Abstract #301265

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JSM 2003 Abstract #301265
Activity Number: 339
Type: Contributed
Date/Time: Wednesday, August 6, 2003 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Graphics
Abstract - #301265
Title: Visualization and Diagnostics of Nonlinear Statistical Models
Author(s): Barbara Ann Bailey*+
Companies: University of Illinois at Urbana-Champaign
Address: 725 S Wright St., Champaign, IL, 61820-5710,
Keywords: nonlinear least squares ; visualization
Abstract:

Nonlinear statistical models arise in many areas of research in a wide range of disciplines. The least squares principle is used to estimate the parameters in nonlinear models and iterative numerical methods are used to find the set of parameters that minimize the residual sum of squares surface. Nonlinear least squares regression problems are intrinsically hard, and it is generally possible to find a dataset that will defeat even the most robust numerical codes. We integrate diagnostics of nonlinear regression fitting procedures and visualization of multidimensional parameter spaces to educate and provide insight for fitting nonlinear models. Visualization of the residual sum of squares surface involves the construction of contour and perspective plots with the appropriate slicing and projection of the multidimensional parameter space to provide insight into the location and function value of local minimum of the residual sum of squares surface. A graphical display and visualization of likelihood based inference of model parameters is also useful.

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