lambda_fun: Title: Getting betas use the max(beta, 1)

In Goodgolden/LDTM: Longitudinal Dirichlet Tree Multinomial Model

Title: Getting betas use the max(beta, 1)

Description

Title: Getting betas use the max(beta, 1)

Usage

lambda_fun(grad, L, alpha, lambda)

Arguments

grad	the gradient descent
L	numeric Lipschitz constant, instead of choosing a constant step size L. We can use the backtracking to choose a suitable L at each iteration. Note: This is noted at C in Tao Wang and Hongyu Zhao (2017)
alpha	numeric the desired lasso parameter. In paper they used (0, 0.25, 0,5, and 1) to investigate the covariate selection. Note: In the paper they noted this as Gamma
lambda	numeric the tuning parameter

Details

This function is looking to maximize the beta matrix

Value

The updated Beta matrix obtained from the algortihm

Goodgolden/LDTM documentation built on May 25, 2022, 5:25 p.m.