Abstract Details
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Activity Number:
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597
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Type:
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Contributed
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Date/Time:
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Wednesday, August 7, 2013 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Nonparametric Statistics
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| Abstract - #308468 |
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Title:
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Bootstrap Confidence Bands for Regression Curves Using Polynomial Splines
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Author(s):
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Ella Revzin*+ and Jing Wang and Lijian Yang
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Companies:
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and University of Illinois at Chicago and Michigan State University
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Keywords:
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Bootstrap ;
Confidence Band ;
Splines ;
Nonparametric Regression
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Abstract:
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Confidence regions for regression estimates are a simple way to assess model fit and perform goodness of fit tests. In this work, we construct simultaneous confidence bands for a univariate regression model using a Wild bootstrap of polynomial spline estimates. The bands vary in width at each point of the predictor variable and are not constrained to be symmetric. We show that the bootstrap bands are valid for heteroscedastic errors and have the correct asymptotic coverage probabilities. We illustrate our method with Monte Carlo simulations and an empirical study.
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Authors who are presenting talks have a * after their name.
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