Creating a linear regression model
In the previous section, we adopted an algebraic approach to calculating the regression line. More generally, to create a linear regression model, we use the lm()
function. This function creates a LinearModel
object. The object of class lm
has a series of properties that can be immediately viewed by simply clicking on it. These types of objects can be used for residual analysis and regression diagnosis.
Note
LinearModel
is an object comprised of data, model description, diagnostic information, and fitted coefficients for a linear regression.
Models for the lm()
function are specified symbolically. In fact, the first argument of the function is an object of class formula
. A typical formula
object has the following form:
response ~ terms
response
represents the (numeric) response vector and terms
is a series of terms specifying a linear predictor for response. Let us take a look at a terms specification of the following form:
A + B
This indicates all the terms...