One of the most common statistical models is the linear regression model. A linear model predicts the value of a response variable by the linear combination of predictor variables or functions of predictor variables. In
Mathematica,
LinearModelFit returns an object that contains fitting information for a linear regression model and allows for easy extraction of results and diagnostics.
Use
LinearModelFit to construct a linear model for the data:
Extract the functional form of the model:
Plot the functional form of the model:
Show the data and the line of best fit:
Obtain information about the parameter estimates:
Extract and plot the standardized residuals and fit residuals:
Plot the Cook distances by observation number:
Alternatively, plot the Cook distances versus predictor value:
The previous examples demonstrated a selection of properties supported by
LinearModelFit; many more are available:
