A coverage probability of bootstrap-t confidence interval for the variance

Bootstrap estimate of the variance and confidence interval of kappa.

New Technical Efficiency Estimates with Improved Bootstrap Confidence Interval Coverage

Bootstrap confidence intervals on fixed-effects efficiency estimates from finite-sample panel data models exhibit low coverage probabilities, because the traditional estimate involves a "max" operator that induces a finite sample bias. Attempts to bootstrap confidence intervals for the traditional estimate have focused on correcting bias. Rather than addressing this bias at the bootstrap stage,...

Coverage Probability of Confidence Intervals for the Normal Mean and Variance with Restricted Parameter Space

Recent articles have addressed the problem to construct the confidence intervals for the mean of a normal distribution where the parameter space is restricted, see for example Wang [Confidence intervals for the mean of a normal distribution with restricted parameter space. Journal of Statistical Computation and Simulation, Vol. 78, No. 9, 2008, 829–841.], we derived, in this paper, analytic exp...

Explicit Nonparametric Confidence Intervals for the Variance with Guaranteed Coverage

_________________________________________________________________ In this paper, we provide a method for constructing confidence intervals for the variance that exhibit guaranteed coverage probability for any sample size, uniformly over a wide class of probability distributions. In contrast, standard methods achieve guaranteed coverage only in the limit for a fixed distribution or for any sampl...

Bootstrap confidence interval estimates of the bullwhip effect

This paper introduces the confidence interval estimate for measuring the bullwhip effect, which has been observed across most industries. Calculating a confidence interval usually needs the assumption about the underlying distribution. Bootstrapping is a non-parametric, but computer intensive, estimation method. In this paper, a simulation study on the behavior of the 95% bootstrap confidence i...