lbc_train: Train a Logistic Box-Cox model

In ubclxing/lboxcox: Implementation of Logistic Box-Cox Regression

Train a Logistic Box-Cox model

Description

Train the given formula using a Logistic Box-Cox model.

Usage

lbc_train(
  formula,
  weight_column_name,
  data,
  init = NULL,
  svy_lambda_vector = seq(0, 2, length = 100),
  num_cores = 1
)

Arguments

formula	a formula of the form y ~ x + z1 + z2 where y is a binary response variable, x is a continuous predictor variable, and z1, z2, ... are covariates
weight_column_name	the name of the column in 'data' containing the survey weights.
data	dataframe containing the dataset to train on
init	initial estimates for the coefficients. If NULL the svyglm model will be used
svy_lambda_vector	values of lambda used in training svyglm model. Best model is used for initial coefficient estimates. If init is not NULL this parameter is ignored.
num_cores	the number of cores used when finding the best svyglm model. If init is not NULL this parameter is ignored.

Value

object of class 'maxLik' from the 'maxLik' package. Contains the coefficient estimates that maximizes likelhood among other statistics.

Note

This is reliant on the following work:

Henningsen, A., Toomet, O. (2011). maxLik: A package for maximum likelihood estimation in R. Computational Statistics, 26(3), 443-458.

Microsoft Corporation, Weston, S. (2020). foreach: Provides Foreach Looping Construct. R package version 1.5.1.

Microsoft Corporation, Weston, S. (2020). doParallel: Foreach Parallel Adaptor for the 'parallel' Package. R package version 1.0.16.

ubclxing/lboxcox documentation built on Sept. 1, 2022, 9:09 a.m.