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Confounder Adjustment in Shape-on-Scalar Regression Model: Corpus Callosum Shape Alterations in Alzheimer’s Disease 形状-标量回归模型的混杂调整:阿尔茨海默病胼胝体形状改变
Stats Pub Date : 2023-09-28 DOI: 10.3390/stats6040061
Harshita Dogra, Shengxian Ding, Miyeon Yeon, Rongjie Liu, Chao Huang
{"title":"Confounder Adjustment in Shape-on-Scalar Regression Model: Corpus Callosum Shape Alterations in Alzheimer’s Disease","authors":"Harshita Dogra, Shengxian Ding, Miyeon Yeon, Rongjie Liu, Chao Huang","doi":"10.3390/stats6040061","DOIUrl":"https://doi.org/10.3390/stats6040061","url":null,"abstract":"Large-scale imaging studies often face challenges stemming from heterogeneity arising from differences in geographic location, instrumental setups, image acquisition protocols, study design, and latent variables that remain undisclosed. While numerous regression models have been developed to elucidate the interplay between imaging responses and relevant covariates, limited attention has been devoted to cases where the imaging responses pertain to the domain of shape. This adds complexity to the problem of imaging heterogeneity, primarily due to the unique properties inherent to shape representations, including nonlinearity, high-dimensionality, and the intricacies of quotient space geometry. To tackle this intricate issue, we propose a novel approach: a shape-on-scalar regression model that incorporates confounder adjustment. In particular, we leverage the square root velocity function to extract elastic shape representations which are embedded within the linear Hilbert space of square integrable functions. Subsequently, we introduce a shape regression model aimed at characterizing the intricate relationship between elastic shapes and covariates of interest, all while effectively managing the challenges posed by imaging heterogeneity. We develop comprehensive procedures for estimating and making inferences about the unknown model parameters. Through real-data analysis, our method demonstrates its superiority in terms of estimation accuracy when compared to existing approaches.","PeriodicalId":93142,"journal":{"name":"Stats","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135425878","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
Terroir in View of Bibliometrics 文献计量学视角下的风土
Stats Pub Date : 2023-09-27 DOI: 10.3390/stats6040060
Christos Stefanis, Elpida Giorgi, Giorgios Tselemponis, Chrysa Voidarou, Ioannis Skoufos, Athina Tzora, Christina Tsigalou, Yiannis Kourkoutas, Theodoros C. Constantinidis, Eugenia Bezirtzoglou
{"title":"Terroir in View of Bibliometrics","authors":"Christos Stefanis, Elpida Giorgi, Giorgios Tselemponis, Chrysa Voidarou, Ioannis Skoufos, Athina Tzora, Christina Tsigalou, Yiannis Kourkoutas, Theodoros C. Constantinidis, Eugenia Bezirtzoglou","doi":"10.3390/stats6040060","DOIUrl":"https://doi.org/10.3390/stats6040060","url":null,"abstract":"This study aimed to perform a bibliometric analysis of terroir and explore its conceptual horizons. Advancements in terroir research until 2022 were investigated using the Scopus database, R, and VOSviewer. Out of the 907 results, the most prevalent document types were articles (771) and reviews (70). The annual growth rate of published manuscripts in this field was 7.8%. The research on terroir encompassed a wide range of disciplines, with significant contributions from Agricultural and Biological Sciences, Social Sciences, Environmental Science, Biochemistry, Genetics, and Molecular Biology. Through keyword analysis, the study identified the most frequently occurring terms in titles, abstracts, and keywords fields, including ‘terroir’, ‘wine’, ‘soil’, ‘wines’, ‘grape’, ‘analysis’, ‘vineyard’, ‘composition’, and ‘climate’. A trend topic analysis revealed that research in terroir primarily focused on the geo-ecology and physiology of grapes. Furthermore, considerable attention was given to methods and techniques related to the physicochemical, sensory, and microbial characterization of terroir and various aspects of the wine industry. Initially, the research in this domain was focused on terroir, authenticity, grapevine, soils, soil moisture, and wine quality. However, over time, the research agenda expanded to include topics such as food analysis, viticulture, wine, taste, sustainability, and climate change. New research areas emerged, including phenolic compounds, anthocyanin, phenols, sensory analysis, and precision agriculture—all of which became integral components of the scientific studies on terroir. Overall, this study provided valuable insights into the historical trends and current developments in terroir research, contributing to our understanding of the frontiers in this field.","PeriodicalId":93142,"journal":{"name":"Stats","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135536911","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
A Family of Finite Mixture Distributions for Modelling Dispersion in Count Data 一组有限混合分布用于模拟计数数据中的色散
Stats Pub Date : 2023-09-18 DOI: 10.3390/stats6030059
Seng Huat Ong, Shin Zhu Sim, Shuangzhe Liu, Hari M. Srivastava
{"title":"A Family of Finite Mixture Distributions for Modelling Dispersion in Count Data","authors":"Seng Huat Ong, Shin Zhu Sim, Shuangzhe Liu, Hari M. Srivastava","doi":"10.3390/stats6030059","DOIUrl":"https://doi.org/10.3390/stats6030059","url":null,"abstract":"This paper considers the construction of a family of discrete distributions with the flexibility to cater for under-, equi- and over-dispersion in count data using a finite mixture model based on standard distributions. We are motivated to introduce this family because its simple finite mixture structure adds flexibility and facilitates application and use in analysis. The family of distributions is exemplified using a mixture of negative binomial and shifted negative binomial distributions. Some basic and probabilistic properties are derived. We perform hypothesis testing for equi-dispersion and simulation studies of their power and consider parameter estimation via maximum likelihood and probability-generating-function-based methods. The utility of the distributions is illustrated via their application to real biological data sets exhibiting under-, equi- and over-dispersion. It is shown that the distribution fits better than the well-known generalized Poisson and COM–Poisson distributions for handling under-, equi- and over-dispersion in count data.","PeriodicalId":93142,"journal":{"name":"Stats","volume":"173 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135202745","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
A Detecting System for Abrupt Changes in Temporal Incidence Rate of COVID-19 and Other Pandemics 新型冠状病毒病及其他大流行发病时间突变检测系统
Stats Pub Date : 2023-09-18 DOI: 10.3390/stats6030058
Jiecheng Song, Guanchao Tong, Wei Zhu
{"title":"A Detecting System for Abrupt Changes in Temporal Incidence Rate of COVID-19 and Other Pandemics","authors":"Jiecheng Song, Guanchao Tong, Wei Zhu","doi":"10.3390/stats6030058","DOIUrl":"https://doi.org/10.3390/stats6030058","url":null,"abstract":"COVID-19 spread dramatically across the world in the beginning of 2020. This paper presents a novel alert system that will detect abrupt changes in the COVID-19 or other pandemic incidence rate through the estimated time-varying reproduction number (Rt). We applied the system to detect abrupt changes in the COVID-19 pandemic incidence rates in thirteen world regions with eight in the US and five across the world. Subsequently, we also evaluated the system with the 2009 H1N1 pandemic in Hong Kong. Our system performs well in detecting both the abrupt increases and decreases. Users of the system can obtain accurate information on the changing trend of the pandemic to avoid being misled by low incidence numbers. The world may face other threatening pandemics in the future; therefore, it is crucial to have a reliable alert system to detect impending abrupt changes in the daily incidence rates. An added benefit of the system is its ability to detect the emergence of viral mutations, as different virus strains are likely to have different infection rates.","PeriodicalId":93142,"journal":{"name":"Stats","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135202902","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
Orthonormal F Contrasts for Factors with Ordered Levels in Two-Factor Fixed-Effects ANOVAs 双因素固定效应方差分析中有序水平因子的正交F对比
Stats Pub Date : 2023-09-01 DOI: 10.3390/stats6030057
J. C. W. Rayner, G. C. Livingston
{"title":"Orthonormal F Contrasts for Factors with Ordered Levels in Two-Factor Fixed-Effects ANOVAs","authors":"J. C. W. Rayner, G. C. Livingston","doi":"10.3390/stats6030057","DOIUrl":"https://doi.org/10.3390/stats6030057","url":null,"abstract":"In multifactor fixed-effects ANOVAs, we show how to construct orthonormal F contrasts for main effects. Our primary focus is the case when the levels of the factor of interest are ordered. Likewise, in multifactor equally replicated fixed-effects ANOVAs, we show how to construct orthonormal F contrasts for interactions. The primary focus here is on interactions when both factors are ordered, although the approach also applies if just one factor is ordered. Interactions with both factors ordered may be interpreted in terms of generalised correlations.","PeriodicalId":93142,"journal":{"name":"Stats","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49004821","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
Investigating Self-Rationalizing Models for Commonsense Reasoning 常识推理的自合理化模型研究
Stats Pub Date : 2023-08-29 DOI: 10.3390/stats6030056
Fanny Rancourt, Paula Vondrlik, Diego Maupomé, Marie-Jean Meurs
{"title":"Investigating Self-Rationalizing Models for Commonsense Reasoning","authors":"Fanny Rancourt, Paula Vondrlik, Diego Maupomé, Marie-Jean Meurs","doi":"10.3390/stats6030056","DOIUrl":"https://doi.org/10.3390/stats6030056","url":null,"abstract":"The rise of explainable natural language processing spurred a bulk of work on datasets augmented with human explanations, as well as technical approaches to leverage them. Notably, generative large language models offer new possibilities, as they can output a prediction as well as an explanation in natural language. This work investigates the capabilities of fine-tuned text-to-text transfer Transformer (T5) models for commonsense reasoning and explanation generation. Our experiments suggest that while self-rationalizing models achieve interesting results, a significant gap remains: classifiers consistently outperformed self-rationalizing models, and a substantial fraction of model-generated explanations are not valid. Furthermore, training with expressive free-text explanations substantially altered the inner representation of the model, suggesting that they supplied additional information and may bridge the knowledge gap. Our code is publicly available, and the experiments were run on open-access datasets, hence allowing full reproducibility.","PeriodicalId":93142,"journal":{"name":"Stats","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47029258","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
Statistical Modeling of Implicit Functional Relations 隐函数关系的统计建模
Stats Pub Date : 2023-08-25 DOI: 10.3390/stats6030055
S. Lipovetsky
{"title":"Statistical Modeling of Implicit Functional Relations","authors":"S. Lipovetsky","doi":"10.3390/stats6030055","DOIUrl":"https://doi.org/10.3390/stats6030055","url":null,"abstract":"This study considers the statistical estimation of relations presented by implicit functions. Such structures define mutual interconnections of variables rather than outcome variable dependence by predictor variables considered in regular regression analysis. For a simple case of two variables, pairwise regression modeling produces two different lines of each variable dependence using another variable, but building an implicit relation yields one invertible model composed of two simple regressions. Modeling an implicit linear relation for multiple variables can be expressed as a generalized eigenproblem of the covariance matrix of the variables in the metric of the covariance matrix of their errors. For unknown errors, this work describes their estimation by the residual errors of each variable in its regression by the other predictors. Then, the generalized eigenproblem can be reduced to the diagonalization of a special matrix built from the variables’ covariance matrix and its inversion. Numerical examples demonstrate the eigenvector solution’s good properties for building a unique equation of the relations between all variables. The proposed approach can be useful in practical regression modeling with all variables containing unobserved errors, which is a common situation for the applied problems.","PeriodicalId":93142,"journal":{"name":"Stats","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42159354","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
Statistical Predictors of Project Management Maturity 项目管理成熟度的统计预测因子
Stats Pub Date : 2023-08-15 DOI: 10.3390/stats6030054
Helder Jose Celani de Souza, V. Salomon, Carlos Eduardo Sanches da Silva
{"title":"Statistical Predictors of Project Management Maturity","authors":"Helder Jose Celani de Souza, V. Salomon, Carlos Eduardo Sanches da Silva","doi":"10.3390/stats6030054","DOIUrl":"https://doi.org/10.3390/stats6030054","url":null,"abstract":"Global scenarios of organizations show investments wasted in projects with poor performances in more than 11 percent of cases, according to the Project Management Institute. This research aims to guide organizations in assertively investing in the right pertinent factors to improve project success rates and speed up project management maturity at a higher accuracy level using statistical predictions. Challenging existing drivers for project management maturity models and expanding their current practical view will be the result of a quantitative methodology based on a survey supported by data collection targeting the project management community in Brazil. The originality and value of this research are in contributing to the development of new project maturity models statistically supported by the increasing rate of maturity accuracy, which can be continually improved by confident data input into the model. The results show a high correlation between the performance measurement system and the project success rate associated with project management maturity. In addition, this research contemplates the relationship between organizational culture, business type, and project management office and project management maturity.","PeriodicalId":93142,"journal":{"name":"Stats","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48820979","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
Multi-Step-Ahead Prediction Intervals for Nonparametric Autoregressions via Bootstrap: Consistency, Debiasing, and Pertinence 基于Bootstrap的非参数自回归的多步预测区间：一致性、去偏性和相关性
Stats Pub Date : 2023-08-11 DOI: 10.3390/stats6030053
D. Politis, Kejin Wu
{"title":"Multi-Step-Ahead Prediction Intervals for Nonparametric Autoregressions via Bootstrap: Consistency, Debiasing, and Pertinence","authors":"D. Politis, Kejin Wu","doi":"10.3390/stats6030053","DOIUrl":"https://doi.org/10.3390/stats6030053","url":null,"abstract":"To address the difficult problem of the multi-step-ahead prediction of nonparametric autoregressions, we consider a forward bootstrap approach. Employing a local constant estimator, we can analyze a general type of nonparametric time-series model and show that the proposed point predictions are consistent with the true optimal predictor. We construct a quantile prediction interval that is asymptotically valid. Moreover, using a debiasing technique, we can asymptotically approximate the distribution of multi-step-ahead nonparametric estimation by the bootstrap. As a result, we can build bootstrap prediction intervals that are pertinent, i.e., can capture the model estimation variability, thus improving the standard quantile prediction intervals. Simulation studies are presented to illustrate the performance of our point predictions and pertinent prediction intervals for finite samples.","PeriodicalId":93142,"journal":{"name":"Stats","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46813674","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
On the Extreme Value H-Function 关于极值h函数
Stats Pub Date : 2023-08-04 DOI: 10.3390/stats6030051
P. N. Rathie, L. Ozelim, Felipe Quintino, Tiago A. da Fonseca
{"title":"On the Extreme Value H-Function","authors":"P. N. Rathie, L. Ozelim, Felipe Quintino, Tiago A. da Fonseca","doi":"10.3390/stats6030051","DOIUrl":"https://doi.org/10.3390/stats6030051","url":null,"abstract":"In the present paper, a new special function, the so-called extreme value H-function, is introduced. This new function, which is a generalization of the H-function with a particular set of parameters, appears while dealing with products and quotients of a wide class of extreme value random variables. Some properties, special cases and a series representation are provided. Some statistical applications are also briefly discussed.","PeriodicalId":93142,"journal":{"name":"Stats","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47291323","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
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