convergenceDiagnostics: Diagnose convergence of EMLasso.lognet objects

Description Usage Arguments Value Author(s) Examples

View source: R/convergenceDiagnostics.R

Description

Diagnose convergence of EMLasso.lognet objects

Usage

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  convergenceDiagnostics(model, minIt = 10,
    checkConvergence = checkConvergence.glmnet, ...,
    verbosity = 0)

Arguments

model

model fit (should be the result of EMLasso)

minIt

check convergence from this iteration on

checkConvergence

method, normally checkConvergence.glmnet, that checks convergence.

...

passed on to checkConvergence

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

list with one item per lambda. Each item is a list with items:

numit

number of iterations until convergence for this lambda

simpleconv

for all iterations from minIt to the last one used, whether or not convergence occurred

changedNonZeroness

for all iterations from minIt to the last one used, the variable names for which zeroness is different from the last iteration

Author(s)

Nick Sabbe nick.sabbe@ugent.be

Examples

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y<-rbinom(nrow(iris), 1, 0.5)
require(addendum)
require(NumDfr)
require(GLoMo)
require(snowfall)
require(EMLasso)
sfInit(parallel = FALSE, cpus = 1)
sfLibrary(addendum)
sfLibrary(NumDfr)
sfLibrary(GLoMo)
sfLibrary(EMLasso)
iris.cpy<-randomNA(iris, n=0.1)
iris.emlognet<-EMLasso(ds=numdfr(iris.cpy), out=y,
	lambdas=c(0.03,0.002,0.0003), nrOfSamplesPerMDRow=7, verbosity=2,
	convergenceChecker=convergenceCheckCreator(minIt=5, maxIt=10))
sfStop()
convergenceDiagnostics(iris.emlognet, minIt=2, verbosity=1)

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