Kernel Regression Estimation Using Repeated Measurements Data

The estimation of growth curves has been studied extensively in parametric situations. Here we consider the nonparametric estimation of an average growth curve. Suppose that there are observations from several experimental units, each following the regression model y(x i )=f(x j )+ε(j=1,...,n), wher...

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Bibliographic Details
Published in:Journal of the American Statistical Association 1986-12, Vol.81 (396), p.1080-1088
Main Authors: Hart, Jeffrey D., Wehrly, Thomas E.
Format: Article
Language:English
Subjects:
Analytical estimating
Citrates
Consistent estimators
Correlated data
Correlations
Data analysis
Error rates
Estimation methods
Estimators
Exact sciences and technology
Growth curves
Infinity
Linear inference, regression
Mathematics
Nonparametric regression
Optimum bandwidth
Probability and statistics
Sciences and techniques of general use
Statistics
Theory and Methods
Unbiased estimators
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Summary:The estimation of growth curves has been studied extensively in parametric situations. Here we consider the nonparametric estimation of an average growth curve. Suppose that there are observations from several experimental units, each following the regression model y(x i )=f(x j )+ε(j=1,...,n), where ε 1 , ..., ε n are correlated zero mean errors and 0≤x 1
ISSN:0162-1459
1537-274X
DOI:10.1080/01621459.1986.10478377