www.gusucode.com > econ 案例源码程序 matlab代码 > econ/AutoregressiveModelExample.m

    %% Autoregressive Model  
% This example shows how to compute and plot the impulse response function
% for an autoregressive (AR) model. The AR(_p_) model is given by 
%
% $${y_t} = \mu  + \phi {(L)^{ - 1}}{\varepsilon _t},$$
%
% where $\phi(L)$  is a $p$-degree
% AR operator polynomial, $(1 - {\phi _1}L -  \ldots  - {\phi _p}{L^p})$. 
%
% An AR process is stationary provided that the AR operator polynomial is
% stable, meaning all its roots lie outside the unit circle. In this case,
% the infinite-degree inverse polynomial, $\psi (L) = \phi {(L)^{ - 1}}$,
% has absolutely summable coefficients, and the impulse response function
% decays to zero.

% Copyright 2015 The MathWorks, Inc.


%% Step 1. Specify the AR model. 
% Specify an AR(2) model with coefficients $\phi_1 = 0.5$ 
% and $\phi_2 = -0.75$. 
modelAR = arima('AR',{0.5,-0.75});  

%% Step 2. Plot the impulse response function. 
% Plot the impulse response function for 30 periods. 
impulse(modelAR,30)    

%%
% The impulse function decays in a sinusoidal pattern.