[Y,E] =
simulate(Mdl,numObs)
[Y,E,V]
= simulate(Mdl,numObs)
[Y,E,V] = simulate(Mdl,numObs,Name,Value)
[
simulates
sample paths and innovations from the ARIMA model, Y
,E
] =
simulate(Mdl
,numObs
)Mdl
.
The responses can include the effects of seasonality.
[
additionally
simulates conditional variances, Y
,E
,V
]
= simulate(Mdl
,numObs
)V
.
[Y,E,V] = simulate(Mdl,numObs,
simulates
sample paths with additional options specified by one or more Name,Value
)Name,Value
pair
arguments.

ARIMA or ARIMAX model, specified as an The properties of 

Positive integer that indicates the number of observations (rows)
to generate for each path of the outputs 
Specify optional commaseparated pairs of Name,Value
arguments.
Name
is the argument
name and Value
is the corresponding
value. Name
must appear
inside single quotes (' '
).
You can specify several name and value pair
arguments in any order as Name1,Value1,...,NameN,ValueN
.

Mean zero presample innovations that provide initial values
for the model. Default: 

Positive integer that indicates the number of sample paths (columns) to generate. Default: 

Positive presample conditional variances which provide initial
values for any conditional variance model. If the variance of the
model is constant, then Default: 

Matrix of predictor data with length Default: 

Presample response data that provides initial values for the
model. Default: 
Notes







[1] Box, G. E. P., G. M. Jenkins, and G. C. Reinsel. Time Series Analysis: Forecasting and Control 3rd ed. Englewood Cliffs, NJ: Prentice Hall, 1994.
[2] Enders, W. Applied Econometric Time Series. Hoboken, NJ: John Wiley & Sons, 1995.
[3] Hamilton, J. D. Time Series Analysis. Princeton, NJ: Princeton University Press, 1994.
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