Brazilian Journal of Probability and Statistics最新文献_第9页

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

Brazilian Journal of Probability and Statistics Pub Date : 2021-05-01 DOI: 10.1214/20-BJPS481

Mozhgan Alirezaei Dizicheh, Ehsan Zamanzade, N. Iranpanah

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

Brazilian Journal of Probability and Statistics Pub Date : 2021-04-25 DOI: 10.1214/21-bjps522

Stephen B. Connor, C. Fewster

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

Brazilian Journal of Probability and Statistics Pub Date : 2021-04-13 DOI: 10.1214/22-BJPS531

Y. Akaoka, K. Okamura, Y. Otobe

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

Brazilian Journal of Probability and Statistics Pub Date : 2021-03-11 DOI: 10.1214/23-bjps570

S. Pareek, K. Das, S. Mukhopadhyay

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

Brazilian Journal of Probability and Statistics Pub Date : 2021-03-01 DOI: 10.1214/20-BJPS478

Roohollah Roozegar, N. Balakrishnan, A. Bekker, A. Jamalizadeh

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

Brazilian Journal of Probability and Statistics Pub Date : 2021-03-01 DOI: 10.1214/20-BJPS476

Marcelo M. Taddeo, P. Morettin

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

Brazilian Journal of Probability and Statistics Pub Date : 2021-03-01 DOI: 10.1214/20-BJPS473

Yan Cui, Qi Li, Fukang Zhu

{"title":"Modeling Z-valued time series based on new versions of the Skellam INGARCH model","authors":"Yan Cui, Qi Li, Fukang Zhu","doi":"10.1214/20-BJPS473","DOIUrl":"https://doi.org/10.1214/20-BJPS473","url":null,"abstract":"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.","PeriodicalId":51242,"journal":{"name":"Brazilian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42589973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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

Brazilian Journal of Probability and Statistics Pub Date : 2021-02-01 DOI: 10.1214/20-bjps488

F. Nascimento, Alan da Silva Assunção

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

Brazilian Journal of Probability and Statistics Pub Date : 2021-02-01 DOI: 10.1214/20-bjps469

Mahendra Saha, S. Dey, A. Yadav, Sajid Ali

{"title":"Confidence intervals of the index $C_{pk}$ for normally distributed quality characteristics using classical and Bayesian methods of estimation","authors":"Mahendra Saha, S. Dey, A. Yadav, Sajid Ali","doi":"10.1214/20-bjps469","DOIUrl":"https://doi.org/10.1214/20-bjps469","url":null,"abstract":"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.","PeriodicalId":51242,"journal":{"name":"Brazilian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41350479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15

Preface 前言

IF 1 4区数学

Brazilian Journal of Probability and Statistics Pub Date : 2021-02-01 DOI: 10.1214/20-bjps351pre

引用次数: 0