Bootstrap Con dence Intervals for Smoothing Splines and theirComparison to Bayesian ` Con dence Intervals ' 1
نویسنده
چکیده
We construct bootstrap conndence intervals for smoothing spline and smoothing spline ANOVA estimates based on Gaussian data, and penalized likelihood smoothing spline estimates based on data from exponential families. Several variations of bootstrap conndence intervals are considered and compared. We nd that the commonly used bootstrap percentile intervals are inferior to the T intervals and to intervals based on bootstrap estimation of mean squared errors. The best variations of the bootstrap conndence intervals behave similar to the well known Bayesian conndence intervals. These bootstrap conndence intervals have an average coverage probability across the function being estimated, as opposed to a pointwise property.
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