Communications in Statistics Case Studies Data Analysis and Applications最新文献_第10页

Functional time series forecasting of extreme values 极值的函数时间序列预测

Communications in Statistics Case Studies Data Analysis and Applications Pub Date : 2020-12-19 DOI: 10.1080/23737484.2020.1869629

H. Shang, Ruofan Xu

引用次数: 4

A wavelet-based approach for Johansen’s likelihood ratio test for cointegration in the presence of measurement errors: An application to CO2 emissions and real GDP data 存在测量误差的协整的约翰森似然比检验的基于小波的方法:对二氧化碳排放和实际GDP数据的应用

Communications in Statistics Case Studies Data Analysis and Applications Pub Date : 2020-12-09 DOI: 10.1080/23737484.2020.1850372

O. Habimana, K. Månsson, P. Sjölander

{"title":"A wavelet-based approach for Johansen’s likelihood ratio test for cointegration in the presence of measurement errors: An application to CO2 emissions and real GDP data","authors":"O. Habimana, K. Månsson, P. Sjölander","doi":"10.1080/23737484.2020.1850372","DOIUrl":"https://doi.org/10.1080/23737484.2020.1850372","url":null,"abstract":"Abstract We suggest a wavelet filtering technique as a remedy to the problem of measurement errors when testing for cointegration using Johansen’s (1988) likelihood ratio test. Measurement errors, which more or less are always present in empirical economic data, essentially indicates that the variable of interest (the true signal) is contaminated with noise, which may induce biased and inconsistent estimates and erroneous inference. Our Monte Carlo experiments demonstrate that measurement errors distort the statistical size of Johansen’s cointegration test in finite samples; the test is significantly oversized. A contribution and major finding of this article is that the proposed wavelet-based technique significantly improves the statistical size of the traditional Johansen test in small and medium sized samples. Since Johansen’s test is a standard cointegration test, and we demonstrate that the constantly present measurement errors in empirical data over sizes the test, this simple alteration can be used in most situations with more reliable finite sample inference. We empirically examine the long-run relation between CO2 emissions and the real GDP in the G7 countries. The traditional Johansen tests provide evidence of an equilibrium relation for Canada and weak evidence for the US. However, the suggested size-unbiased wavelet-filtering approach consistently indicates no evidence of cointegration for all six countries.","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"14 1","pages":"128 - 145"},"PeriodicalIF":0.0,"publicationDate":"2020-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88862684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Soybean production value in the Rio Grande do Sul under the GAMLSS framework 在GAMLSS框架下的南里奥格兰德州大豆产值

Communications in Statistics Case Studies Data Analysis and Applications Pub Date : 2020-12-08 DOI: 10.1080/23737484.2020.1852131

Tatiane Fontana Ribeiro, E. Seidel, R. Guerra, Fernando A. Peña-Ramírez, A. M. D. Silva

引用次数: 0

Special Issue – Communications in Statistics – Case Studies and Data Analysis: 5th Stochastic Modeling Techniques and Data Analysis International Conference 特刊-统计通讯-案例研究和数据分析:第五届随机建模技术和数据分析国际会议

Communications in Statistics Case Studies Data Analysis and Applications Pub Date : 2020-11-11 DOI: 10.1080/23737484.2020.1850108

C. Skiadas, Yiannis Dimotikalis, C. Skiadas

引用次数: 0

Modeling road traffic accidents in Mauritius using clustered longitudinal COM-Poisson with gamma random effects 利用具有伽马随机效应的聚类纵向com -泊松模型模拟毛里求斯的道路交通事故

Communications in Statistics Case Studies Data Analysis and Applications Pub Date : 2020-11-05 DOI: 10.1080/23737484.2020.1842269

N. M. Khan, Ashwinee Devi Soobhug, Z. Jannoo

{"title":"Modeling road traffic accidents in Mauritius using clustered longitudinal COM-Poisson with gamma random effects","authors":"N. M. Khan, Ashwinee Devi Soobhug, Z. Jannoo","doi":"10.1080/23737484.2020.1842269","DOIUrl":"https://doi.org/10.1080/23737484.2020.1842269","url":null,"abstract":"Abstract This article proposes a nonstationary clustered longitudinal model to analyze road traffic accident time series data from 2016 to 2017 in Mauritius. The Conway–Maxwell–Poisson model (COM-Poisson) is used as the baseline model with gamma-distributed random effects (CMP-G). Several time-variant explanatory variables are incorporated into the model specification link predictor to identify the likely causes of road crashes in the Mauritius. The proposed model competes with the popular Poisson gamma and log-normal mixtures when modeling over-dispersion. The model parameters namely the regression, serial, and dispersion effects, are estimated suitably by a generalized quasi-likelihood (GQL) estimation method while the serial parameter is treated as nuisance and estimated by method of moments. The asymptotic properties of the GQL estimators are discussed. A simulation study based on an integer-valued auto-regressive of order 1 structure (INAR(1)) with CMP-G distributed innovation terms, is also proposed to assess the performance of GQL based on the CMP-G. Data application is of road traffic accidents in Mauritius where some model criteria have been computed to assess the goodness of fits of the proposed model against the Poisson-gamma and Poisson-log normal mixtures.","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"1 1","pages":"113 - 127"},"PeriodicalIF":0.0,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73436860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Detecting long term and abrupt changes of river overflows in Slovakia 检测斯洛伐克河流溢流的长期和突然变化

Communications in Statistics Case Studies Data Analysis and Applications Pub Date : 2020-11-04 DOI: 10.1080/23737484.2020.1842268

Dominika Ballová

引用次数: 0

Auxiliary information based exponentially weighted moving co-efficient of variation control chart: An application to monitor electric conductivity for water system 基于指数加权变化控制图移动系数的辅助信息:在水系统电导率监测中的应用

Communications in Statistics Case Studies Data Analysis and Applications Pub Date : 2020-10-22 DOI: 10.1080/23737484.2020.1836533

Afshan Riaz, Muhammad Noor-ul-Amin, Hina Khan

引用次数: 3

A metafrontier production function for a Bayesian frontier model: A cross-country comparison 贝叶斯前沿模型的元前沿生产函数:跨国比较

Communications in Statistics Case Studies Data Analysis and Applications Pub Date : 2020-10-10 DOI: 10.1080/23737484.2020.1829177

P. Economou, S. Malefaki, K. Kounetas

引用次数: 0

Inference using MCMC to a new conjugate prior to positive parameters, applied in environmental data 在环境数据中应用MCMC对一种新的共轭先验正参数进行推理

Communications in Statistics Case Studies Data Analysis and Applications Pub Date : 2020-10-07 DOI: 10.1080/23737484.2020.1826368

F. Nascimento, Wires do Nascimento Moura

引用次数: 1

A topological approach of multiple correspondence analysis 多对应分析的拓扑方法

Communications in Statistics Case Studies Data Analysis and Applications Pub Date : 2020-10-01 DOI: 10.1080/23737484.2020.1830733

Rafik Abdesselam

{"title":"A topological approach of multiple correspondence analysis","authors":"Rafik Abdesselam","doi":"10.1080/23737484.2020.1830733","DOIUrl":"https://doi.org/10.1080/23737484.2020.1830733","url":null,"abstract":"ABSTRACT Topological multiple correspondence analysis (TMCA) studies a group of categorical variables defined on the same set of individuals. It is a topological method of data analysis that consists of exploring, analyzing, and representing the associations between several qualitative variables in the context of multiple correspondence analysis (MCA). It compares and classifies proximity measures to select the best one according to the data under consideration, then analyzes, interprets, and visualizes with graphic representations, the possible associations between several categorical variables relating to the known problem of MCA. Based on the notion of neighborhood graphs, some of these proximity measures are more-or-less equivalent. A topological equivalence index between two measures is defined and statistically tested according to the degree of description of the associations between the modalities of these qualitative variables. We compare proximity measures and propose a topological criterion for choosing the best association measure, adapted to the data considered, from among some of the most widely used proximity measures for categorical data. The principle of the proposed approach is illustrated using a real dataset with conventional proximity measures for binary variables from the literature. The first step is to find the proximity measure that can best be adapted to the data; the second step is to use this measure to perform the TMCA.","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"1 1","pages":"429 - 447"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86442973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1