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
bakcast
whether a backcasted value is prepended to the time series (defaults to false)
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