lessSEM (version 1.5.5)

fit: fit

Description

Optimizes an object with mixed penalty. See ?mixedPenalty for more details.

Usage

fit(mixedPenalty)

Value

throws error in case of undefined penalty combinations.

Arguments

mixedPenalty

object of class mixedPenalty. This object can be created with the mixedPenalty function. Penalties can be added with the addCappedL1, addElastiNet, addLasso, addLsp, addMcp, and addScad functions.

Examples

library(lessSEM)

# Identical to regsem, lessSEM builds on the lavaan
# package for model specification. The first step
# therefore is to implement the model in lavaan.

dataset <- simulateExampleData()

lavaanSyntax <- "
f =~ l1*y1 + l2*y2 + l3*y3 + l4*y4 + l5*y5 + 
     l6*y6 + l7*y7 + l8*y8 + l9*y9 + l10*y10 + 
     l11*y11 + l12*y12 + l13*y13 + l14*y14 + l15*y15
f ~~ 1*f
"

lavaanModel <- lavaan::sem(lavaanSyntax,
                           data = dataset,
                           meanstructure = TRUE,
                           std.lv = TRUE)

# We can add mixed penalties as follows:

regularized <- lavaanModel |>
  # create template for regularized model with mixed penalty:
  mixedPenalty() |>
  # add penalty on loadings l6 - l10:
  addElasticNet(regularized = paste0("l", 11:15), 
          lambdas = seq(0,1,.1),
          alphas = .4) |>
  # fit the model:
  fit()