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GARCH models are useful tools in the investigation of phenomena, where volatility changes are prominent features, like most financial data. The parameter estimation via quasi maximum likelihood (QMLE)...
本文检测非参数回归模型均值函数结构变点,针对均值函数跃度的长期均值为零时,基于残量的CUSUM统计量对均值函数结构变点检验无效的问题,本文提出了一种基于均值函数的核估计的检验统计量,得到统计量在原假设和备择假设下的极限分布,并构造Bootstrap方法对非参数回归模型均值函数结构变点进行检验,证明了检验和估计的一致性;模拟结果表明本文方法明显优于已有方法。
A general notion of bootstrapped $\phi$-divergences estimates constructed by exchangeably weighting sample is introduced.
In the problem of estimating the lower and upper tail copula we propose two bootstrap procedures for approximating the distribution of the corresponding empirical tail copulas. The first method ...
We prove Edgeworth expansions for degenerate von Mises statistics like the Beran, Watson, and Cram&-von Mises goodness-of-fit statistics. Furthermore, we show that the bootstrap approximation works...
We consider the construction of unconditional bootstrap- t prediction intervals for stationary time series. Our approach relies on the sieve bootstrap resampling scheme introduced by Biihlmann. Ba...
In a two-stage cluster sampling procedure, $n$ random populations are drawn independently from independent populations and a sub-sample of observations is taken in each of them. The estimator of the g...
The purpose of this note is to provide an approximation for the generalized bootstrapped empirical process achieving the rate in Komlós et al. (1975). The proof is based onmuch the same arguments used...
We investigate the canonical correlation of the principal components from two populations, and attain the limiting distribution using the perturbation expansion of the canonical correlation estimate. ...
Because the stationary bootstrap resamples data blocks of random length, this method has been thought to have the largest asymptotic variance among block bootstraps Lahiri [Ann. Statist. 27 (1999) ...
We consider the least-square linear regression problem with regularization by the ℓ1-norm, a problem usually referred to as the Lasso. In this paper, we first present a detailed asymptotic ana...
Bootstrap techniques (also called resampling computation techniques) have introduced new advances in modeling and model evaluation [10]. Using resampling methods to construct a series of new samples...
In the analysis of microarray data, and in some other contemporary statistical problems, it is not uncommon to apply hypothesis tests in a highly simultaneous way. The number, N say, of tests used c...

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