Variance analysis for kernel smoothing of a varying-coefficient model with longitudinal data
- UNCW Author/Contributor (non-UNCW co-authors, if there are any, appear on document)
- Jinsong Chen (Creator)
- Institution
- The University of North Carolina Wilmington (UNCW )
- Web Site: http://library.uncw.edu/
Abstract: We consider the estimation of the k + 1-dimensional nonparametric component (t) of
the varying-coefficient model Y (t) = XT (t) (t) + "(t) based on longitudinal observation
(Yij ,Xi(tij), tij), i = 1, ..., n, j = 1, ..., ni, where tij is the jth observed design time
point t of the ith subjects at tij . The subjects are independently selected, but the repeated
measurements within subject are possibly correlated.A Monte Carlo Simulation was established,
kernel smoothing method was used to estimate (t) that minimizes a local least
square criterion. The distribution for "(t) was analyzed. The degree of freedom was
investigated.
Variance analysis for kernel smoothing of a varying-coefficient model with longitudinal data
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Created on 1/1/2009
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Additional Information
- Publication
- Thesis
- A Thesis Submitted to the University of North Carolina at Wilmington in Partial Fulfillment Of the Requirements for the Degree of Master of Arts
- Language: English
- Date: 2009
- Keywords
- Functional analysis, Kernel functions, Monte Carlo method, Nonparametric statistics
- Subjects
- Kernel functions
- Monte Carlo method
- Nonparametric statistics
- Functional analysis