linear.model: Linear Model summarizer

In Chaiji/LemilExamST522:

Description

This function takes as argument a formula with a certain syntax, dependent~predictor1+predictor2+...+predictorN, And returns a list of information including residuals and coefficients(Estimate, standard error, t-value, Pr(>|t|)) in data.frames, as well as the residual standard error, degrees of freedom, Multiple R-squared, Adjusted R-squared, F-statistic and the p-value.

Usage

linear.model(formula)

Arguments

formula

is an argument of the type 'language' that apply the syntax: dependent~predictor1+predictor2+...+predictorN

Value

Returns a list containing: a vector of residuals, a single value for Residual Standard Error, single value for R-squared, single value for adjusted R-squared, single value for F-statistic, single value for degrees of freedom, single value for p-value, And a data.frame of coefficients(Estimates, standard error, t-value, PR(>|t|))

Author(s)

Nguyen Khanh Le Ho & Emil H. Andersen
Department of Mathematics and Computer Science (IMADA)
University of Southern Denmark, Denmark
[e-mail]
[e-mail]

Examples

linear.model(cars$speed~cars$dist)
linear.model(cars$speed~cars$dist+I(cars$dist^2))
linear.model(cars$speed~cars$dist+I(cars$dist^2)+I(cars$dist*cars$dist*cars$dist))

Chaiji/LemilExamST522 documentation built on May 6, 2019, 9:55 a.m.