unimix: Univariate Mixtures of Exponential, Normal and Gamma...

In tpetzoldt/antibioticR: Analysis of Antibiotic Resistance Data

Description

Density, distribution function, quantile function and random generation for univariate mixture distributions, composed of exponential, normal and gamma distributions.

Usage

dunimix(x, obj, full.out, ...)

punimix(q, obj, full.out, ...)

runimix(n, obj, ...)

## S4 method for signature 'numeric,list'
dunimix(x, obj, full.out, ...)

## S4 method for signature 'numeric,mxObj'
dunimix(x, obj, full.out = FALSE, ...)

## S4 method for signature 'numeric,list'
punimix(q, obj, full.out = FALSE, ...)

## S4 method for signature 'numeric,mxObj'
punimix(q, obj, full.out, ...)

## S4 method for signature 'numeric,list'
runimix(n, obj, ...)

## S4 method for signature 'numeric,mxObj'
runimix(n, obj, ...)

Arguments

x	vector of quantiles
obj	obkect of class mxObj with mixture distribution parameters
full.out	return total density only or a matrix with all components
...	reserved for future extensions
q	vector of quantiles
n	number of random values

Value

dunimix gives the density, punimix gives the distribution function, qunimix gives the quantile function, and runimix generates random deviates. The length of the result is determined by the legnt of x. Argument full.out determines whether only a vector with the totals of the distribution or a data frame with all components is returned.

Note

A quantile function qunimix is not yet implemented. Automatic coercion of arguments may still have bugs.

tpetzoldt/antibioticR documentation built on Sept. 25, 2021, 1:17 p.m.