搜索结果: 1-15 共查到“数学 Testing”相关记录41条 . 查询时间(0.14 秒)
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars:Kolmogorov-Smirnov type testing for structural breaks: A new adjusted-range based self-normalization approach
结构断裂 Kolmogorov-Smirnov检验 KS检验 调整范围 自归一化方法
2023/4/23
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars:Fixed Effects Bayesian Testing in High-Dimensional Linear Mixed Models
高维 线性混合模型 固定效应 贝叶斯检验
2023/5/5
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars:Recoverability effects on reliability assessment for accelerated degradation testing
可恢复性 加速退化测试 可靠性评估
2023/4/24
昆明理工大学理学院概率论与数理统计课件Chapter 8 Hypothesis Testing--Tests Concerning Variance
昆明理工大学理学院 概率论与数理统计 课件 Chapter 8 Hypothesis Testing Tests Concerning Variance
2017/4/17
昆明理工大学理学院概率论与数理统计课件Chapter 8 Hypothesis Testing--Tests Concerning Variance.
昆明理工大学理学院概率论与数理统计课件Chapter 8 Hypothesis Testing--Tests Concerning Mean
昆明理工大学理学院 概率论与数理统计 课件 Chapter 8 Hypothesis Testing Tests Concerning Mean
2017/4/17
昆明理工大学理学院概率论与数理统计课件Chapter 8 Hypothesis Testing--Tests Concerning Mean.
昆明理工大学理学院概率论与数理统计课件Chapter 8 Hypothesis Testing--Introduction
昆明理工大学理学院 概率论与数理统计 课件 Chapter 8 Hypothesis Testing Introduction
2017/4/17
昆明理工大学理学院概率论与数理统计课件Chapter 8 Hypothesis Testing--Introduction.
On large deviations in testing simple hypotheses for locally stationary Gaussian processes
Hypothesis testing Likelihood ratio Large deviations Locally stationary Gaussian processes Hoeffding bound Stein’s lemma Chernoff bound
2015/8/25
We derive a large deviation result for the log-likelihood ratio for testing simple hypotheses in locally stationary Gaussian processes. This result allows us to find explicitly the rates of exponentia...
AN ASYMPTOTIC ERROR BOUND FOR TESTING MULTIPLE QUANTUM HYPOTHESES
ASYMPTOTIC ERROR BOUND TESTING MULTIPLE QUANTUM HYPOTHESES
2015/8/25
We consider the problem of detecting the true quantum state among r possible ones, based of measurements performed on n copies of a finitedimensional quantum system. A special case is the problem of d...
THE CHERNOFF LOWER BOUND FOR SYMMETRIC QUANTUM HYPOTHESIS TESTING
CHERNOFF LOWER BOUND SYMMETRIC QUANTUM HYPOTHESIS TESTING
2015/8/25
We consider symmetric hypothesis testing in quantum statistics, where the hypotheses are density operators on a finite-dimensional complex Hilbert space, representing states of a finite quantum system...
Asymptotic Error Rates in Quantum Hypothesis Testing
Asymptotic Error Rates Quantum Hypothesis Testing
2015/8/25
We consider the problem of discriminating between two different states of a finite quantum system in the setting of large numbers of copies, and find a closed form expression for the asymptotic expone...
Optimal Multiple Testing Under a Gaussian Prior on the Effect Sizes
Effect Sizes Multiple Testing
2015/8/21
We develop a new method for frequentist multiple testing with Bayesian prior information.
Our procedure nds a new set of optimal p-value weights called the Bayes weights. Prior
information is relev...
Large-Scale Simultaneous Hypothesis Testing: The Choice of a Null Hypothesis
Null Hypothesis Simultaneous Hypothesis Testing
2015/8/20
Current scientific techniques in genomics and image processing routinely produce hypothesis testing problems with hundreds or thousands of cases to consider simultaneously.
This poses new di...
Simultaneous Inference: When Should Hypothesis Testing Problems Be Combined?
Simultaneous Inference Testing Problems
2015/8/20
Modern statisticians are often presented with hundreds or thousands of hypothesis
testing problems to evaluate at the same time, generated from new scientific technologies such as microarrays, ...
TESTING FOR INDEPENDENCE IN A TWO-WAY TABLE: NEW INTERPRETATIONS OF THE CHI-SQUARE STATISTIC
Classic chi-square distribution independent statistics dimension
2015/7/14
The classical chi-square test for independence in a two-way contingency
table often rejects the independence hypothesis at an extremely small signif-
icance level, particularly when the sample siz...
Statistical Estimation and Testing via the Sorted 1 Norm
Sparse regression variable selection false discovery rate lasso sorted 1 penalized estimation (SLOPE) prox operator
2015/6/17
We introduce a novel method for sparse regression and variable selection, which is inspired by modern ideas in multiple testing. Imagine we have observations from the linear model y = Xβ + z, then we ...