sample(lambda, 30, replace=TRUE )
dmm <- fitdmm(sequence, 1, 1, c('a','c','g','t'), init.estim = "freq")
t <- 10
getStationaryLaw(dmm,pos=t)
getStationaryLaw(dmm,all.pos=TRUE)

## -----------------------------------------------------------------------------
data(lambda, package = "drimmR")
dmm <- fitdmm(lambda, 1, 1, c('a','c','g','t'), init.estim = "freq")
word_probability("cgt",10,dmm,output_file=tempfile("drimmR"))

## -----------------------------------------------------------------------------
data(lambda, package = "drimmR")
dmm <- fitdmm(lambda, 1, 1, c('a','c','g','t'), init.estim = "freq", fit.method="sum")
res <- word_probabilities("cgt", c(100, length(lambda)-3), dmm, output_file=tempfile("drimmR"), plot=TRUE)
head(res[[1]], n=10)
res[2]

## -----------------------------------------------------------------------------
data(lambda, package = "drimmR")
dmm <- fitdmm(lambda, 1, 1, c('a','c','g','t'), init.estim = "freq")
res <- lengthWord_probabilities(2, lambda, c(100, length(lambda)-2), dmm, output_file=tempfile("drimmR"), plot=TRUE)
res[2]

## -----------------------------------------------------------------------------
data(lambda, package = "drimmR")
dmm <- fitdmm(lambda, 1, 1, c('a','c','g','t'), init.estim = "freq")
# simulate a sequence of length 20 000 from dmm
simulate(dmm, tempfile("drimmR"), 20000)

## -----------------------------------------------------------------------------
data(lambda, package = "drimmR")
dmm <- fitdmm(lambda, 1, 1, c("a","c","g","t"), init.estim ="freq", fit.method="sum")
reliability(dmm, k1=1, k2=10, upstates=c("a","c"),output_file = tempfile("drimmR"), plot=TRUE)

## -----------------------------------------------------------------------------
data(lambda, package = "drimmR")
dmm <- fitdmm(lambda, 1, 1, c("a", "c", "g", "t"), init.estim = "freq", fit.method="sum")
availability(dmm, k1=1, k2=10, upstates=c("a","c"), output_file = tempfile("drimmR"), plot=TRUE)

## -----------------------------------------------------------------------------
data(lambda, package = "drimmR")
dmm <- fitdmm(lambda, 1, 1, c("a","c","g","t"), init.estim="freq", fit.method="sum")
maintainability(dmm, k1=1, k2=10, upstates=c("a","c"), output_file = tempfile("drimmR"), plot=TRUE)

## -----------------------------------------------------------------------------
data(lambda, package = "drimmR")
dmm <- fitdmm(lambda, 1, 1, c("a","c","g","t"), init.estim="freq", fit.method="sum")
failureRate(dmm, k1=1, k2=10, upstates=c("a","c"), failure.rate="BMP", output_file=tempfile("drimmR"), plot=TRUE)