multivariate_linear_regression: Multivariate Linear Regression

In UAHDataScienceSC: Learn Supervised Classification Methods Through Examples and Code

Multivariate Linear Regression

Description

Calculates and plots the linear regression of a given set of values. Being all of them independent values but one, which is the dependent value. It provides information about the process and intermediate values used to calculate the line equation.

Usage

multivariate_linear_regression(data, learn = FALSE, waiting = TRUE)

Arguments

data	x*y data frame with already classified observations. Each column represents a parameter of the values (independent variable). The last column represents the classification value (dependent variable). Each row is a different observation.
learn	Boolean value. If it is set to "TRUE" multiple clarifications and explanations are printed along the code
waiting	If TRUE while learn = TRUE. The code will stop in each "block" of code and wait for the user to press "enter" to continue.

Value

List containing a list for each independent variable, each one contains, the variable name, the intercept and the slope.

Author(s)

Víctor Amador Padilla, [e-mail]

Examples

# example code
multivariate_linear_regression(db1rl)

UAHDataScienceSC documentation built on April 3, 2025, 8:58 p.m.