Complete a Residual Weighted Learning Analysis
# S4 method for Kernel
.newRWL(
moPropen,
moMain,
responseType,
data,
response,
txName,
lambdas,
cvFolds,
surrogate,
guess,
kernel,
fSet,
suppress,
...
)An RWL object
modelObj for propensity modeling
modelObj for main effects
Character indicating type of response
data.frame of covariates
vector of responses
treatment variable column header in data
tuning parameter(s)
number of cross-validation folds
Surrogate object
optional numeric vector providing starting values for optimization methods
Kernel object
Function or NULL defining subsets
T/F indicating if prints to screen are executed
Additional inputs for optimization