GMMPPClass: GMMPP: Approximation for MAP

In mapfit: PH/MAP Parameter Estimation

GMMPP: Approximation for MAP

Description

GMMPP: Approximation for MAP

GMMPP: Approximation for MAP

Details

A point process dominated by a continuous-time Markov chain.

Super class

mapfit::MAPClass -> GMMPPClass

Methods

Public methods

• GMMPPClass$new()

• GMMPPClass$copy()

• GMMPPClass$emfit()

• GMMPPClass$clone()

Inherited methods

• mapfit::MAPClass$D0()
• mapfit::MAPClass$D1()
• mapfit::MAPClass$acf()
• mapfit::MAPClass$alpha()
• mapfit::MAPClass$df()
• mapfit::MAPClass$init()
• mapfit::MAPClass$jmoment()
• mapfit::MAPClass$mmoment()
• mapfit::MAPClass$print()
• mapfit::MAPClass$size()
• mapfit::MAPClass$xi()

---

Method new()

Create a MAP

Usage

GMMPPClass$new(alpha, D0, D1, xi)

Arguments

alpha

A vector of initial probability

D0

An infinitesimal generator

D1

An infinitesimal generator

xi

An exit rate vector

Returns

An instance of MAP

---

Method copy()

copy

Usage

GMMPPClass$copy()

Returns

A new instance

---

Method emfit()

Run EM

Usage

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

Arguments

data

A dataframe

options

A list of options

...

Others

---

Method clone()

The objects of this class are cloneable with this method.

Usage

GMMPPClass$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

mapfit documentation built on Nov. 22, 2022, 5:05 p.m.