param_reg | R Documentation |
Create a named list of model parameters that can be passed into regression and machine learning functions.
param_reg(
regmod = "least_squares",
intercept = TRUE,
singmin = 1e-05,
dimax = 0L,
residscale = "none",
confl = 0.1,
alphac = 0
)
method |
A character string specifying the type of
regression model (the default is |
intercept |
A Boolean specifying whether an intercept
term should be added to the predictor (the default is |
singmin |
A numeric threshold level for discarding
small singular values in order to regularize the inverse of the
predictor matrix (the default is |
dimax |
An integer equal to the number of singular
values used for calculating the reduced inverse of the
predictor matrix (the default is |
confl |
The confidence level for calculating the quantiles of
returns (the default is |
alphac |
The shrinkage intensity of |
The function param_reg()
creates a named list of model parameters
that can be passed into regression and machine learning functions. For
example into the functions calc_reg()
and roll_reg()
.
The function param_reg()
simplifies the creation of regression
parameter lists. The users can create a parameter list with the default
values, or they can specify custom parameter values.
A named list of model parameters that can be passed into regression and machine learning functions.
## Not run:
# Create a default list of regression parameters
controlv <- HighFreq::param_reg()
unlist(controlv)
# Create a custom list of regression parameters
controlv <- HighFreq::param_reg(intercept=FALSE, method="regular", dimax=4)
unlist(controlv)
## End(Not run)
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