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Efficient estimation of the odds using judgment post stratification 使用判断后分层的有效几率估计
IF 1 4区 数学 Q4 STATISTICS & PROBABILITY Pub Date : 2021-05-01 DOI: 10.1214/20-BJPS481
Mozhgan Alirezaei Dizicheh, Ehsan Zamanzade, N. Iranpanah
This work deals with problem of estimating the odds using judgment post stratification (JPS) sampling design. Several estimators of the odds are described and the asymptotic normality of each of them is established. Monte Carlo simulation study is then used to compare different estimators of the odds in the JPS with the standard estimator in simple random sampling (SRS) with replacement for both perfect/imperfect ranking and for both JPS data with/without empty strata. The comparison results indicate that the estimators developed here can be highly more efficient than their SRS counterpart in some certain circumstances. Finally, a real dataset from the third National Health and Nutrition Examination Survey (NHANES III) is employed for illustration purposes.
本文研究了用判断后分层(JPS)抽样设计估计概率的问题。描述了概率的几个估计量,并建立了它们的渐近正态性。然后使用蒙特卡罗模拟研究来比较JPS中概率的不同估计值与简单随机抽样(SRS)中的标准估计值,并替换完美/不完美排名以及有/没有空层的JPS数据。比较结果表明,在某些情况下,本文开发的估计器比相应的SRS估计器效率更高。最后,为了说明目的,使用了第三次国家健康和营养检查调查(NHANES III)的真实数据集。
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引用次数: 0
Integrals of incomplete beta functions, with applications to order statistics, random walks and string enumeration 不完全贝塔函数的集成,应用于订单统计、随机游动和字符串枚举
IF 1 4区 数学 Q4 STATISTICS & PROBABILITY Pub Date : 2021-04-25 DOI: 10.1214/21-bjps522
Stephen B. Connor, C. Fewster
Abstract. We study the probability that one beta-distributed random variable exceeds the maximum of two others, allowing all three to have general parameters. This amounts to studying Euler transforms of products of two incomplete beta functions. We provide a closed form for the general problem in terms of Kampé de Fériet functions and a variety of simpler closed forms in special cases. The results are applied to derive the moments of the maximum of two independent beta-distributed random variables and to find inner products of incomplete beta functions. Restricted to positive integer parameters, our results are applied to determine an expected exit time for a conditioned random walk and also to a combinatorial problem of enumerating strings comprised of three different letters, subject to constraints.
摘要我们研究一个β分布随机变量超过另外两个随机变量最大值的概率,允许所有三个随机变量都有一般参数。这相当于研究两个不完全函数乘积的欧拉变换。我们用kamp de fsamriet函数给出了一般问题的封闭形式,并在特殊情况下给出了各种更简单的封闭形式。结果应用于推导两个独立的β分布随机变量的极大值的矩和求不完全β函数的内积。由于受正整数参数的限制,我们的结果被应用于确定条件随机漫步的预期退出时间,以及在约束条件下枚举由三个不同字母组成的字符串的组合问题。
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引用次数: 1
Limit theorems for quasi-arithmetic means of random variables with applications to point estimations for the Cauchy distribution 随机变量拟算术均值的极限定理及其在柯西分布点估计中的应用
IF 1 4区 数学 Q4 STATISTICS & PROBABILITY Pub Date : 2021-04-13 DOI: 10.1214/22-BJPS531
Y. Akaoka, K. Okamura, Y. Otobe
Abstract. We establish some limit theorems for quasi-arithmetic means of random variables. This class of means contains the arithmetic, geometric and harmonic means. Our feature is that the generators of quasiarithmetic means are allowed to be complex-valued, which makes considerations for quasi-arithmetic means of random variables which could take negative values possible. Our motivation for the limit theorems is finding simple estimators of the parameters of the Cauchy distribution. By applying the limit theorems, we obtain some closed-form unbiased strongly-consistent estimators for the joint of the location and scale parameters of the Cauchy distribution, which are easy to compute and analyze.
摘要我们建立了随机变量拟算术平均的一些极限定理。这类均值包括算术均值、几何均值和调和均值。我们的特点是允许拟算术平均的生成元是复值的,这使得考虑可能取负值的随机变量的拟算术平均成为可能。极限定理的动机是找到柯西分布参数的简单估计量。通过应用极限定理,我们得到了Cauchy分布的位置和尺度参数联合的一些闭形式无偏强相合估计量,这些估计量易于计算和分析。
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引用次数: 7
Likelihood-based missing data analysis in crossover trials 交叉试验中基于似然性的缺失数据分析
IF 1 4区 数学 Q4 STATISTICS & PROBABILITY Pub Date : 2021-03-11 DOI: 10.1214/23-bjps570
S. Pareek, K. Das, S. Mukhopadhyay
A multivariate mixed-effects model seems to be the most appropriate for gene expression data collected in a crossover trial. It is, however, difficult to obtain reliable results using standard statistical inference when some responses are missing. Particularly for crossover studies, missingness is a serious concern as the trial requires a small number of participants. A Monte Carlo EM (MCEM)-based technique was adopted to deal with this situation. In addition to estimation, MCEM likelihood ratio tests (LRTs) are developed to test fixed effects in crossover models with missing data. Intensive simulation studies were conducted prior to analyzing gene expression data.
多变量混合效应模型似乎最适合交叉试验中收集的基因表达数据。然而,当某些响应缺失时,使用标准统计推断很难获得可靠的结果。特别是对于交叉研究,缺失是一个严重的问题,因为试验需要少量的参与者。采用蒙特卡罗电磁法(MCEM)来处理这种情况。除了估计之外,MCEM似然比检验(LRTs)被开发用于检验缺失数据的交叉模型中的固定效应。在分析基因表达数据之前,进行了密集的模拟研究。
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引用次数: 1
On multivariate selection scale-mixtures of normal distributions 多元选择尺度-正态分布的混合
IF 1 4区 数学 Q4 STATISTICS & PROBABILITY Pub Date : 2021-03-01 DOI: 10.1214/20-BJPS478
Roohollah Roozegar, N. Balakrishnan, A. Bekker, A. Jamalizadeh
In this paper, we establish some results for multivariate selection scale-mixtures of normal distributions with arbitrary mixing variable. First, we discuss their stochastic representation in terms of multivariate selection normal distributions. Next, the conditional distributions as well as the first two moments of multivariate selection scale-mixtures of normal distributions are obtained when the selection set is an arbitrary rectangle in the q-dimensional Euclidean space of R. The unified skew-scale mixture of normal (SUSMN) distributions are subsequently discussed as a special case. As a subclass of SUSMN distributions, the class of unified skew-symmetric generalized hyperbolic (SUSGH) distributions are studied in detail. Finally, we show that our results can be used to obtain moments of L-statistics and of multivariate concomitants from multivariate scale-mixtures of normal distributions.
本文建立了具有任意混合变量的正态分布的多变量选择尺度混合的一些结果。首先,我们用多元选择正态分布来讨论它们的随机表示。接下来,当选择集是R的q维欧氏空间中的任意矩形时,获得了正态分布的多变量选择尺度混合的条件分布以及前两个矩。随后,作为特例讨论了统一斜尺度正态分布混合(SUSMN)。作为SUSMN分布的一个子类,详细研究了一类统一的斜对称广义双曲(SUSGH)分布。最后,我们证明了我们的结果可以用于从正态分布的多变量尺度混合中获得L-统计量和多变量伴随项的矩。
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引用次数: 1
Estimation of semiparametric models with errors following a scale mixture of Gaussian distributions 高斯分布尺度混合后带误差的半参数模型估计
IF 1 4区 数学 Q4 STATISTICS & PROBABILITY Pub Date : 2021-03-01 DOI: 10.1214/20-BJPS476
Marcelo M. Taddeo, P. Morettin
In this paper we consider a semiparametric regression model where the error follows a scale mixture of Gaussian distributions. The purpose is to estimate the target function which is assumed to belong to some class of functions using the EM algorithm and approximations via P -splines and B-splines. We illustrate the proposed methodology through several simulation studies. Other forms of function approximation are also studied, namely Fourier and wavelet expansions.
在本文中,我们考虑了一个半参数回归模型,其中误差遵循高斯分布的比例混合。其目的是使用EM算法和P样条和B样条的近似来估计被假设属于某类函数的目标函数。我们通过几个模拟研究来说明所提出的方法。还研究了其他形式的函数近似,即傅立叶展开和小波展开。
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引用次数: 0
Modeling Z-valued time series based on new versions of the Skellam INGARCH model 基于新版Skellam INGARCH模型的z值时间序列建模
IF 1 4区 数学 Q4 STATISTICS & PROBABILITY Pub Date : 2021-03-01 DOI: 10.1214/20-BJPS473
Yan Cui, Qi Li, Fukang Zhu
Recently, there has been a growing interest in integer-valued time series models, including integer-valued autoregressive (INAR) models and integer-valued generalized autoregressive conditional heteroscedastic (INGARCH) models, but only a few of them can deal with data on the full set of integers, i.e., Z = {...,−2,−1, 0, 1, 2, ...}. Although some attempts have been made to deal with Z-valued time series, these models do not provide enough flexibility in modeling some specific integers (e.g. 0, ±1). A symmetric Skellam INGARCH(1,1) model was proposed in the literature, but it only considered zero-mean processes, which limits its application. We first extend the symmetric Skellam INGARCH model to an asymmetric version, which can deal with non-zero-mean processes. Then we propose a modified Skellam model which adopts a careful treatment on integers 0 and ±1 to satisfy a special feature of the data. Our models are easy-to-use and flexible. The maximum likelihood method is used to estimate unknown parameters and the log-likelihood ratio test statistic is provided for testing the asymmetric model against the modified one. Simulation studies are given to evaluate performances of the parametric estimation and log-likelihood ratio test. A real data example is also presented to demonstrate good performances of newly proposed models.
近年来,人们对整值时间序列模型越来越感兴趣,包括整值自回归(INAR)模型和整值广义自回归条件异方差(INGARCH)模型,但只有少数模型能够处理整集合上的数据,即Z ={…,−2,−1,0,1,2,…}。尽管已经进行了一些尝试来处理z值时间序列,但这些模型在建模某些特定整数(例如0,±1)时不能提供足够的灵活性。文献中提出了一种对称的Skellam INGARCH(1,1)模型,但该模型只考虑零均值过程,限制了其应用。我们首先将对称的Skellam INGARCH模型扩展到非对称的版本,该版本可以处理非零均值过程。然后,我们提出了一种改进的Skellam模型,该模型对整数0和±1进行了仔细处理,以满足数据的特殊特征。我们的模型易于使用和灵活。采用极大似然法估计未知参数,并采用对数似然比检验统计量对修正后的非对称模型进行检验。对参数估计和对数似然比检验的性能进行了仿真研究。最后给出了一个实际的数据示例,验证了所提模型的良好性能。
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引用次数: 9
Regression models for change point data in extremes 极值变化点数据的回归模型
IF 1 4区 数学 Q4 STATISTICS & PROBABILITY Pub Date : 2021-02-01 DOI: 10.1214/20-bjps488
F. Nascimento, Alan da Silva Assunção
Many extreme events are characterized by being always susceptible to outside influences that will modify their behavior at some point in time. The change point tool has been used in statistical models to detect when these changes occur. This paper presents a model based on a Bayesian approach that describes the behavior of extreme data regarding river quota, which may present more than one change point. In each one of the regimes, the GEV distribution is adjusted and each GEV parameter of each regime is written in function of presence of covariates. In the applications proposed here, the results showed that the model was able to accurately estimate the actual amount of change points in the series, and also showed that it was extremely important to consider them in the analysis, since it was verified that after the change of regime, the levels of return have changed considerably. The results were also able to show which months the occurrence of an extreme event is greater.
许多极端事件的特点是总是容易受到外部影响,这些影响会在某个时间点改变他们的行为。变化点工具已在统计模型中用于检测这些变化何时发生。本文提出了一个基于贝叶斯方法的模型,该模型描述了关于河流配额的极端数据的行为,该数据可能会出现多个变化点。在每个方案中,调整GEV分布,并将每个方案的每个GEV参数写成协变量存在的函数。在本文提出的应用中,结果表明,该模型能够准确估计序列中变化点的实际数量,并表明在分析中考虑这些变化点是极其重要的,因为已经证实,在制度改变后,回报水平发生了显著变化。研究结果还能够显示极端事件发生的月份更大。
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引用次数: 0
Confidence intervals of the index $C_{pk}$ for normally distributed quality characteristics using classical and Bayesian methods of estimation 正态分布质量特征指数$C_{pk}$的置信区间的经典和贝叶斯估计方法
IF 1 4区 数学 Q4 STATISTICS & PROBABILITY Pub Date : 2021-02-01 DOI: 10.1214/20-bjps469
Mahendra Saha, S. Dey, A. Yadav, Sajid Ali
One of the indicators for evaluating the capability of a process potential and performance in an effective way is the process capability index (PCI). It is of great significance to quality control engineers as it quantifies the relation between the actual performance of the process and the pre-set specifications of the product. Most of the traditional PCIs performed well when process follows the normal behaviour. In this article, we consider a process capability index, $C_{pk}$, suggested by Kane (Journal of Quality Technology 18 (1986) 41–52) which can be used for normal random variables. The objective of this article is three fold: First, we address different methods of estimation of the process capability index $C_{pk}$ from frequentist approaches for the normal distribution. We briefly describe different frequentist approaches, namely, maximum likelihood estimators, least squares and weighted least squares estimators, maximum product of spacings estimators, Cramer–von-Mises estimators, Anderson–Darling estimators and Right-Tail Anderson–Darling estimators and compare them in terms of their mean squared errors using extensive numerical simulations. Second, we compare three parametric bootstrap confidence intervals (BCIs) namely, standard bootstrap, percentile bootstrap and bias-corrected percentile bootstrap. Third, we consider Bayesian estimation under squared error loss function using normal prior for location parameter and inverse gamma for scale parameter for the considered model. Monte Carlo simulation study has been carried out to compare the performances of the classical BCIs and highest posterior density (HPD) credible intervals of $C_{pk}$ in terms of average widths and coverage probabilities. Finally, two real data sets have been analyzed for illustrative purposes.
以有效的方式评估过程潜力和性能的能力的指标之一是过程能力指数(PCI)。它对质量控制工程师具有重要意义,因为它量化了过程的实际性能和产品的预设规格之间的关系。当流程遵循正常行为时,大多数传统PCI都表现良好。在本文中,我们考虑Kane(Journal of Quality Technology 18(1986)41-52)提出的过程能力指数$C_{pk}$,该指数可用于正态随机变量。本文的目的有三个方面:首先,我们讨论了从正态分布的频率论方法中估计过程能力指数$C{pk}$的不同方法。我们简要描述了不同的频率论方法,即最大似然估计量、最小二乘和加权最小二乘估计量、空间最大乘积估计量、Cramer–von Mises估计量、Anderson–Darling估计量和右尾Anderson–达林估计量,并使用广泛的数值模拟对它们的均方误差进行了比较。其次,我们比较了三种参数bootstrap置信区间,即标准bootstrap、百分位bootstrap和偏差校正百分位bootstrap。第三,我们考虑了在平方误差损失函数下的贝叶斯估计,使用正态先验作为所考虑模型的位置参数,使用逆伽马作为尺度参数。蒙特卡罗模拟研究比较了经典脑机接口和最高后验密度(HPD)可信区间$C_{pk}$在平均宽度和覆盖概率方面的性能。最后,为了便于说明,对两个真实的数据集进行了分析。
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引用次数: 15
Preface 前言
IF 1 4区 数学 Q4 STATISTICS & PROBABILITY Pub Date : 2021-02-01 DOI: 10.1214/20-bjps351pre
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引用次数: 0
期刊
Brazilian Journal of Probability and Statistics
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