Default method for computing primary event censored PMF

Computes the PMF by differencing pcens_cdf() at x and min(x + swindow, D), normalised over [L, D]. Where swindow = 0 the primary event censored density at x is returned instead. See dprimarycensored() for the details.

Usage

# Default S3 method
pcens_pmf(object, x, pwindow, swindow = 1, L = -Inf, D = Inf, log = FALSE, ...)

Arguments

object

A pcens object as created by new_pcens().

x

Vector of quantiles

pwindow

Primary event window. Use pwindow = 0 for an exactly observed primary event, in which case the delay CDF is used directly.

swindow

Secondary event window (default: 1). Use swindow = 0 for an exactly observed secondary event, in which case a density is returned rather than a probability (see Details).

L

Minimum delay (lower truncation point). Defaults to -Inf, meaning no left truncation. For any finite value of L the distribution is left-truncated at L.

D

Maximum delay (upper truncation point). If finite, the distribution is truncated at D. If set to Inf, no upper truncation is applied. Defaults to Inf.

log

Logical; if TRUE, probabilities p are given as log(p)

...

Additional arguments passed to methods.

Value

Vector of primary event censored PMFs, normalized over [L, D] if truncation is applied

See also

Low level primary event censored distribution objects and methods new_pcens(), pcens_cdf(), pcens_cdf.default(), pcens_cdf.pcens_pdiscretehazard(), pcens_cdf.pcens_pdiscretestep(), pcens_cdf.pcens_pgamma_dunif(), pcens_cdf.pcens_pgengamma.orig_dunif(), pcens_cdf.pcens_pgengamma_dunif(), pcens_cdf.pcens_plnorm_dunif(), pcens_cdf.pcens_pweibull_dunif(), pcens_pmf(), pcens_quantile(), pcens_quantile.default(), update.pcens()

Examples

obj <- new_pcens(
  pdist = pgamma, dprimary = dunif,
  primary_args = list(min = 0, max = 1),
  shape = 3, scale = 2
)
pcens_pmf(obj, x = 0:9, pwindow = 1, D = 10)
#>  [1] 0.004551244 0.045675031 0.105784553 0.144941751 0.157178437 0.149641077
#>  [7] 0.131158433 0.108576455 0.086202811 0.066290209