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Visual Statistics Procedures
 

The NLMOD Procedure

Least Squares Estimation

Models that are estimated by PROC NLMOD can be represented by using the equations

where

bold upper Y

is the left-parenthesis n times 1 right-parenthesis vector of observed responses.

bold f

is the nonlinear prediction function of parameters and regressor variables.

bold-italic beta

is the vector of model parameters to be estimated.

bold z 1 comma ellipsis comma bold z Subscript k Baseline

are the left-parenthesis n times 1 right-parenthesis vectors of each of the k regressor variables.

bold-italic epsilon

is the left-parenthesis n times 1 right-parenthesis vector of residuals.

sigma squared

is the variance of the residuals.

In these models, the distribution of the residuals is not specified and the model parameters are estimated using the least squares method. For the standard errors and confidence limits in the "ParameterEstimates" table to apply, the errors are assumed to be homoscedastic and uncorrelated and to have zero mean.

Last updated: April 08, 2021