## NAR modeling

Purpose

Description

Macro Synopsis

Modules

Related Functions

References

### Purpose

Estimate the coefficients of a NAR model

### Description

"NAR modeling" calculates the least-squares estimates of the
coefficients of a Nonlinear Auto-Regressive (NAR) model involving
linear and bilinear terms of lagged values of the response signal,

The input signal y is regarded as NAR model response.
The output signal r is the residual, i.e. the estimation error.
Parameters are:

- the linear order K of the response process,
- the bilinear order M of the response process.

Besides the estimated coefficients, a residual constant term, the mean of the
residues, the residual variance, and the normalized residual variance are
displayed in the message window.

### Macro Synopsis

`r = NARmodel(y,K,M);`

signal r,y;

int K,M;

### Modules

Statistics

### Related Functions

AR simulation, ARIMA modeling,
ARIMAX modeling, ARMA model order,
ARMA modeling, ARMA simulation,
ARMA spectral density, ARMAX modeling,
ARMAX simulation, NARMA modeling.

### References

Ljung [10], Conover [11], Graybill
[12], Hollander/Wolfe [13]