linearModelTraining {MRReg} | R Documentation |
linearModelTraining
Description
linearModelTraining is a support function for training linear models for partitions in all layers.
Usage
linearModelTraining(
DataT,
insigThs = 1e-08,
alpha = 0.05,
messageFlag = FALSE,
polyDegree = 1,
expFlag = FALSE
)
Arguments
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 |
Value
This function returns models
and DataT
.
models |
|
DataT |
is a |
Examples
# Running linearModelTraining using simulation data
DataT<-SimpleSimulation(100,type=1)
obj<-linearModelTraining(DataT)