Keywords - Function groups - @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Library: multi

Quantlet: simvar
Description: computes a multidimensional autoregressive time series.

Usage: y = simvar(u,y0,a)
Input:
u (K x T)-matrix of 'noise'. Each column represents the K-dimensional noise, or innovation of a point in time.
y0 (K x p)-matrix of starting ('pre-sample')-values of time series.
a (K x K*p) or (K x K*p+1)-matrix of model parameters. The model can be specified with [(K x K*p+1)] or without [(K x K*p)] intercept. If an intercept is specified simvar() regards the first column of 'a' as the intercept.
Output:
y (K x p+T)-matrix of autoregressive time series. The first p columns of 'y' are 'y0', the remaining are the computed time series.

Example:

library("multi")

a = #(.4,0)~#(.2,-.1)

randomize(101)

u = normal(2,5)

simvar( u, 10|20, a)  

Result:

Contents of y

[1,]       10    8.995   2.8483   1.8941  0.28264   1.2074 

[2,]       20  -3.2578   1.6874  -1.6002   1.7628 -0.70274 


Library: multi

Keywords - Function groups - @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Author: Benkwitz, 98.01.27
(C) MD*TECH Method and Data Technologies, 21.9.2000