Statistics Toolbox

rstool

Interactive fitting and visualization of a response surface

Syntax

• rstool(x,y)
  rstool(x,y,model)
  rstool(x,y,model,alpha,'xname','yname')
  

Description

rstool(x,y) displays an interactive prediction plot with 95% global confidence intervals. This plot results from a multiple regression of (x,y) data using a linear additive model.

rstool displays a "vector" of plots, one for each column of the matrix of inputs x. The response variable, y, is a column vector that matches the number of rows in x.

rstool(x,y,model) enables you to control the initial regression model, where model can be one of the following strings:

• 'linear' - includes constant and first order terms only
• 'purequadratic' - includes constant, linear and squared terms
• 'interaction' - includes constant, linear, and cross product terms
• 'quadratic' - includes interactions and squared terms

Alternatively, model can be a matrix of model terms as accepted by the x2fx function. See x2fx for a description of this matrix and for a description of the order in which terms appear.

rstool(x,y,model,alpha) plots 100(1 - alpha)% global confidence interval for predictions as two red curves. For example, alpha = 0.01 gives 99% confidence intervals.

rstool(x,y,model,alpha,'xname','yname') labels the graph using the string matrix 'xname' for the labels to the x-axes and the string, 'yname', to label the y-axis common to all the plots.

Drag the dashed blue reference line and watch the predicted values update simultaneously. Alternatively, you can get a specific prediction by typing the value of x into an editable text field. Use the pop-up menu to interactively change the model. Click the Export button to move specified variables to the base workspace.

Example

See Quadratic Response Surface Models.

See Also

nlintool, x2fx

rsmdemo

schart