filter_lambda: Optimal lambda and corresponding final GLMM LASSO model

Description Usage Arguments Value

View source: R/filter_lambda.R

Description

Select the optimal lambda that minimizes BIC. The starting values of the parameters play an essential part in GLMM LASSO model fitting. We first consider glmmPQL fitted values. Then, we consider 0s for sparse signal scenario.

Usage

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filter_lambda(
  data,
  outcome,
  ID,
  lambdaseq,
  range = 0,
  family = gaussian(link = "identity"),
  startPQL = TRUE
)

Arguments

data

A long format complete data frame.

outcome

Outcome variable of interest.

ID

Name of the ID variable in the dataset.

lambdaseq

A vector of lambdas to consider.

range

The next lambda sequence to consider, given the best lambda from current lambdaseq.

family

Link function for the outcome.

startPQL

Logical. If TRUE initiate parameter estimates are generated from glmmPQL. IF FALSE, initiate parameter estimates are 0s.

Value


SOCR/DataSifterII documentation built on Dec. 15, 2021, 10:29 a.m.