Non-Smooth Regularization for Structural Equation Models

Documentation for package ‘lessSEM’ version 1.5.5

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-- A --

-- B --

bfgs	bfgs
bfgsEnet	smoothly approximated elastic net
bfgsEnetMgSEM	smoothly approximated elastic net
bfgsEnetSEM	smoothly approximated elastic net
BIC-method	BIC
BIC-method	BIC
BIC-method	BIC
BIC-method	BIC
BIC-method	BIC

-- C --

callFitFunction	callFitFunction
cappedL1	cappedL1
coef-method	coef
coef-method	coef
coef-method	coef
coef-method	coef
coef-method	coef
coef-method	coef
controlBFGS	controlBFGS
controlGlmnet	controlGlmnet
controlIsta	controlIsta
covariances	covariances
createSubsets	createSubsets
curveLambda	curveLambda
cvAdaptiveLasso	cvAdaptiveLasso
cvCappedL1	cvCappedL1
cvElasticNet	cvElasticNet
cvLasso	cvLasso
cvLsp	cvLsp
cvMcp	cvMcp
cvRegularizedSEM-class	Class for cross-validated regularized SEM
cvRidge	cvRidge
cvRidgeBfgs	cvRidgeBfgs
cvScad	cvScad
cvScaler	cvScaler
cvSmoothAdaptiveLasso	cvSmoothAdaptiveLasso
cvSmoothElasticNet	cvSmoothElasticNet
cvSmoothLasso	cvSmoothLasso

-- E --

elasticNet	elasticNet
estimates	S4 method to exract the estimates of an object
estimates-method	estimates
estimates-method	estimates
estimates-method	estimates

-- F --

fit	fit
fitIndices	S4 method to compute fit indices (e.g., AIC, BIC, ...)
fitIndices-method	fitIndices
fitIndices-method	fitIndices
fitIndices-method	fitIndices

-- G --

getLavaanParameters	getLavaanParameters
getTuningParameterConfiguration	getTuningParameterConfiguration
glmnetCappedL1MgSEM	CappedL1 optimization with glmnet optimizer
glmnetCappedL1SEM	CappedL1 optimization with glmnet optimizer
glmnetEnetGeneralPurpose	elastic net optimization with glmnet optimizer
glmnetEnetGeneralPurposeCpp	elastic net optimization with glmnet optimizer
glmnetEnetMgSEM	elastic net optimization with glmnet optimizer
glmnetEnetSEM	elastic net optimization with glmnet optimizer
glmnetLspMgSEM	lsp optimization with glmnet optimizer
glmnetLspSEM	lsp optimization with glmnet optimizer
glmnetMcpMgSEM	mcp optimization with glmnet optimizer
glmnetMcpSEM	mcp optimization with glmnet optimizer
glmnetMixedMgSEM	mixed optimization with glmnet optimizer
glmnetMixedPenaltyGeneralPurpose	mixed optimization with glmnet optimizer
glmnetMixedPenaltyGeneralPurposeCpp	mixed optimization with glmnet optimizer
glmnetMixedSEM	mixed optimization with glmnet optimizer
glmnetScadMgSEM	scad optimization with glmnet optimizer
glmnetScadSEM	scad optimization with glmnet optimizer
gpAdaptiveLasso	gpAdaptiveLasso
gpAdaptiveLassoCpp	gpAdaptiveLassoCpp
gpCappedL1	gpCappedL1
gpCappedL1Cpp	gpCappedL1Cpp
gpElasticNet	gpElasticNet
gpElasticNetCpp	gpElasticNetCpp
gpLasso	gpLasso
gpLassoCpp	gpLassoCpp
gpLsp	gpLsp
gpLspCpp	gpLspCpp
gpMcp	gpMcp
gpMcpCpp	gpMcpCpp
gpRegularized-class	Class for regularized model using general purpose optimization interface
gpRidge	gpRidge
gpRidgeCpp	gpRidgeCpp
gpScad	gpScad
gpScadCpp	gpScadCpp

-- I --

istaCappedL1mgSEM	cappedL1 optimization with ista
istaCappedL1SEM	cappedL1 optimization with ista
istaEnetGeneralPurpose	elastic net optimization with ista
istaEnetGeneralPurposeCpp	elastic net optimization with ista
istaEnetMgSEM	elastic net optimization with ista optimizer
istaEnetSEM	elastic net optimization with ista optimizer
istaLSPMgSEM	lsp optimization with ista
istaLSPSEM	lsp optimization with ista
istaMcpMgSEM	mcp optimization with ista
istaMcpSEM	mcp optimization with ista
istaMixedPenaltyGeneralPurpose	mixed penalty optimization with ista
istaMixedPenaltyGeneralPurposeCpp	mixed penalty optimization with ista
istaMixedPenaltymgSEM	mixed penalty optimization with ista
istaMixedPenaltySEM	mixed penalty optimization with ista
istaScadMgSEM	scad optimization with ista
istaScadSEM	scad optimization with ista

-- L --

lasso	lasso
lavaan2lslxLabels	lavaan2lslxLabels
lessSEM2Lavaan	lessSEM2Lavaan
lessSEMCoef-class	Class for the coefficients estimated by lessSEM.
loadings	loadings
logicalMatch	logicalMatch
logLik-method	logLik
logLik-method	logLik
logLikelihood-class	Class for log-likelihood of regularized SEM. Note: we define a custom logLik - Function because the generic one is using df = number of parameters which might be confusing.
lsp	lsp

-- M --

-- N --

-- P --

plot-method	plots the cross-validation fits
plot-method	plots the regularized and unregularized parameters for all levels of lambda
plot-method	plots the regularized and unregularized parameters for all levels of lambda
plot-method	plots the regularized and unregularized parameters for all levels of the tuning parameters

-- R --

regressions	regressions
regsem2LavaanParameters	regsem2LavaanParameters
regularizedSEM-class	Class for regularized SEM
regularizedSEMMixedPenalty-class	Class for regularized SEM
ridge	ridge
ridgeBfgs	ridgeBfgs

-- S --

scad	scad
scadPenalty_C	scadPenalty_C
SEMCpp	SEMCpp class
show-method	show
show-method	show
show-method	Show method for objects of class 'cvRegularizedSEM'.
show-method	show
show-method	show
show-method	show
show-method	show
show-method	show
show-method	show
simulateExampleData	simulateExampleData
smoothAdaptiveLasso	smoothAdaptiveLasso
smoothElasticNet	smoothElasticNet
smoothLasso	smoothLasso
stabilitySelection	stabilitySelection
stabSel-class	Class for stability selection
summary-method	summary method for objects of class 'cvRegularizedSEM'.
summary-method	summary
summary-method	summary
summary-method	summary

-- V --

-- misc --