Specifying an Expectation Function - Nonlinear Regression
main topic
    
 

You must enter the function that you expect describes the relationship between the predictor(s) and response variable. You can either specify an existing expectation function in the catalog or specify a new function.

If you specify a new function, it must contain at least one of each of the three basic components:

·    Parameters Minitab estimates parameters by fitting the expectation function to the data using an iterative algorithm that minimizes the sum of the squared residuals (SSE). In the function, enter text that does not match a column name or a mathematical operation to indicate a parameter. For example, you can enter b1, b2, Theta1, Theta2, and so on.

·    Predictors Variables that you enter in worksheet columns. Enter the column name in the function. If the name contains more than one word, use single quotes (e.g. 'Density Ln')

·    Mathematical operations and functions Specify the mathematical relationship between the parameters and predictors that produces the expected value of the response variable. You can use the Nonlinear Regression Calculator to easily enter the operations and functions (for example, *, +, COS, EXP, and so on). Or, you can type them directly into the Edit directly text box.

The following examples from the expectation function catalog are acceptable functions. Thetas represent parameters and X's represent predictors. You replace the X's with the variable names. Each time you perform nonlinear regression using a new function, Minitab automatically adds the function to the catalog.

Expectation function

Model name

Model contains

1 / (1 + Theta *X )

Convex 1

One parameter and one predictor

Theta1* X / ( Theta2 + X )

Michaelis-Menten

Two parameters and one predictor

Theta1 * cos ( X + Theta4 ) + Theta2 * cos ( 2 * X + Theta4 ) + Theta3

Fourier 1

Four parameters and one predictor

Theta1 - Theta2 * ( ln ( X1 + Theta3 ) - ln ( X2 ) )

Nernst equation

Three parameters and 2 predictors

X1 * X2 / ( Theta1 + Theta2 * X1 + Theta3 * X1 * X2 + Theta4 * X1 * X3 )

Enzyme reaction

Four Parameters and 3 predictors