outcomeModelValidationReusables: Create reusable part of validation (for rejection sampling)

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

Description

Create reusable part of validation (for rejection sampling)

Usage

  outcomeModelValidationReusables(outcomeModel, ds, out,
    imputeDs2FitDsProperties, verbosity = 0)

  ## Default S3 method:
outcomeModelValidationReusables(outcomeModel,
    ds, out, imputeDs2FitDsProperties, verbosity=0)

  ## S3 method for class 'lognet'
outcomeModelValidationReusables(outcomeModel,
    ds, out, imputeDs2FitDsProperties, verbosity=0)

Arguments

outcomeModel	outcome model (e.g. glmnet)
ds	dataset for which validation needs to occur
out	outcomes for which validation needs to occur
imputeDs2FitDsProperties	see imputeDs2FitDs
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

a single logical (TRUE is convergence has happened or maxIt passed)

the result of basicCheckFunction

the result of basicCheckFunction

Note

the first row (initial estimates) and column (intercept) are skipped in the checks

Author(s)

Nick Sabbe [e-mail]

See Also

EMLasso.1l

EMLasso.1l

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