lboxcox (version 1.2)

lbc_train: 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
)

Value

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

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.