postProcessEMLasso1l: Postprocess EMLasso for 1 lambda result (e.g. add extra...

In EMLasso: Fit (logistic) LASSO when there is missing data in the predictors

Description

Postprocess EMLasso for 1 lambda result (e.g. add extra members or change class)

Usage

  postProcessEMLasso1l(outcomeModel, retval, lastData,
    imputeDs2FitDsProperties, reusableForSampling,
    reusableForvalidation, verbosity = 0)

  ## Default S3 method:
postProcessEMLasso1l(outcomeModel,
    retval, lastData, imputeDs2FitDsProperties,
    reusableForSampling, reusableForvalidation,
    verbosity=0)

  ## S3 method for class 'lognet'
postProcessEMLasso1l(outcomeModel,
    retval, lastData, imputeDs2FitDsProperties,
    reusableForSampling, reusableForvalidation,
    verbosity=0)

Arguments

outcomeModel	the final outcome model will be passed in here (e.g. glmnet object)
retval	the return value of EMLasso.1l to be postprocessed
lastData	dataset (completed) from the last EM iteration
imputeDs2FitDsProperties	see imputeDs2FitDs
reusableForSampling	Which of the rows of dfr/resp can be used for fitting the LASSO
reusableForvalidation	minimum number of iterations before convergence is possible
verbosity	The higher this value, the more levels of progress and debug information is displayed (note: in R for Windows, turn off buffered output)

Value

Typically the passed along retval object with optionally some more items/class/attributes

Author(s)

Nick Sabbe [e-mail]

See Also

EMLasso.1l

EMLasso documentation built on May 2, 2019, 5:49 p.m.