my.lm: my.lm

In srhaup2/my.lm: Fits a Linear Model

Description

Fits a linear regression model using OLS or WLS

Usage

my.lm(formula, data, weights = NULL)

Arguments

formula	formula specifying the regression equation
data	n x p data.frame to be used to fit the model
weights	optional length n numeric vector to be used in a WLS regression

Value

A list containing regression results

• coefficients - beta coefficients

• residuals - observed minus fitted values

• fitted.values - expected outcomes based on regression coefficients

• mse - variance of the outcome

• se_beta - standard errors for the coefficients

• r2 - R-squared

• adj.r2 - adjusted R-squared

• t - t test statistics for each coefficient

• t.p.vals - p values for each coefficient

• f - f statistic for the model

• f.p.val - p value for the f statistic

• df.residual - degrees of freedom for SSE (n-p)

• n - number of observations

• p - number of mean parameters

• method - OLS or WLS depending on whether weights were specified

• weights - if weights provided as argument, this returns that argument

• formula - this returns the formula argument

• design.mat - design matrix used to fit the model

Examples

get(data(mtcars))

#OLS
my.fit = my.lm(mpg ~ cyl, data = mtcars)
my.fit$coefficients

#WLS
my.fit2 = my.lm(mpg ~ cyl, data = mtcars, weights = 1:32)
my.fit2$coefficients

srhaup2/my.lm documentation built on Dec. 23, 2021, 4:30 a.m.