# Pch: The Piecewise constant hazards (Pch) distribution In eha: Event History Analysis

## Description

Density, distribution function, quantile function, hazard function, cumulative hazard function, and random generation for the pch distribution with parameters `cuts` and `levels`.

## Usage

 ```1 2 3 4 5 6``` ```dpch(x, cuts, levels, log = FALSE) ppch(q, cuts, levels, lower.tail = TRUE, log.p = FALSE) qpch(p, cuts, levels, lower.tail = TRUE, log.p = FALSE) hpch(x, cuts, levels, log = FALSE) Hpch(x, cuts, levels, log.p = FALSE) rpch(n, cuts, levels) ```

## Arguments

 `x, q` vector of quantiles. `p` vector of probabilities. `n` number of observations. If `length(n) > 1`, the length is taken to be the number required. `cuts, levels` `cuts` devine the intervals where the hazard function is constant. The cuts must be strictly positive and finite. `levels` are the interval-constant values, one more than the cuts. `log, log.p` logical; if TRUE, probabilities p are given as log(p). `lower.tail` logical; if TRUE (default), probabilities are P(X <= x), otherwise, P(X > x).

## Details

The Pch distribution is defined by the cuts and the levels so that the hazard function is constant on intervals.

## Value

`dpch` gives the density, `ppch` gives the distribution function, `qpch` gives the quantile function, `hpch` gives the hazard function, `Hpch` gives the cumulative hazard function, and `rpch` generates random deviates.

Invalid arguments will result in return value `NaN`, with a warning.

eha documentation built on Sept. 22, 2017, 5:04 p.m.