View source: R/linearModelTraining.R
linearModelTraining | R Documentation |
linearModelTraining is a support function for training linear models for partitions in all layers.
linearModelTraining( DataT, insigThs = 1e-08, alpha = 0.05, messageFlag = FALSE, polyDegree = 1, expFlag = FALSE )
DataT |
contains a multiresolution dataset s.t.
|
insigThs |
is a threshold to determine whether a magnitude of a feature coefficient is enough so that the feature is designated as a selected feature. |
alpha |
is a significance level to determine whether a magnitude of a feature coefficient is enough so that the feature is designated as a selected feature. |
messageFlag |
is a flag. If it is true, the function shows the text regarding the progress of computing. |
polyDegree |
is a degree of polynomial function that is used to fit the data.
If it is greater than 1, the polynomial formula is used in |
expFlag |
is an exponential flag to control the formula for data fitting.
If it is true, then the exp() formula is used in |
This function returns models
and DataT
.
models |
|
DataT |
is a |
# Running linearModelTraining using simulation data DataT<-SimpleSimulation(100,type=1) obj<-linearModelTraining(DataT)
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