Using linear interpolation to reduce the order of the coverage error of nonparametric prediction intervals based on right-censored data

E. Beutner; E. Cramer

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Using linear interpolation to reduce the order of the coverage error of nonparametric prediction intervals based on right-censored data

机译：使用线性插值来减少基于右删失数据的非参数预测区间的覆盖误差的顺序

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We prove a general result showing that a simple linear interpolation between adjacent random variables reduces the coverage error of nonparametric prediction intervals for a future observation from the same underlying distribution function from O(n~(-1)) to O(n~(-2)). To illustrate the result we show that it can be applied to various scenarios of right censored data including Type-II censored samples, pooled Type-II censored data, and progressively Type-II censored order statistics. We further illustrate the result by simulations indicating that the desired level of significance is almost attained for moderate sample sizes.

机译：我们证明了一个一般结果，该结果表明相邻随机变量之间的简单线性插值可减少非参数预测区间的覆盖误差，以便将来从O（n〜（-1））到O（n〜（- 2））。为了说明结果，我们显示了它可以应用于各种类型的右删失数据，包括II型删失样本，合并的II型删失数据以及渐进的II型删失顺序统计。我们通过仿真进一步说明了结果，该仿真表明对于中等样本量几乎可以达到所需的显着性水平。

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《Journal of Multivariate Analysis: An International Journal》 |2014年第null期|共15页
作者
E. Beutner; E. Cramer;
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原文格式 PDF
正文语种 eng
中图分类多元分析;
关键词
Nonparametric prediction intervals; Right-censored data; Asymptotic refinements;

机译：非参数预测区间;右删失数据;渐近细化;

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1. Using linear interpolation to reduce the order of the coverage error of nonparametric prediction intervals based on right-censored data [J] . E. Beutner, E. Cramer Journal of Multivariate Analysis: An International Journal . 2014,第Null期

机译：使用线性插值来减少基于右删失数据的非参数预测区间的覆盖误差的顺序
2. Exact nonparametric confidence, prediction and tolerance intervals based on multi-sample Type-II right censored data [J] . Volterman W., Balakrishnan N. Journal of Statistical Planning and Inference . 2010,第11期

机译：基于多样本II型右删失数据的精确非参数置信度，预测和公差区间
3. Adaptive error prediction method based on multiple linear regression for reversible data hiding [J] . Ma Bin, Wang Xiaoyu, Li Qi, Journal of Real-Time Image Processing . 2019,第4期

机译：基于多元线性回归的可逆数据隐藏自适应误差预测方法
4. A Multiple Linear Regression Based High-Accuracy Error Prediction Algorithm for Reversible Data Hiding [C] . Bin Ma, Xiaoyu Wang, Bing Li, Interntaional Workshop on Digital Forensics and Watermarking . 2019

机译：基于多元线性回归的可逆数据隐藏的高精度误差预测算法
5. Essays on Nonparametric Identification: Identification of Dependent Multidimensional Unobserved Variables in a System of Linear Equations Identification and Estimation for Regressions with Errors in All Variables Identification of Nonparametrically Distributed Random Coefficients in Linear Panel Data Models. [D] . Ben-Moshe, Dan. 2012

机译：关于非参数识别的论文：线性方程组中相关多维多维观测变量的识别以及线性面板数据模型中非参数分布随机系数的所有变量中所有变量均具有误差的回归估计。
6. Berry-Esseen bounds of weighted kernel estimator for a nonparametric regression model based on linear process errors under a LNQD sequence [O] . Liwang Ding, Ping Chen, Yongming Li -1

机译：LNQD序列下基于线性过程误差的非参数回归模型的加权核估计的Berry-Esseen界
7. Reversible Audio Data Hiding Based on Variable Error-Expansion of Linear Prediction for Segmental Audio and G.711 Speech [O] . Akira NISHIMURA 2016

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Using linear interpolation to reduce the order of the coverage error of nonparametric prediction intervals based on right-censored data

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