Sample from a hazard-parameterised step distribution

Draws n independent samples from the discrete distribution defined by hazards. Converts hazards to a PMF via hazards_to_pmf() then delegates to rdiscretestep().

Usage

rdiscretehazard(n, boundaries = NULL, hazards)

Arguments

n

Integer. Number of samples to draw.

boundaries

Numeric vector of length \(K+1\) defining the bin edges. Must be strictly increasing. Defaults to 0:K.

hazards

Numeric vector of length \(K\) (or \(K-1\), in which case a trailing 1 is appended) giving the discrete-time conditional hazard for each bin. Values must be in \([0, 1]\).

Value

Numeric vector of length n.

Details

Outside fitting it is a deterministic wrapper around rdiscretestep(). It earns its keep as a fitting parameterisation in fitdistdoublecens() because the random walk on the logit hazard smooths the recovered PMF.

See also

rdiscretestep(), hazards_to_pmf(), pmf_to_hazards(), fitdistdoublecens()

Other pdiscretehazard: ddiscretehazard(), discretehazard_start(), pdiscretehazard()

Examples

set.seed(42)
rdiscretehazard(10, boundaries = 0:3, hazards = c(0.3, 0.5, 1))
#>  [1] 1 1 2 1 3 3 1 2 3 1