VARMASIM Call
generates a VARMA(,) time series
- CALL VARMASIM( series, phi, theta, mu, sigma, n
<, p, q, initial, seed>);
The inputs to the VARMASIM subroutine are as follows:
- phi
- specifies a matrix
containing the autoregressive coefficient matrices,
where is the number of the elements in the subset
of the AR order and is the number of variables.
You must specify either phi or theta.
- theta
- specifies a matrix
containing the moving-average coefficient matrices,
where is the number of the elements in the subset
of the MA order.
You must specify either phi or theta.
- mu
- specifies a (or ) mean vector of the series.
If mu is not specified, a zero vector is used.
- sigma
- specifies a covariance matrix of the innovation series.
If sigma is not specified, an identity matrix is used.
- n
- specifies the length of the series. If n is not specified,
is used.
- p
- specifies the subset of the AR order.
See the VARMACOV subroutine.
- q
- specifies the subset of the MA order.
See the VARMACOV subroutine.
- initial
- specifies the initial values of random variables.
If , then and
all take the same value .
If the initial option is not specified,
the initial values are estimated
for the stationary vector time series;
the initial values are assumed as zero
for the nonstationary vector time series.
- seed
- is a scalar containing the random number seed.
At the first execution of the subroutine,
the seed variable is used as follows:
If seed > 0, the input seed is used for generating the series.
If seed = 0, the system clock is used to generate the seed.
If seed < 0, the value (-1)(seed) is used for generating the series.
If the seed is not supplied, the system clock is used
to generate the seed.
On subsequent calls of the subroutine in the DO loop
like environment the seed variable is used as follows:
If seed > 0, the seed remains unchanged.
In other cases, after each execution of the subroutine,
the current seed is updated internally.
The VARMASIM subroutine returns the following value:
- series
- is an matrix containing
the generated VARMA() time series.
When either the initial option is specified or
zero initial values are used, these
initial values are not included in series.
Consider the following bivariate (
) stationary VARMA(1,1)
time series:
To generate this series, you can use the following statements:
phi = { 1.2 -0.5, 0.6 0.3 };
theta= {-0.6 0.3, 0.3 0.6 };
mu = { 10, 20 };
sigma= { 1.0 0.5, 0.5 1.25};
call varmasim(yt, phi, theta, mu, sigma, 100);
Consider a bivariate (
) nonstationary VARMA(1,1) time series
with the same
,
, and
in
the previous example and the following AR coefficient:
To generate this series, you can use the following statements:
phi = { 1.0 0.0, 0.0 0.3 };
call varmasim(yt, phi, theta, mu, sigma, 100) initial=3;
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