Considering the condition of small sample sizes, quantifies uncertainty from systematic measurement error, this paper presents an accuracy Comprehensive evaluation method for Auto-Parking System based on bootstrap method. Collecting parking precision data by 8 practical experiments and taking the full use of the various information of limited sample data, we resample from the original samples, ...

Nonparametric variance estimation for the distortion risk measure can be readily done through the bootstrap or the nonparametric delta method based on the influence function. The same task for the bootstrapped risk measures, however, has been relatively unexplored in the literature. In this paper we analytically derive the influence function of the exactly bootstrapped quantile and later extend...

are then summarized as a bootstrap consensus tree. The frequency at which each clade is recovered is termed the bootstrap proportion, or bootstrap support. Jackknife analyses (reviewed by Miller, 1974) have also been used to estimate internal support on phylogenetic trees (e.g., Farris et al., 1996; Källersjö et al., 1999). The jackknife differs from the bootstrap in that characters are sampled...

• There is a vast literature on robust estimators, but in some situations it is still not easy to make inferences, such as confidence regions and hypothesis testing. This is mainly due to the following facts. On one hand, in most situations, it is difficult to derive the exact distribution of the estimator. On the other one, even if its asymptotic behaviour is known, in many cases, the converge...

This paper proposed a novel framework of facial feature localization and extraction method for images in the presence of various face conditions. Based on Gaussian skin-color model in the bootstrap algorithm and a light filtration method, the face mask is firstly constructed while using Gaussian skin-color model through the bootstrap process, and the clear facial feature is gained by utilizing ...

The determination of empirical confidence intervals for the location of quantitative trait loci (QTLs) by interval mapping was investigated using simulation. Confidence intervals were created using a non-parametric (resampling method) and parametric (resimulation method) bootstrap for a backcross population derived from inbred lines. QTLs explaining 1%, 5% and 10% of the phenotypic variance wer...

The Least Trimmed Squares (LTS) estimator is a frequently used robust estimator of regression. When it comes to inference for the parameters of the regression model, the asymptotic normality of the LTS estimator can be used. However, this is usually not appropriate in situations where the use of robust estimators is recommended. The bootstrap method constitutes an alternative, but has two major...

An Edgeworth expansion of a Studentized statistic for an ergodic regenerative strong Markov process is validated. A specific nonparametric bootstrap method is proposed and proved to be second-order correct in the light of the Edgeworth expansion, which is a variant of the regenerative block bootstrap designed for discrete-time Markov processes. One-dimensional diffusions and semi-Markov process...

This paper considers the problem of determining a confidence interval for the difference between two treatments in a simplified sequential paired clinical trial, which is analogous to setting an interval for the drift of a random walk subject to a parabolic stopping boundary. Three bootstrap methods of construction are applied: Efron’s accelerated bias-corrected, the DiCiccio-Romano, and the bo...