Theoretical Comparison of Bootstrap Confidence Intervals

Theoretical Comparison of Bootstrap t Confidence Bounds

On Teaching Bootstrap Confidence Intervals

notion the theoretical distribution on the random variable ) is not available. All we have ICOTS8 (2010) Invited Paper Engel International Association of Statistical Education (IASE) www.stat.auckland.ac.nz/~iase/ to rely on are the data at hand, i.e. the sample or recapture of size n. These data–if drawn by some random mechanism–may well be taken as a good representation of the total fish popu...

Bootstrap Confidence Intervals for Smoothing Splines and Their Comparison to Bayesian Confidence Intervals

We construct bootstrap confidence 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 confidence intervals are considered and compared. We find that the commonly used bootstrap percentile intervals are inferior to the T intervals an...

BOOTSTRAP CONFIDENCE INTERVALS 1 BootES : An R Package for Bootstrap Confidence Intervals on Effect Sizes

Bootstrap Effect Sizes (bootES; Gerlanc & Kirby, 2012) is a free, open source software package for R (R Development Core Team, 2012), which is a language and environment for statistical computing. BootES computes both unstandardized and standardized effect sizes (such as Cohen’s d, Hedges’s g, and Pearson’s r), and makes easily available for the first time the computation of their bootstrap CIs...

Improving the Reliability of Bootstrap Confidence Intervals

This paper investigates the relation between hypothesis testing and the construction of confidence intervals, with particular regard to bootstrap tests. In practice, confidence intervals are almost always based on Wald tests, and consequently are not invariant under nonlinear reparametrisations. Bootstrap percentile-t confidence intervals are an instance of this. However, the (asymptotically) p...