sinar_pois: Simulating SINAR(1,1) process with innovations from a poison...

In gilberto-sassi/sinar: Conditional Least Squared (CLS) Method for the Model SINAR(1,1)

Description

sinar_pois returns a matrix representing a simulated regular lattice from a SINAR(1,1) process with innovations from a poison distribution.

Usage

sinar_pois(n_row, n_col, a10, a01, a11, l)

Arguments

n_row	Number of rows in the simulated lattice.
n_col	Number of columns in the simulated lattice.
a10	Coefficient from the element X_{i-1, j}.
a01	Coefficient from the element X_{i, j-1}.
a11	Coefficient from the element X_{i-1, j-1}.
l	Mean of the poison distribution used as innovations.

Details

This function simulates a regular lattice from the model

X_{i,j}= a_{10} X_{i-1,j} + a_{01} X_{i,j-1} + a_{11} X_{i-1, j-1} + ε_{i,j}

where ε_{i,j} is an iid process with poison distribution. Note the a_{10}, a_{01}, a_{11} must belong to the interval [0,1].

Value

A integer matrix.

Examples

n_row <- 20
n_col <- 50
a10 <- 0.2
a01 <- 0.2
a11 <-  0.5
l <- 1
sinar_pois(n_row, n_col, a10, a01, a11, l)

gilberto-sassi/sinar documentation built on Nov. 16, 2020, 1:42 p.m.