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

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Documentation for package ‘EMLasso’ version 2.0.9

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A C E F G I L M N O P R S T U V misc

EMLasso-package EM (logistic) LASSO

-- A --

acceptOrRejectFunction Complete a dataset conditional on a model and the outcomes
acceptOrRejectFunction.default Complete a dataset conditional on a model and the outcomes
acceptOrRejectFunction.lognet Complete a dataset conditional on a model and the outcomes

-- C --

checkConvergence.glmnet Check whether convergence has occurred in the zeroness of coefficients
collectImputationModels Collect data from a model, needed for multiple imputation based on this model
collectImputationModels.EMLassoGLoMo Collect data from a model, needed for multiple imputation based on this model
completeMarginal Wrapper to complete a dataset based on (univariate) marginal distributions
completeMarginal.default Wrapper to complete a dataset based on (univariate) marginal distributions
completeMarginal.function Wrapper to complete a dataset based on (univariate) marginal distributions
constButWarnFunction Reusable information to convert an imputed dataset to fitting form
convergenceCheckCreator Check whether convergence has occurred in the zeroness of coefficients
convergenceDiagnostics Diagnose convergence of EMLasso.lognet objects
crossValidate Crossvalidate a model
crossValidate.EMLassoGLoMo Crossvalidate a model
cv.EMLasso.lognet Crossvalidate a model
cv.EMLassoGLoMo-class Crossvalidate a model
cv.MI.logreg Crossvalidate a model
cv.MI.logreg-class Crossvalidate a model

-- E --

EMLasso Fit EMLasso to a complete dataset, creating a GLoMo for each lambda
EMLasso-class Fit EMLasso to a complete dataset, creating a GLoMo for each lambda
EMLasso.1l Fit EMLasso for 1 lambda
EMLasso.1l.param Collect parameters to EMLasso.1l into one list
EMLasso.glmnet Fit EMLasso to a complete dataset, creating a GLoMo for each lambda
EMLasso.glmnet-class Fit EMLasso to a complete dataset, creating a GLoMo for each lambda
EMLasso.lognet Fit EMLasso to a complete dataset, creating a GLoMo for each lambda
EMLasso.lognet-class Fit EMLasso to a complete dataset, creating a GLoMo for each lambda
EMLasso1l Fit EMLasso for 1 lambda
EMLasso1l-class Fit EMLasso for 1 lambda
EMLassoFromDir Get EMLasso from the save files in a folder
EMLassoGLoMo Postprocess EMLasso (e.g. add extra members or change class)
EMLassoGLoMo-class Postprocess EMLasso (e.g. add extra members or change class)
EMLassoGLoMoImputationData Collect data from a model, needed for multiple imputation based on this model
EMLassoGLoMoImputationData-class Collect data from a model, needed for multiple imputation based on this model

-- F --

findReasonableLambdaHelper Function to run on a dataset with not too much missing data to identify a set of reasonable lambda values
fit.glmnet Tailormade weighted fitting of logistic glmnet
fit.lognet Tailormade weighted fitting of logistic glmnet
fit.logreg Fit logistic regression by using logistic LASSO with lambda=0

-- G --

getLambdas Function to run on a dataset with not too much missing data to identify a set of reasonable lambda values
getLambdas.LambdaHelper Function to run on a dataset with not too much missing data to identify a set of reasonable lambda values
getLambdas.lambdaregion Function to run on a dataset with not too much missing data to identify a set of reasonable lambda values
getMinMaxPosLikeGlmnet Find a region of interest in a set of lambdas given criteria and their SE
getMinMaxPosLikeGlmnet.cv.glmnet Find a region of interest in a set of lambdas given criteria and their SE
getMinMaxPosLikeGlmnet.default Find a region of interest in a set of lambdas given criteria and their SE
getSafeFunction Reusable information to convert an imputed dataset to fitting form
getSafeFunction.default Reusable information to convert an imputed dataset to fitting form
getSafeFunction.unsafefunction Reusable information to convert an imputed dataset to fitting form
getUnsafeFunction Reusable information to convert an imputed dataset to fitting form
getUnsafeFunction.default Reusable information to convert an imputed dataset to fitting form
getUnsafeFunction.unsafefunction Reusable information to convert an imputed dataset to fitting form

-- I --

illegals2Null Reusable information to convert an imputed dataset to fitting form
illegalsCalculatedConstCountered Reusable information to convert an imputed dataset to fitting form
illegalsCountered Reusable information to convert an imputed dataset to fitting form
illegalToSmryLegalFunction Reusable information to convert an imputed dataset to fitting form
imputeDs2FitDs Reusable information to convert an imputed dataset to fitting form
imputeDs2FitDs.default Reusable information to convert an imputed dataset to fitting form
imputeDs2FitDs.dfrConversionProps Reusable information to convert an imputed dataset to fitting form
imputeDs2FitDs.dfrConversionPropsEx Reusable information to convert an imputed dataset to fitting form
imputeDs2FitDsProps Reusable information to convert an imputed dataset to fitting form
imputeDs2FitDsProps.default Reusable information to convert an imputed dataset to fitting form
imputeDs2FitDsProps.normalImputationConversion Reusable information to convert an imputed dataset to fitting form
interactionAdderAllNonSelf Reusable information to convert an imputed dataset to fitting form
isIllegal Reusable information to convert an imputed dataset to fitting form

-- L --

length.EMLasso.1l.param Collect parameters to EMLasso.1l into one list
lognetProbabilityReusable Function to help calculate predicted probability of a lognet fit
logregLikeGlmnet Fit logistic regression by using logistic LASSO with lambda=0

-- M --

marginalCompleted Wrapper to complete a dataset based on (univariate) marginal distributions
marginalCompleted-class Wrapper to complete a dataset based on (univariate) marginal distributions
marginalCompleter Wrapper to complete a dataset based on (univariate) marginal distributions

-- N --

newIllegals Reusable information to convert an imputed dataset to fitting form
normalImputationConversion Reusable information to convert an imputed dataset to fitting form
normalImputationConversion-class Reusable information to convert an imputed dataset to fitting form

-- O --

outcomeModelValidationReusables Create reusable part of validation (for rejection sampling)
outcomeModelValidationReusables.default Create reusable part of validation (for rejection sampling)
outcomeModelValidationReusables.lognet Create reusable part of validation (for rejection sampling)

-- P --

plotCoefConvergence Plot coefficient evolution of EMLasso.lognet objects
postProcessEMLasso Postprocess EMLasso (e.g. add extra members or change class)
postProcessEMLasso.default Postprocess EMLasso (e.g. add extra members or change class)
postProcessEMLasso.GLoMo Postprocess EMLasso (e.g. add extra members or change class)
postProcessEMLasso1l Postprocess EMLasso for 1 lambda result (e.g. add extra members or change class)
postProcessEMLasso1l.default Postprocess EMLasso for 1 lambda result (e.g. add extra members or change class)
postProcessEMLasso1l.lognet Postprocess EMLasso for 1 lambda result (e.g. add extra members or change class)
predict.EMLassoGLoMoImputationData Collect data from a model, needed for multiple imputation based on this model
predictorModelSamplingReusables Create reusable part of prediction for repeated sampling
predictorModelSamplingReusables.GLoMo Create reusable part of prediction for repeated sampling
predictProb predict probabilities
predictProb.lognetProbabilityReusable predict probabilities
print.unsafefunction Reusable information to convert an imputed dataset to fitting form

-- R --

removeIllegals Reusable information to convert an imputed dataset to fitting form
removeScaling Reusable information to convert an imputed dataset to fitting form
removeScaling.default Reusable information to convert an imputed dataset to fitting form
removeScaling.dfrConversionPropsEx Reusable information to convert an imputed dataset to fitting form
repeatedlyPredictOut Crossvalidate a model
repeatedPredictedProbAUC Crossvalidate a model
retrieveLambdas Retrieve lambdas
retrieveLambdas.default Retrieve lambdas
retrieveLambdas.smartLambdaRetriever Retrieve lambdas

-- S --

sampleConditional Complete a dataset conditional on a model and the outcomes
sampleConditional.GLoMo Complete a dataset conditional on a model and the outcomes
sampledConditionally Complete a dataset conditional on a model and the outcomes
sampledConditionally-class Complete a dataset conditional on a model and the outcomes
sampledConditionallyGLomo Complete a dataset conditional on a model and the outcomes
sampledConditionallyGLomo-class Complete a dataset conditional on a model and the outcomes
SamplingReusablesGLoMo Create reusable part of prediction for repeated sampling
SamplingReusablesGLoMo-class Create reusable part of prediction for repeated sampling
setDebugmodeEMLasso Set tracing of all calls on/off
simplyValidate Validate a model (to its original data)
simplyValidate.EMLassoGLoMo Validate a model (to its original data)
smartLambdaRetriever Retrieve lambdas
smartLambdaRetriever-class Retrieve lambdas
specialLegalX Reusable information to convert an imputed dataset to fitting form
sv.EMLasso.lognet Validate a model (to its original data)
sv.EMLassoGLoMo-class Validate a model (to its original data)

-- T --

thresHolding Simple threshold selection for some sets of variables selected by EMLasso
typicalScaleAndCenter Reusable information to convert an imputed dataset to fitting form
typicalTransformations Reusable information to convert an imputed dataset to fitting form

-- U --

unsafefunction Reusable information to convert an imputed dataset to fitting form
unsafefunction-class Reusable information to convert an imputed dataset to fitting form

-- V --

validateFunction.lognet validation function for use in 'predict.conditional.allrows.GLoMo'

-- misc --

[.EMLasso.1l.param Collect parameters to EMLasso.1l into one list
[.LambdaHelper Function to run on a dataset with not too much missing data to identify a set of reasonable lambda values