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Department of Statistics

STAT 715

715—Nonlinear Statistical Models. (3) (Prereq: STAT 714 or consent of instructor) Violations of classical regression assumptions; nonlinear models for univariate response; generalized least squares; generalized nonlinear models; quasilikelihood; modeling nonconstant variance; linear and quadratic estimating equations; multivariate response; nonlinear mixed models.

Usually Offered: Even Numbered Falls

Purpose: To provide a rigorous analytical treatment of nonlinear regression models and associated inferential methods for both univariate and multivariate response.

Current Textbook: Consult instructor.

 

Topics Covered Time        
Classical linear regression and departures 1 week
Nonlinear models and generalized least squares 2 weeks
Generalized nonlinear models 1 week
Maximum likelihood and variance modeling 3 weeks
Large sample results 2 weeks
Optimality issues 2 weeks
Nonlinear models for multivariate response 3 weeks

The above textbook and course outline should correspond to the most recent offering of the course by the Statistics Department. Please check the current course homepage or with the instructor for the course regulations, expectations, and operating procedures.

Contact Faculty: Joshua Tebbs


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