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mapfit (version 1.0.0)

ERHMMClass: ErlangHMM for MAP

Description

ErlangHMM for MAP

ErlangHMM for MAP

Arguments

Methods


Method alpha()

Get alpha

Usage

ERHMMClass$alpha()

Returns

A vector of alpha


Method shape()

Get shape

Usage

ERHMMClass$shape()

Returns

A vector of shapes


Method rate()

Get rate

Usage

ERHMMClass$rate()

Returns

A vector of rates


Method P()

Get P

Usage

ERHMMClass$P()

Returns

A matrix of P


Method xi()

Get exit rates

Usage

ERHMMClass$xi()

Returns

A vector of exit rates


Method new()

Create an ERHMM

Usage

ERHMMClass$new(alpha, shape, rate, P, xi)

Arguments

alpha

A vector of initial probability

shape

A vector of shape parameters

rate

A vector of rate parameters

P

A matrix of transition probabilities

xi

An exit rate vector

Returns

An instance of ERHMM


Method copy()

copy

Usage

ERHMMClass$copy()

Returns

A new instance


Method size()

The number of components

Usage

ERHMMClass$size()

Returns

The number of components


Method df()

Degrees of freedom

Usage

ERHMMClass$df()

Returns

The degrees of freedom


Method print()

Print

Usage

ERHMMClass$print(...)

Arguments

...

Others


Method mmoment()

Marginal moments

Usage

ERHMMClass$mmoment(k, ...)

Arguments

k

An integer of degree

...

Others

Returns

A vector of moments


Method jmoment()

Joint moments

Usage

ERHMMClass$jmoment(lag, ...)

Arguments

lag

An integer of lag

...

Others

Returns

A matrix of moments


Method acf()

k-lag correlation

Usage

ERHMMClass$acf(...)

Arguments

...

Others

Returns

A vector for k-lag correlation


Method emfit()

Run EM

Usage

ERHMMClass$emfit(data, options, ...)

Arguments

data

A dataframe

options

A list of options

...

Others


Method init()

Initialize with data

Usage

ERHMMClass$init(data, ...)

Arguments

data

A dataframe

...

Others


Method clone()

The objects of this class are cloneable with this method.

Usage

ERHMMClass$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Details

A special case of MAP.