dkx: K-aggregated Distribution

In HVoltBb/konez: K-aggregated transformation for modeling excess ones

Description

Density, distribution function, and random generation for the k-aggregated discrete distributions

Usage

dkx(x, k, family, param = list(lambda = NA, size = NA, logmu = NA, lognu
  = NA))

pkx(q, k, family, param = list(lambda = NA, size = NA, logmu = NA, lognu
  = NA))

rkx(n, k, family, param = list(lambda = NA, size = NA, logmu = NA, lognu
  = NA))

Arguments

x	vector of (non-negative integers) quantiles.
k	the additional number of mass to aggregate into the single mass.
family	character string partial matched from a list of base line distributions (Poisson, zero truncated Poisson, negative binomial, zero truncated negative binomial, Conway-Maxwell-Poisson, and zero truncated CMP distributions) c('pois', 'tpois', 'negbinom', 'tnegbinom', 'cmp', 'tcmp'). Defaults to 'pois'.
param	list of parameters to pass to the base line function.
q	vector of quantiles.
n	number of random number samples to return.

Details

For different base line distributions, a different set of parameters needs to be supplied through param: for families 'pois' and 'tpois', param$lambda cannot be NA; for families 'negbinom' and 'tnegbinom', param$size and param$logmu cannot be NA; for families 'cmp' and 'tcmp', param$lognu and param$logmu cannot be NA.

Functions

• dkx: Density function for a k-aggregated distribution.

• pkx: Distribution function for the k-aggregated distribution.

• rkx: Random number generator for the k-aggregated distribution.

See Also

dcmp, dpois, dNegBinom

HVoltBb/konez documentation built on Nov. 7, 2019, 1:30 a.m.