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Shrinkage for covariance estimation: asymptotics, confidence intervals, bounds and applications in sensor monitoring and finance

机译：协方差估计的收缩：传感器监测和融资中的渐近学，置信区间，界限和应用

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Ansgar Steland;
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年度 2018
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1. Shrinkage for covariance estimation: asymptotics, confidence intervals, bounds and applications in sensor monitoring and finance [J] . Steland Ansgar Statistical papers . 2018,第4期

机译：协方差估计的收缩：传感器监测和融资中的渐近学，置信区间，界限和应用
2. Asymptotics of the weighted least squares estimation for AR(1) processes with applications to confidence intervals [J] . Han Ruidong, Wang Xinghui, Hu Shuhe Statistical Methods and Applications . 2018,第3期

机译：AR（1）过程的加权最小二乘估计的渐近性和置信区间的应用
3. Asymptotics for high-dimensional covariance matrices and quadratic forms with applications to the trace functional and shrinkage [J] . Steland Ansgar, von Sachs Rainer Stochastic Processes and Their Applications: An Official Journal of the Bernoulli Society for Mathematical Statistics and Probability . 2018,第8期

机译：高维协方差矩阵的渐近学和具有跨性功能和收缩的应用的二次形式
4. PREDICTION INTERVALS VERSUS CONFIDENCE INTERVALS FOR ON-LINE SENSOR MONITORING [C] . R.M. Seibert, D.R. Garvey, J.W. Hines Society for Machinery Failure Prevention Technology Meeting; 20060403-06; Virginia Beach,VA(US) . 2006

机译：在线传感器监控的预测区间与置信区间
5. Studies in Covariance Estimation and Applications in Finance [D] . Arndt, Carl-Fredrik. 2016

机译：经济协方差估算与应用研究
6. Confidence Interval Estimation for Pooled-Sample Biomonitoring from a Complex Survey Design [O] . Samuel P. Caudill -1

机译：复杂调查设计中样本池生物监测的置信区间估计
7. "Asymptotic Correction of Empirical Bayes Confidence Intervals and its Application to Small Area Estimation" (in Japanese) [O] . Yoshitaka Sasase, Tatsuya Kubokawa 100

机译：“经验贝叶斯置信区间的渐近校正及其在小面积估计中的应用”（日文）
8. Optimal Upper Confidence Limits for Products of Poisson Parameters with Applications to the interval Estimation of the Failure Probability of Parallel Systems [R] . Harris, B., Soms, A. P. 1980

机译：泊松参数乘积的最优上置信限及其在并联系统失效概率区间估计中的应用

Shrinkage for covariance estimation: asymptotics, confidence intervals, bounds and applications in sensor monitoring and finance

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