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 (starting from the "...") are to be named and that a warning will be displayed if unknown arguments are passed. |

`kappa` |
A numeric value >= 0. A |

`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, e.g., #' 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.

Returns a `numeric`

value or vector will be returned.

# 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)