Communications in Statistics Case Studies Data Analysis and Applications最新文献_第9页

Tail aligned composite quantile estimator for bootstrapping of high quantiles 用于高分位数自举的尾部对齐复合分位数估计器

Communications in Statistics Case Studies Data Analysis and Applications Pub Date : 2021-05-02 DOI: 10.1080/23737484.2021.1915900

R. S. Jagtap, Mohan Kale, V. K. Gedam

引用次数: 0

School motivation profiles of Dutch 9th graders 荷兰九年级学生求学动机分析

Communications in Statistics Case Studies Data Analysis and Applications Pub Date : 2021-05-01 DOI: 10.1080/23737484.2021.1911719

Denise M. Blom, M. Warrens, Meike Faber

{"title":"School motivation profiles of Dutch 9th graders","authors":"Denise M. Blom, M. Warrens, Meike Faber","doi":"10.1080/23737484.2021.1911719","DOIUrl":"https://doi.org/10.1080/23737484.2021.1911719","url":null,"abstract":"Abstract The aim of this study was to identify school motivation profiles of Dutch 9th grade students in a four-dimensional motivation space, including mastery, performance, social and extrinsic motivation. Multiple clustering methods (K-means, K-medoids, restricted latent profile analysis) and multiple indices for selecting the optimal number of clusters were applied. The statistical selection methods did not completely concur on the optimal number of clusters, but a clear common denominator was provided by the Calinski-Harabasz index and the minimum and mean Silhouette values. All three indices indicated two clusters as the optimal number, regardless of the clustering method used: one cluster of 9th graders with high average scores on all dimensions and one cluster with low mean scores on all dimensions. In addition, we explored the substantive interpretation of multiple cluster solutions. It was discovered that most students are in clusters that can be classified into one of three profile types that may differ in level: (1) approximately equal mean scores on all dimensions, (2) relative high mean scores on mastery and social motivation, and (3) a relatively low mean score on performance motivation. The latter profile type is believed to be a new discovery.","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"58 2 1","pages":"359 - 381"},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76868487","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: 0

Disease mapping of biomarkers for breast cancer in Tehran using spatial joint model: A Bayesian perspective 利用空间联合模型绘制德黑兰乳腺癌生物标志物的疾病图谱:贝叶斯视角

Communications in Statistics Case Studies Data Analysis and Applications Pub Date : 2021-03-14 DOI: 10.1080/23737484.2021.1882354

T. Baghfalaki, M. Kamarehee, M. Ganjali, A. Shabbak, M. Khayamzadeh, M. Akbari

引用次数: 0

Detecting time lag between a pair of time series using visibility graph algorithm 利用可见性图算法检测一对时间序列之间的时间滞后

Communications in Statistics Case Studies Data Analysis and Applications Pub Date : 2021-02-26 DOI: 10.1080/23737484.2021.1882356

Majnu John, J. Ferbinteanu

引用次数: 3

A flexible probability model for proportion data: Unit-half-normal distribution 一种灵活的比例数据概率模型:单位半正态分布

Communications in Statistics Case Studies Data Analysis and Applications Pub Date : 2021-02-11 DOI: 10.1080/23737484.2021.1882355

H. Bakouch, A. S. Nik, A. Asgharzadeh, Hugo S. Salinas

引用次数: 13

A double mixture autoregressive model of commodity prices 商品价格的双混合自回归模型

Communications in Statistics Case Studies Data Analysis and Applications Pub Date : 2021-02-11 DOI: 10.1080/23737484.2021.1882353

Gilbert Mbara

{"title":"A double mixture autoregressive model of commodity prices","authors":"Gilbert Mbara","doi":"10.1080/23737484.2021.1882353","DOIUrl":"https://doi.org/10.1080/23737484.2021.1882353","url":null,"abstract":"Abstract Many commodity prices exhibit boom-bust type behavior: sustained periods of price increases, followed by sudden sharp collapses. Since around the year 2000, booms have become longer while busts have tended to be short but steep, suggesting a structural change in growth and persistence. We model these features of the data using a novel double mixture autoregression with two independent hidden Markov chains. One chain tracks shifts in mean growth rates that account for rising and falling prices, while a second chain tracks changes in volatility and lag-structure. While the two chains are independent, the persistence of price growth depends on the volatility state, which allows the lag-structure to vary across variance regimes. Estimation requires a two-stage Fisherian approach. Initially, location-related parameters are estimated while suppressing the underlying autoregressive structure. These parameters are then held fixed while the optimal lag-structure across variance regimes is determined. We apply the model to three industrial commodities price time series: Crude Oil, Aluminum, and Rubber. We find that in each case, the model captures boom and bust cycles, with data from more recent periods exhibiting higher volatility, longer price rallies, and steeper collapses.","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"97 1","pages":"249 - 270"},"PeriodicalIF":0.0,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79188194","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

Tweedie, Bar-Lev, and Enis class of leptokurtic distributions as a candidate for modeling real data Tweedie, Bar-Lev和Enis类的细峰分布作为真实数据建模的候选

Communications in Statistics Case Studies Data Analysis and Applications Pub Date : 2021-02-11 DOI: 10.1080/23737484.2021.1880988

S. Bar-Lev, A. Batsidis, P. Economou

{"title":"Tweedie, Bar-Lev, and Enis class of leptokurtic distributions as a candidate for modeling real data","authors":"S. Bar-Lev, A. Batsidis, P. Economou","doi":"10.1080/23737484.2021.1880988","DOIUrl":"https://doi.org/10.1080/23737484.2021.1880988","url":null,"abstract":"Abstract Modeling real life data is often a demanding task and plethora of distributional models have been proposed in the statistical literature in an attempt to describe different data sets in a better way than those used to describe them. In this article, we establish a broad pool of families of parametric distributions previously used in the literature. This pool, which includes 23 parametric models of distributions, is implemented to test the fit of its models to 17 data sets having different characteristics. In doing so, we will mainly pay attention to a three-parameter model that includes the class of natural exponential families generated by positive stable distributions. Indeed, this is the class we wish to pinpoint in this article and highlight its importance for modeling real data sets. The class is shown to be rather competitive alternative to some well-known parametric models in the pool especially when applied to leptokurtic data sets is available. Appropriate R codes which include all parametric models in the pool are provided in a supplementary file for further applications and implementations for other data sets. Supplemental data for this article is available online at https://doi.org/10.1080/23737484.2021.1880988","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"65 1","pages":"229 - 248"},"PeriodicalIF":0.0,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85802369","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

Bayesian inference for the Birnbaum–Saunders autoregressive conditional duration model with application to high-frequency financial data Birnbaum-Saunders自回归条件期限模型的贝叶斯推断及其在高频金融数据中的应用

Communications in Statistics Case Studies Data Analysis and Applications Pub Date : 2021-01-28 DOI: 10.1080/23737484.2021.1874571

Nascimento Fernando, Leao Jeremias, H. Saulo

引用次数: 2

Geographically weighted Poisson regression models with different kernels: Application to road traffic accident data 不同核的地理加权泊松回归模型:在道路交通事故数据中的应用

Communications in Statistics Case Studies Data Analysis and Applications Pub Date : 2021-01-25 DOI: 10.1080/23737484.2020.1869628

Ghanim Al-Hasani, M. Asaduzzaman, A. Soliman

{"title":"Geographically weighted Poisson regression models with different kernels: Application to road traffic accident data","authors":"Ghanim Al-Hasani, M. Asaduzzaman, A. Soliman","doi":"10.1080/23737484.2020.1869628","DOIUrl":"https://doi.org/10.1080/23737484.2020.1869628","url":null,"abstract":"Abstract Geographically weighted Poisson regression (GWPR) models are the class of spatial count regression models that capture the localization effect on various influencing factors on the dependent variable. The main challenge with the GWPR models is to set appropriate kernel function to give weights for each neighboring point during the model calibration. In this article, we consider GWPR models for many different kernel functions, including box-car, bi-square, tri-cube, exponential, and Gaussian function. Likelihood function, parameter estimation, and model selection criteria have been shown in details. We applied the model formulation to the road traffic accident (RTA) data in Oman as the country is one of the largest RTA-prone countries in the Gulf region. Akaike information criterion, corrected Akaike information criterion, and geographically weighted deviance have been used to assess the model fitting. The model with the exponential kernel weighted function provides the best fit for the data and captures the spatial heterogeneity and factors better with the exponential kernel weighting function.","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"70 1","pages":"166 - 181"},"PeriodicalIF":0.0,"publicationDate":"2021-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86905651","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: 6

Modeling and forecasting life expectancy in India: A systematic approach 印度人预期寿命的建模和预测:一种系统的方法

Communications in Statistics Case Studies Data Analysis and Applications Pub Date : 2021-01-12 DOI: 10.1080/23737484.2020.1869630

Abhishek Singh, S. Hasija

引用次数: 1