PP偏度,峰度正态性检验的P-VALUES

给出了用于高维正态性检验的PP偏度,峰度及其偏度,峰度混合的检验统计量,获得了诸统计量极限分布的尾部概率展开式,由此可比较准确而迅速地获得这类检验的各种临界值及其P-Values.本文的方法也适用对其它椭球等高分布检验的P-Vlalues计算问题。

The p-value and model specification in statistics

SUMMARY The p value has been widely used as a way to summarise the significance in data analysis. However, misuse and misinterpretation of the p value is common in practice. Our result shows that if the model specification is wrong, the distribution of the p value may be inappropriate, which makes the decision based on the p value invalid.

A New Definition of P-Value Involving the Maximum Likelihood Estimator

We present here an alternative definition of the P-value for statistical hypothesis test of a real-valued parameter for a continuous random variable X. Our approach uses neither the notion of Type I error nor the assumption that null hypothesis is true. Instead, the new P-value involves the maximum likelihood estimator, which is usually available for a parameter such as the mean μ or standard deviation σ of a random variable X with a common distribution.

GENERALIZED p-VALUES AND GENERALIZED CONFIDENCE INTERVALS FOR VARIANCE COMPONENTS IN GENERAL RANDOM EFFECT MODEL WITH BALANCED DATA

Various random models with balanced data that are relevant for analyzing practical test data are described, along with several hypothesis testing and interval estimation problems concerning variance components. In this paper, we mainly consider these problems in general random effect model with balanced data. Exact tests and confidence intervals for a single variance component corresponding to random effect are developed by using generalized p-values and generalized confidence intervals. The resulting procedures are easy to compute and are applicable to small samples. Exact tests and confidence intervals are also established for comparing the random-effects variance components and the sum of random-effects variance components in two independent general random effect models with balanced data. Furthermore, we investigate the statistical properties of the resulting tests. Finally, some simulation results on the type Ⅰ error probability and power of the proposed test are reported. The simulation results indicate that exact test is extremely satisfactory for controlling type Ⅰ error probability.

A fiducial argument for generalized p-value

This paper provides a general method for constructing generalized p-value via the fiducial inference.Furthermore,the power properties of the generalized test are discussed.As illustrations, the two-parameter exponential distribution and unbalanced two-fold nested design are researched.It is shown that the resulting generalized p-values are of good frequency property.

磷酸化基序精确置换检验p-value的计算方法

蛋白质磷酸化基序指的是位于磷酸化位点周围具有位置特殊性的氨基酸序列.磷酸化基序挖掘是生物信息学中的一个重要问题.针对该问题,已经提出了一些有效的挖掘方法.但是,这些方法所挖掘到的磷酸化基序中会存在很多的假阳性结果.采用这些假阳性结果做进一步研究会导致严重的误导.通常,可以采用统计显著性检验来过滤掉这些无意义的磷酸化基序.置换检验是统计显著性检验中一种常用的方法,但该方法存在3个明显的缺点,这些缺点降低了置换检验的实用性.本文分析导致置换检验3个缺点的原因,提出了一个叫做EPPM的算法来计算所有被检验的磷酸化基序的精确置换检验p-value.实验证明,EPPM算法能够成功消除掉置换检验中的3个缺点,并且在几个性能评估指标上要胜过非精确置换检验算法.据作者所知,这是目前唯一能计算精确置换检验p-value进行磷酸化基序结果评估的研究工作.

How big are the increments of 1~p-valued Gaussian processes?

be a sequence of independent Gaussian processes with σk2 (h)The large increments for Y(·) with boundedσ (p, h ) are investigated. As an example the large increments of infinite-dimensional fractional Ornstein-Uhlenbeck process in 1p are given. The method can also be applied to certain processes with stationary increments.

GENERALIZED p-VALUES FOR TESTING REGRESSION COEFFICIENTS IN PARTIALLY LINEAR MODELS

The one-sided and two-sided hypotheses about the parametric component in partially linear model are considered in this paper. Generalized p-values are proposed based on fiducial method for testing the two hypotheses at the presence of nonparametric nuisance parameter. Note that the nonparametric component can be approximated by a linear combination of some known functions, thus, the partially linear model can be approximated by a linear model. Thereby, generalized p-values for a linear model are studied first, and then the results are extended to the situation of partially linear model. Small sample frequency properties are analyzed theoretically. Meanwhile, simulations are conducted to assess the finite sample performance of the tests based on the proposed p-values.

Genetic Pleiotropy Test by Quasi p-Value with Application to Typhoon Data in China

To test genetic pleiotropy,the main difficulty lies in the failure to find a test statistic and calculate its p-value for determining whether to reject the null hypothesis or not.To deal with this issue,the authors propose a quasi p-value,which plays the similar role as the usual p-value in genetic pleiotropy test.In the formula of the quasi p-value,the main task is to determine the weights.In this paper,the authors present two weighted methods based on the Bayesian rule and extend the proposed methods to study a single binary trait using a data-driven EM algorithm.Extensive simulation studies are conducted for the assessment of the two proposed methods and illustrate that the proposed methods improve the performance of power by comparing with the two-stage method.In addition,the authors apply the proposed methods to the data of tropical storms that occurred on the mainland of China since 1949,investigating the relationship between the landing site and predictive features of tropical storms,and showing that the landing site has a large influence on at least two features of typhoon.

Transient postseismic slip and aftershock triggering:A case study of the 2008 M_W7.9 Wenchuan Earthquake,China

In this study,we investigate how a stress variation generated by a fault that experiences transient postseismic slip(TPS)affects the rate of aftershocks.First,we show that the postseismic slip from Rubin-Ampuero model is a TPS that can occur on the main fault with a velocity-weakening frictional motion,that the resultant slip function is similar to the generalized Jeffreys-Lomnitz creep law,and that the TPS can be explained by a continuous creep process undergoing reloading.Second,we obtain an approximate solution based on the Helmstetter-Shaw seismicity model relating the rate of aftershocks to such TPS.For the Wenchuan sequence,we perform a numerical fitting of the cumulative number of aftershocks using the Modified Omori Law(MOL),the Dieterich model,and the specific TPS model.The fitting curves indicate that the data can be better explained by the TPS model with a B/A ratio of approximately 1.12,where A and B are the parameters in the rate-and state-dependent friction law respectively.Moreover,the p and c that appear in the MOL can be interpreted by the B/A and the critical slip distance,respectively.Because the B/A ratio in the current model is always larger than 1,the model could become a possible candidate to explain aftershock rate commonly decay as a power law with a p-value larger than 1.Finally,the influence of the background seismicity rate r on parameters is studied;the results show that except for the apparent aftershock duration,other parameters are insensitive to r.

基于熵的随机性检测相关性研究

目前,存在众多的随机性检测项目,并且许多项目都带有参数.选择所有的项目进行检测不现实,因此需要研究检测项目之间的关系.从统计学角度出发,对检测项目的相关性进行研究,首先定义了检测项目之间存在的4种关系,提出了检测项目相关度的概念,然后利用熵值法对检测项目相关度进行度量,并证明了这4种关系与相关度的联系,同时给出了一种计算相关度的算法和一个基于相关度的检测项目选择策略.所研究的结果为随机性检测项目及其参数选择提供了理论依据.与此同时,利用相关度对NIST在评选AES中所采用的检测项目进行研究,发现了其中一些检测项目之间存在着依赖关系.

随机性检测参数选择研究

从统计学角度对同一个随机性检测项目中2个独立的参数所应满足的条件进行了研究,在此基础上设计了一个假设检验方法,用于检测2个参数是否满足独立的关系。以扑克检测为实例,对其参数集中的参数进行了实验研究,并对结果进行了分析。提出的方法是一个通用的方法,可以直接应用于其他带参数的检测项目的参数关系研究中,这为随机性检测中参数选择提供了一种可操作的手段。

地理标志产品绍兴黄酒与非地理标志黄酒感官评价分析的研究

根据5位黄酒国家级评酒委员对地理标志产品绍兴黄酒与非地理标志黄酒的感官品评,对其醇和度、甜度、鲜爽度、酸度、协调性进行量化评分,采用P-value假设数据统计法进行比较分析。结果表明,绍兴地理标志黄酒产品在醇和度、鲜爽度和协调性3个方面得分均高于非绍兴地理标志黄酒产品,醇和度、鲜爽度和协调性的口感指标可以作为绍兴地理标志黄酒区别于非地理标志黄酒的特征性感官鉴定指标,为黄酒鉴别进一步研究打下基础。

多个正态总体均值相等性检验方法的模拟比较

针对t个正态总体,提出均值相等性似然比检验.总结了三种检验方法,即似然比检验、bootstrap p-value检验和bootstrap检验.用Monte Carlo方法检验多个正态总体均值相等性问题,通过给出的模拟结果,比较了检验方法的有效性.

NIST随机性检测方法及应用

序列的随机性检测是密码学研究的一个重要课题,首先介绍了美国NIST测试标准,然后利用Linux系统下的makefile和sts软件两种方法对流密码ZUC生成的序列了进行随机性检测,16种测试结果表明ZUC的密钥流序列是随机的。

Asymptotic Inference for the Weak Stationary Double AR(1) Model

An AR(1) model with ARCH(1) error structure is known as the first-order double autoregressive (DAR(1)) model. In this paper, a conditional likelihood based method is proposed to obtain inference for the two scalar parameters of interest of the DAR(1) model. Theoretically, the proposed method has rate of convergence O(n-3/2). Applying the proposed method to a real-life data set shows that the results obtained by the proposed method can be quite different from the results obtained by the existing methods. Results from Monte Carlo simulation studies illustrate the supreme accuracy of the proposed method even when the sample size is small.

Epidemiological Analysis of the Coronavirus Disease Outbreak with Random Effects

Today,coronavirus appears as a serious challenge to the whole world.Epidemiological data of coronavirus is collected through media and web sources for the purpose of analysis.New data on COVID-19 are available daily,yet information about the biological aspects of SARS-CoV-2 and epidemiological characteristics of COVID-19 remains limited,and uncertainty remains around nearly all its parameters’values.This research provides the scientic and public health communities better resources,knowledge,and tools to improve their ability to control the infectious diseases.Using the publicly available data on the ongoing pandemic,the present study investigates the incubation period and other time intervals that govern the epidemiological dynamics of the COVID-19 infections.Formulation of the testing hypotheses for different countries with a 95%level of condence,and descriptive statistics have been calculated to analyze in which region will COVID-19 fall according to the tested hypothesized mean of different countries.The results will be helpful in decision making as well as in further mathematical analysis and control strategy.Statistical tools are used to investigate this pandemic,which will be useful for further research.The testing of the hypothesis is done for the differences in various effects including standard errors.Changes in states’variables are observed over time.The rapid outbreak of coronavirus can be stopped by reducing its transmission.Susceptible should maintain safe distance and follow precautionary measures regarding COVID-19 transmission.

Application of Omori’s Decay Law to the 2001 Bhuj Aftershock Sequence for Kachchh Region of Western India

In the present study, the temporal behavior of 2001 Bhuj aftershock sequence in Kachchh region of western peninsular India is studied by the modified Omori law. The Omori law parameters p, c and K are determined with the standard errors by the maximum likelihood estimates using ZMAP algorithm in MatLab environment. The entire aftershock sequence is analyzed by diving it into three separate series with respect to time to weigh up the bigger earthquake of magnitude M 5.7 occurring on March 7, 2006 at Gedi fault. This study helps to understand the cumulative effect of the aftershocks generated by this bigger earthquake of the mainshock sequence. The results of this analysis are discussed with other studies of the different earthquake sequence for the different parts of the world and suggest that all the three series of Bhuj aftershock sequence follow the Omori relation. Values of parameter p vary significantly from series 1 to series 3, i.e., p-value varies significantly with time. Similarly, other two Omori law parameters K and c are also found to change significantly with time. These parameters are useful to describe temporal behavior of aftershocks and to forecast aftershock activity in time domain. Aftershock decay rate provides insight into stress release processes after the mainshock, thus helping to understand the heterogeneity of the fault zone properties and evaluate time-dependent seismic hazard analysis over the region.

随机性检测综述

随机性序列广泛应用于计算机科学的各个方面，特别是在密码学领域发挥了核心作用，保护了信息安全。实际应用中随机序列由伪随机数发生器产生，而随机性检测正是用于检测序列是否具有规则性。对现有随机性检测的研究成果进行综述，从随机性检测的多层次判别方法、随机性检测的相关性、随机性检测算法效率的优化等方面对研究成果进行梳理，并对现有随机性检测的不足以及今后的研究方向进行分析。

INSTANTANEOUS AVAILABILITY ASSESSMENT OF RENEWABLE COMPONENT IN EXPONENTIAL DISTRIBUTIONS

A renewable component with exponential failure and repair times is considered, and its instantaneous availability at time t is denoted by A（t）. This paper proposes two methods for constructing lower confidence limits of A（t） with Chebyshev inequation and generalized p-value approach.