| train.tspred {TSPred} | R Documentation |
Train method for tspred objects
Description
Fits a model to the time series data contained in a tspred class object
based on a particular model training method. The model training method is defined
by a modeling object contained in the tspred class object.
Usage
## S3 method for class 'tspred'
train(obj, ...)
Arguments
obj |
An object of class |
... |
Ignored |
Details
The function train.tspred calls the method train
on the modeling object for each time series contained in obj.
Finally, the produced time series model is introduced in the structure of the
tspred class object in obj.
If any modeling parameters are computed during training, they are duly updated
in the structure of the tspred class object in obj. This is important
for provenance and reprodutibility of the training process.
Value
An object of class tspred with updated structure containing
the produced trained time series models.
Author(s)
Rebecca Pontes Salles
See Also
[tspred()] for defining a particular time series prediction process, and [ARIMA()] for defining a time series modeling and prediction method.
Other train:
train()
Examples
data(CATS)
#Obtaining objects of the processing class
proc1 <- subsetting(test_len=20)
proc2 <- BoxCoxT(lambda=NULL)
proc3 <- WT(level=1, filter="bl14")
#Obtaining objects of the modeling class
modl1 <- ARIMA()
#Obtaining objects of the evaluating class
eval1 <- MSE_eval()
#Defining a time series prediction process
tspred_1 <- tspred(subsetting=proc1,
processing=list(BCT=proc2,
WT=proc3),
modeling=modl1,
evaluating=list(MSE=eval1)
)
summary(tspred_1)
tspred_1 <- subset(tspred_1, data=CATS[3])
tspred_1 <- preprocess(tspred_1,prep_test=FALSE)
tspred_1 <- train(tspred_1)