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Jackknife Empirical Likelihood Method for Some Risk Measures and Related Quantities
Confidence interval jackknife empirical likelihood risk measure
2016/1/25
Quantifying risks is of importance in insurance. In this paper, we employ the jackknife empirical likelihood method to construct confidence intervals for some risk measures and related quantities stud...
Jackknife Empirical Likelihood Method for Some Risk Measures and Related Quantities
Confidence interval jackknife empirical likelihood risk measure
2016/1/20
Quantifying risks is of importance in insurance. In this paper, we employ the jackknife empirical likelihood method to construct confidence intervals for some risk measures and related quantities stud...
Jackknife Empirical Likelihood for Parametric Copulas
Copulas Empirical likelihood Interval estimation Jackknife
2016/1/19
For fitting a parametric copula to multivariate data, a popular way is to employ the so-called pseudo maximum likelihood estimation proposed by Genest, Ghoudi and Rivest (1995). Although interval esti...
Higher Order Properties of Bootstrap and Jackknife Bias Corrected Maximum Likelihood Estimators
Bootstrap and Jackknife Bias Likelihood Estimators
2015/9/22
Pfanzagl and Wefelmeyer (1978) show that bias corrected ML estimators are higher order efficient.
Their procedure however is computationally complicated because it requires integrating complicat...
Confidence Intervals for Random Forests:The Jackknife and the Infinitesimal Jackknife
bagging jackknife methods Monte Carlo noise variance estimation
2015/8/21
We study the variability of predictions made by bagged learners and random forests, and show how to estimate standard errors for these methods. Our work builds on variance estimates for bagging propos...
Analysis of Performance Measures in Experimental Designs Using Jackknife
Performance Measures Experimental Designs
2015/3/20
Analysis of Performance Measures in Experimental Designs Using Jackknife.
Jackknife and bootstrap with cycling blocks for the estimation of fractional parameter in ARFIMA model
Jackknife bootstrap fractionally parameter ARFIMA model moving blocks non overlapping blocks
2011/4/6
One of most important problems concerning the ARFIMA time series model is the estimation of fractional parameter d. Various methods have been used to solve this problem, such as the log-periodogram r...
The Jackknife method and the Gauss-Markov estimation
The Jackknife method the Gauss-Markov estimation
2009/9/24
yI, t is shown that in many cases the Jackknife estimator
is the least squares estimator in a convenient linear model;
moreover, under some light assumptions about the distribution of
the observati...
Delete-group Jackknife Estimate in Partially Linear Regression Models with Heteroscedasticity
partially linear regression model asymptotic variance
2007/12/10
Consider a partially linear regression model with an unknown vector parameter β, an unknown function g(·), and unknown heteroscedastic error variances. Chen, You~([23]) proposed a semiparametric gener...
在实际的调查中经常会出现缺失数据. 如何处理这种情况下总体目标量的估计是一个重要问题.Zou 等(2002)对缺失数据情况下的样本轮换方法证明了他们所提出的线性化 Jackknife 方差估计量在均匀回答下是估计量方差的近似的设计无偏估计. 这一性质对于 Jackknife 方差估计量的使用提供了重要依据. 对于其它情况下 Jackknife 方差估计量是否也具有这一性质无疑是一个有意义的问题. ...