utilitiesForPiecewiseExponentialDistribution {rpact} | R Documentation |

Distribution function, quantile function and random number generation for the piecewise exponential distribution.

getPiecewiseExponentialDistribution(time, ..., piecewiseSurvivalTime = NA_real_, piecewiseLambda = NA_real_, kappa = 1) ppwexp(t, ..., s = NA_real_, lambda = NA_real_, kappa = 1) getPiecewiseExponentialQuantile(quantile, ..., piecewiseSurvivalTime = NA_real_, piecewiseLambda = NA_real_, kappa = 1) qpwexp(q, ..., s = NA_real_, lambda = NA_real_, kappa = 1) getPiecewiseExponentialRandomNumbers(n, ..., piecewiseSurvivalTime = NA_real_, piecewiseLambda = NA_real_, kappa = 1) rpwexp(n, ..., s = NA_real_, lambda = NA_real_, kappa = 1)

`...` |
Ensures that all arguments after |

`kappa` |
The kappa value. Is needed for the specification of the Weibull distribution. In this case, no piecewise definition is possible, i.e., only lambda and kappa need to be specified. This function is equivalent to pweibull(t, kappa, 1 / lambda) of the R core system, i.e., the scale parameter is 1 / 'hazard rate'. For example, getPiecewiseExponentialDistribution(time = 130, piecewiseLambda = 0.01, kappa = 4.2) and pweibull(q = 130, shape = 4.2, scale = 1 /0.01) provide the sample result. |

`t, time` |
Vector of time values. |

`s, piecewiseSurvivalTime` |
Vector of start times defining the "time pieces". |

`lambda, piecewiseLambda` |
Vector of lambda values (hazard rates) corresponding to the start times. |

`q, quantile` |
Vector of quantiles. |

`n` |
Number of observations. |

`getPiecewiseExponentialDistribution`

(short: `ppwexp`

),
`getPiecewiseExponentialQuantile`

(short: `qpwexp`

), and
`getPiecewiseExponentialRandomNumbers`

(short: `rpwexp`

) provide
probabilities, quantiles, and random numbers according to a piecewise
exponential or a Weibull distribution.
The piecewise definition is performed through a vector of
starting times (`piecewiseSurvivalTime`

) and a vector of hazard rates (`piecewiseLambda`

).
You can also use a list that defines the starting times and piecewise
lambdas together and define piecewiseSurvivalTime as this list.
The list needs to have the form, for example,
piecewiseSurvivalTime <- list(
"0 - <6" = 0.025,
"6 - <9" = 0.04,
"9 - <15" = 0.015,
">=15" = 0.007)
For the Weibull case, you can also specify a shape parameter kappa in order to
calculated probabilities, quantiles, or random numbers.
In this case, no piecewise definition is possible, i.e., only piecewiseLambda and
kappa need to be specified.

# Calculate probabilties for a range of time values for a # piecewise exponential distribution with hazard rates # 0.025, 0.04, 0.015, and 0.007 in the intervals # [0, 6), [6, 9), [9, 15), [15,Inf), respectively, # and re-return the time values: piecewiseSurvivalTime <- list( "0 - <6" = 0.025, "6 - <9" = 0.04, "9 - <15" = 0.015, ">=15" = 0.01) y <- getPiecewiseExponentialDistribution(seq(0, 150, 15), piecewiseSurvivalTime = piecewiseSurvivalTime) getPiecewiseExponentialQuantile(y, piecewiseSurvivalTime = piecewiseSurvivalTime)