scalation.modeling.forecasting.multivar.VAR
See theVAR companion class
The VAR object supports regression for Multivariate Time Series data. Given a response matrix y, a predictor matrix x is built that consists of lagged y vectors. Additional future response vectors are built for training. y_t = b dot x where x = [y_{t-1}, y_{t-2}, ... y_{t-lag}].
Attributes
Companion
class
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Supertypes
class Object
trait Matchable
class Any
Self type
Members list
Create a VAR object from a response matrix. The input/data matrix x is formed from the lagged y vectors as columns in matrix x.
Create a VAR object from a response matrix. The input/data matrix x is formed from the lagged y vectors as columns in matrix x.
Value parameters
fname
the feature/variable names
hh
the maximum forecasting horizon (h = 1 to hh)
hparam
the hyper-parameters (defaults to MakeMatrix4TS.hp)
tRng
the time range, if relevant (time index may suffice)
y
the response/output matrix (multi-variate time series data)
Attributes
Plot actual vs. predicted values for all variables (columns of the matrices).
Plot actual vs. predicted values for all variables (columns of the matrices).
Value parameters
name
the name of the model run to produce yp
y
the original un-expanded output/response matrix
yp
the predicted values (one-step ahead forecasts) matrix
Attributes