validateFunction.lognet: validation function for use in...
In EMLasso: Fit (logistic) LASSO when there is missing data in the predictors

Description Usage Arguments Value Note Author(s) See Also

View source: R/validateFunction.lognet.R

'Validates' samples in the rejection sampling way, by checking the predicted probability in the logistic LASSO

1 2	validateFunction.lognet(attempts, otherData, forrow, verbosity = 0)

`attempts`	`numdfr` or `data.frame` holding the rows to validate (sampled from GLoMo)
`otherData`	extra data that will be passed in. Required to be of class `LognetValidationData`
`forrow`	to which original row of the dataset do these predictions belong
`verbosity`	The higher this value, the more levels of progress and debug information is displayed (note: in R for Windows, turn off buffered output)

integer vector of indices of accepted rows (within attempts)

noticed here that you need a way to map forrow (that is a rowindex in the original dataset) to an item in otherData. This will not be an issue if forrows that is passed to predict.conditional.allrows.GLoMo is really all rows, otherwise (then otherData will likely only hold items only for every selected row) you need more info...

really only used internally from EMLasso.1l

Nick Sabbe nick.sabbe@ugent.be

predict.conditional.allrows.GLoMo, EMLasso.1l

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