Models: Return data.table with model fits for prior probabilities.

In david-salgado/categObsPredModelParam: Class and methods for the parameters of a categorical observation- prediction model

Description

Models computes model fits for prior probabilities for each value or a specific value of the regressand and a specific formula.

Usage

Models(formula, data, id.vars, targetValue = "", maxit, suffix = "_ed")

Arguments

formula	an object of class formula (or one that can be coerced to that class): a symbolic description of the model to be fitted. The details of model specification are given under ‘Details’.
data	data frame, list or environment (or object coercible by as.data.table to a data.table) containing the variables in the model (see 'Details').
id.vars	names of the identification variables for each unit in the input data set data.
targetValue	value of the regressand (an object of class character).
maxit
suffix	parameter for the name of the edited version of the variable under analysis.

Value

A data.table with four colums named with the LHS variable of formula, fit.pi, fit.1 and fit.0. The first column contains every single value of this variable in the input data set data. The second, third and fourth columns contain a glm object with the fit of the model for each variable value.

david-salgado/categObsPredModelParam documentation built on Dec. 3, 2020, 1:42 p.m.