mxObj-methods: Methods for 'mxObj' Univariate Mixture Objects

In tpetzoldt/antibioticR: Analysis of Antibiotic Resistance Data

Description

Constructor and accessor functions of univariate mixture distributions, composed of exponential, normal and gamma distributions.

The methods leverage methods from class 'mle2' of package 'bbmle'

Usage

fit(object, ...)

ecoff(object, ...)

rsquared(object, ...)

startpar(object, ...)

models(object, ...)

## S4 method for signature 'mxObj'
coef(object, i = NULL, ...)

pstart(obj, ...)

## S4 method for signature 'mxObj'
pstart(obj, ...)

## S4 method for signature 'mxMle'
summary(object, ...)

## S4 method for signature 'mxMle'
vcov(object, ...)

## S4 method for signature 'mxMle'
AIC(object, ..., k = 2)

## S4 method for signature 'mxMle'
logLik(object, ...)

get_data(object, ...)

## S4 method for signature 'mxMle'
get_data(object, ...)

mxObj(x, type = NA, left = c("e", "n"))

Arguments

object	an object of class 'mxObj'
...	optional arguments passed to the methods
i	index of an individual distribution component
obj	an object of class 'mxObj'
k	penalty parameter (nearly always left at its default value of 2)
x	object (vector, list, data.frame) containing mixture distributions in one of sereral known formats. (thpe-todo: document known formats)
type	type of the mixture distribution, e.g. "n", "en", "nnn", etc.
left	whether leftmost distribution is exponential ("e") or normal ("n")

See Also

mle2-class

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