Define bounds of a <dist_spec>

Set the bounds that constrain a distribution when it is discretised: max truncates the support at that value, while cdf_cutoff trims the tail by keeping the distribution only up to its cdf_cutoff quantile. Either bound drops the mass beyond it and renormalises the remaining PMF to sum to one.

Usage

bound_dist(x, max = Inf, cdf_cutoff = 1)

Arguments

x

A <dist_spec>.

max

Numeric, maximum value of the distribution. The distribution will be truncated at this value. Default: Inf, i.e. no maximum.

cdf_cutoff

Numeric in (0, 1]; the cumulative probability up to which the distribution is kept, i.e. it is truncated at the cdf_cutoff quantile. For example cdf_cutoff = 0.999 keeps the distribution up to its 99.9th percentile. Default: 1, i.e. keep the full distribution. A value below 0.5 is rejected, as it is almost certainly the tail probability to drop rather than the CDF level to keep (use 1 - x instead).

Value

a <dist_spec> with relevant attributes set that define its bounds

See also

discretise(), which applies these bounds when producing a PMF.

Examples

# Truncate a gamma distribution at 20
bound_dist(Gamma(mean = 5, sd = 1), max = 20)
#> - gamma distribution (max: 19):
#>   shape:
#>     25
#>   rate:
#>     5
# Keep it up to its 99.9th percentile
bound_dist(Gamma(mean = 5, sd = 1), cdf_cutoff = 0.999)
#> - gamma distribution (cdf_cutoff: 0.999):
#>   shape:
#>     25
#>   rate:
#>     5