Modeling and Multivariate Methods - SAS

100 Fitting Standard Least Squares Models Chapter 3
Row Diagnostics
Save Specific
Transformation
Table of Estimates
Prompts you for a lambda value and then does the same thing as the Save
Best Transformation.
Creates a new data table containing parameter estimates and SSE for all
values of λ from -2 to 2.
Row Diagnostics
Plot Regression
Plot Actual by
Predicted
Plot Effect Leverage
Plot Residual By
Predicted
Plot Residual By Row
Press
Produces a regression plot of the response and the continuous X variable. If
there is exactly one continuous term in a model, and no more than one
categorical term, then JMP plots the regression line (or lines).
Displays the observed values by the predicted values of Y. This is the leverage
plot for the whole model. See “Leverage Plots” on page 101.
Produces a leverage plot for each effect in the model showing the
point-by-point composition of the test for that effect. See “Leverage Plots”
on page 101.
Displays the residual values by the predicted values of Y. You typically want
to see the residual values scattered randomly about zero.
Displays the residual value by the row number of its observation.
Displays a Press statistic, which computes the residual sum of squares where
the residual for each row is computed after dropping that row from the
computations. The Press statistic is the total prediction error sum of squares
and is given by
Press
n
= ( ŷ () i – y i
) 2
i = 1
where n is the number of variables in the model, y i is the observed response
value of the i th observation, and
ŷ is the predicted response value of the omitted observation.
() i
The Press RMSE is defined as Press ⁄ n .
The Press statistic is useful when comparing multiple models. Models with
lower Press statistics are favored.