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Weighted bootstrap in GARCH models
asymptotic distribution bootstrap confidence region,GARCH model quasi maximum likelihood
2012/11/22
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。
General bootstrap for dual phi-divergences estimates
Bootstrap consistency weighted bootstrap Kaplan-Meier
2011/7/5
A general notion of bootstrapped $\phi$-divergences estimates constructed by exchangeably weighting sample is introduced.
Edgeworth expansions and bootstrap for degenerate von Mises statistics
Edgeworth expansions bootstrap for degenerate Mises statistics
2009/9/22
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...
ON THE CONSTRUCTION AND PROPERTIES OF BOOTSTRAP-t PREDICTION INTERVALS FOR STATIONARY TIME SERIES
Prediction intervals sieve bootstrap-t method of sieves
2009/9/18
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...
Approximation for general bootstrap of empirical processes with an application to kernel-type density estimation
General bootstrap Brownian bridge Best approximation kernel density estimator
2010/3/19
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...
A note on the stationary bootstrap's variance
Asymptotic expansion block bootstrap periodogram spectralestimation
2010/3/18
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)
...
Model-Consistent Sparse Estimation through the Bootstrap
Model-Consistent Sparse Estimation Bootstrap
2010/3/17
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...