garma_pred: Predict generalized ARMA
In JieGroup/tsms: Modeling Univariate Time Series with Multiple Seasonality
Description
Usage
Arguments
Details
Value
Author(s)
Description
Predict the fitted generalized ARMA model.
Usage
1
garma.pred(obj,X,W=NULL,pred_t)
Arguments
obj
the fitted ARMA model object
X
a data vector or n by 1 matrix
W
exogenous variable matrix p by (n+pred_t) matrix
pred_t
n-outsample prediction length
Details
The function make static prediction within observation period, while use dynamic prediction for out sampled period. For burned-in observations, the predicted value will be recorded as 0.
Value
pred_X
a vector recording predicted values. Length = n + pred_t
Author(s)
Tianyang Xie
JieGroup/tsms documentation built on Sept. 15, 2020, 10:39 a.m.
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Description Usage Arguments Details Value Author(s)
Description
Predict the fitted generalized ARMA model.
Usage
1 | garma.pred(obj,X,W=NULL,pred_t)
|
Arguments
obj |
the fitted ARMA model object |
X |
a data vector or n by 1 matrix |
W |
exogenous variable matrix p by (n+pred_t) matrix |
pred_t |
n-outsample prediction length |
Details
The function make static prediction within observation period, while use dynamic prediction for out sampled period. For burned-in observations, the predicted value will be recorded as 0.
Value
pred_X |
a vector recording predicted values. Length = n + pred_t |
Author(s)
Tianyang Xie
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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