innovation: Family of Innovations Process for Fitting an INAR(p) Model

In rdmatheus/tsinteger: Autoregressive Models for Analysis of Integer-Valued Time Series

Description

Provide the current available distributions that can be used as an innovation process in a fit of the INAR(p) model.

Usage

innovation(dist)

## S3 method for class 'innovation'
print(x, ...)

Arguments

dist	Character specification of the innovation process, see details.
x	An "innovation" object.
...	Further arguments for other specific methods.

Details

There are some discrete distributions available for the innovation process specification. The following table display their names and their abbreviations to be passed to innovation().

Distribution	Abbreviation		Parameters
Bernoulli	"BE"		0 < theta < 1
BerPoi	"BP"		theta > 0; 0 < phi < 1
BerG	"BG"		theta, phi > 0
Geometric	"GE"		theta > 0
Mean-Parameterized COM-Poisson	"CP"		theta, phi > 0
Negative Binomial	"NB"		theta, phi > 0
Poisson	"PO"		theta > 0

Value

The function innovation() returns an "innovation" object that brings a set of information about the innovation process . More specifically, returns a list with the following elements:

• d: Probability mass function function(x, par).

• r: Random generator function function(n, par).

• par: Describes the parametric space of the distribution.

• npar: Number of parameters of the innovation process specified.

• constraint: Character; describes the restriction between parameters if any.

• disp: Describes the types of dispersion that the distribution can model.

• name: Name of the distribution.

The arguments of the returned functions are:

x

Vector of discrete non-negative quantiles.

n

Number of observations to return.

par

Parameter vector of the innovation process.

Author(s)

Rodrigo M. R. Medeiros <[e-mail]>

Examples

## Not run: 
 ### Specification of the Poisson innovation to 'inv' object
 inv <- innovation("PO")

 ### Methods
 inv

 ### Generating observations
 x <- inv$r(500, 5)

 ### Barplot and probability mass function
 xaxis <- barplot(prop.table(table(x)), main = inv$name,
                  xlab = "x", ylab = "Proportion")
 points(xaxis, inv$d(sort(unique(x)), 5),
        type = "b", pch = 16, col = 2)

## End(Not run)

rdmatheus/tsinteger documentation built on March 24, 2021, 12:16 a.m.