Asta-Advances in Statistical Analysis最新文献_第7页

Comment “On the role of data, statistics and decisions in a pandemic” by Jahn et al. 评论Jahn等人的《关于大流行中数据、统计和决策的作用》。

IF 1.4 4区数学

Asta-Advances in Statistical Analysis Pub Date : 2022-06-18 DOI: 10.1007/s10182-022-00451-x

Michael Höhle

引用次数: 4

Having a ball: evaluating scoring streaks and game excitement using in-match trend estimation 拥有一个球:使用比赛趋势估计评估得分连胜和比赛兴奋

IF 1.4 4区数学

Asta-Advances in Statistical Analysis Pub Date : 2022-06-17 DOI: 10.1007/s10182-022-00452-w

Claus Thorn Ekstrøm, Andreas Kryger Jensen

{"title":"Having a ball: evaluating scoring streaks and game excitement using in-match trend estimation","authors":"Claus Thorn Ekstrøm, Andreas Kryger Jensen","doi":"10.1007/s10182-022-00452-w","DOIUrl":"10.1007/s10182-022-00452-w","url":null,"abstract":"<div><p>Many popular sports involve matches between two teams or players where each team have the possibility of scoring points throughout the match. While the overall match winner and result is interesting, it conveys little information about the underlying scoring trends throughout the match. Modeling approaches that accommodate a finer granularity of the score difference throughout the match is needed to evaluate in-game strategies, discuss scoring streaks, teams strengths, and other aspects of the game. We propose a latent Gaussian process to model the score difference between two teams and introduce the Trend Direction Index as an easily interpretable probabilistic measure of the current trend in the match as well as a measure of post-game trend evaluation. In addition we propose the Excitement Trend Index—the expected number of monotonicity changes in the running score difference—as a measure of overall game excitement. Our proposed methodology is applied to all 1143 matches from the 2019–2020 National Basketball Association season. We show how the trends can be interpreted in individual games and how the excitement score can be used to cluster teams according to how exciting they are to watch.</p></div>","PeriodicalId":55446,"journal":{"name":"Asta-Advances in Statistical Analysis","volume":"107 1-2","pages":"295 - 311"},"PeriodicalIF":1.4,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10182-022-00452-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9468995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Discussion on On the role of data, statistics and decisions in a pandemic 关于数据、统计和决策在大流行中的作用的讨论

IF 1.4 4区数学

Asta-Advances in Statistical Analysis Pub Date : 2022-06-10 DOI: 10.1007/s10182-022-00450-y

Ursula Berger, Göran Kauermann, Helmut Küchenhoff

引用次数: 5

Describing a landscape we are yet discovering 描绘了一幅我们尚未发现的风景

IF 1.4 4区数学

Asta-Advances in Statistical Analysis Pub Date : 2022-06-09 DOI: 10.1007/s10182-022-00449-5

Sebastian Contreras, Jonas Dehning, Viola Priesemann

引用次数: 3

Hierarchical clustering and matrix completion for the reconstruction of world input–output tables 世界输入输出表重构的层次聚类和矩阵补全

IF 1.4 4区数学

Asta-Advances in Statistical Analysis Pub Date : 2022-06-02 DOI: 10.1007/s10182-022-00448-6

Rodolfo Metulini, Giorgio Gnecco, Francesco Biancalani, Massimo Riccaboni

{"title":"Hierarchical clustering and matrix completion for the reconstruction of world input–output tables","authors":"Rodolfo Metulini, Giorgio Gnecco, Francesco Biancalani, Massimo Riccaboni","doi":"10.1007/s10182-022-00448-6","DOIUrl":"10.1007/s10182-022-00448-6","url":null,"abstract":"<div><p>Multi-regional input–output (I/O) matrices provide the networks of within- and cross-country economic relations. In the context of I/O analysis, the methodology adopted by national statistical offices in data collection raises the issue of obtaining reliable data in a timely fashion and it makes the reconstruction of (parts of) the I/O matrices of particular interest. In this work, we propose a method combining hierarchical clustering and matrix completion with a LASSO-like nuclear norm penalty, to predict missing entries of a partially unknown I/O matrix. Through analyses based on both real-world and synthetic I/O matrices, we study the effectiveness of the proposed method to predict missing values from both previous years data and current data related to countries similar to the one for which current data are obscured. To show the usefulness of our method, an application based on World Input–Output Database (WIOD) tables—which are an example of industry-by-industry I/O tables—is provided. Strong similarities in structure between WIOD and other I/O tables are also found, which make the proposed approach easily generalizable to them.</p></div>","PeriodicalId":55446,"journal":{"name":"Asta-Advances in Statistical Analysis","volume":"107 3","pages":"575 - 620"},"PeriodicalIF":1.4,"publicationDate":"2022-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10182-022-00448-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50004745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Comment on: On the role of data, statistics and decisions in a pandemic statistics for climate protection and health—dare (more) progress! 评论:关于数据、统计和决策在大流行中的作用，气候保护和健康统计要取得(更多)进展!

IF 1.4 4区数学

Asta-Advances in Statistical Analysis Pub Date : 2022-05-21 DOI: 10.1007/s10182-022-00447-7

Walter J. Radermacher

引用次数: 5

Tests of stochastic dominance with repeated measurements data 用重复测量数据进行随机优势检验

IF 1.4 4区数学

Asta-Advances in Statistical Analysis Pub Date : 2022-05-11 DOI: 10.1007/s10182-022-00446-8

Angel G. Angelov, Magnus Ekström

引用次数: 0

On dealing with the unknown population minimum in parametric inference 参数推理中未知总体最小值的处理

IF 1.4 4区数学

Asta-Advances in Statistical Analysis Pub Date : 2022-05-05 DOI: 10.1007/s10182-022-00445-9

Matheus Henrique Junqueira Saldanha, Adriano Kamimura Suzuki

{"title":"On dealing with the unknown population minimum in parametric inference","authors":"Matheus Henrique Junqueira Saldanha, Adriano Kamimura Suzuki","doi":"10.1007/s10182-022-00445-9","DOIUrl":"10.1007/s10182-022-00445-9","url":null,"abstract":"<div><p>A myriad of physical, biological and other phenomena are better modeled with semi-infinite distribution families, in which case not knowing the population minimum becomes a hassle when performing parametric inference. Ad hoc methods to deal with this problem exist, but are suboptimal and sometimes unfeasible. Besides, having the statistician handcraft solutions in a case-by-case basis is counterproductive. In this paper, we propose a framework under which the issue can be analyzed, and perform an extensive search in the literature for methods that could be used to solve the aforementioned problem; we also propose a method of our own. Simulation experiments were then performed to compare some methods from the literature and our proposal. We found that the straightforward method, which is to infer the population minimum by maximum likelihood, has severe difficulty in giving a good estimate for the population minimum, but manages to achieve very good inferred models. The other methods, including our proposal, involve estimating the population minimum, and we found that our method is superior to the other methods of this kind, considering the distributions simulated, followed very closely by the endpoint estimator by Alves et al. (Stat Sin 24(4):1811–1835, 2014). Although these two give much more accurate estimates for the population minimum, the straightforward method also displays some advantages, so choosing between these three methods will depend on the problem domain.</p></div>","PeriodicalId":55446,"journal":{"name":"Asta-Advances in Statistical Analysis","volume":"107 3","pages":"509 - 535"},"PeriodicalIF":1.4,"publicationDate":"2022-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43197145","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: 1

Local spatial log-Gaussian Cox processes for seismic data 地震数据的局部空间对数-高斯Cox过程

IF 1.4 4区数学

Asta-Advances in Statistical Analysis Pub Date : 2022-04-25 DOI: 10.1007/s10182-022-00444-w

Nicoletta D’Angelo, Marianna Siino, Antonino D’Alessandro, Giada Adelfio

{"title":"Local spatial log-Gaussian Cox processes for seismic data","authors":"Nicoletta D’Angelo, Marianna Siino, Antonino D’Alessandro, Giada Adelfio","doi":"10.1007/s10182-022-00444-w","DOIUrl":"10.1007/s10182-022-00444-w","url":null,"abstract":"<div><p>In this paper, we propose the use of advanced and flexible statistical models to describe the spatial displacement of earthquake data. The paper aims to account for the external geological information in the description of complex seismic point processes, through the estimation of models with space varying parameters. A local version of the Log-Gaussian Cox processes (LGCP) is introduced and applied for the first time, exploiting the inferential tools in Baddeley (Spat Stat 22:261–295, 2017), estimating the model by the local Palm likelihood. We provide methods and approaches accounting for the interaction among points, typically described by LGCP models through the estimation of the covariance parameters of the Gaussian Random Field, that in this local version are allowed to vary in space, providing a more realistic description of the clustering feature of seismic events. Furthermore, we contribute to the framework of diagnostics, outlining suitable methods for the local context and proposing a new step-wise approach addressing the particular case of multiple covariates. Overall, we show that local models provide good inferential results and could serve as the basis for future spatio-temporal local model developments, peculiar for the description of the complex seismic phenomenon.</p></div>","PeriodicalId":55446,"journal":{"name":"Asta-Advances in Statistical Analysis","volume":"106 4","pages":"633 - 671"},"PeriodicalIF":1.4,"publicationDate":"2022-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10182-022-00444-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44906683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Some measures of kurtosis and their inference on large datasets 峰度的一些度量及其在大型数据集上的推断

IF 1.4 4区数学

Asta-Advances in Statistical Analysis Pub Date : 2022-04-14 DOI: 10.1007/s10182-022-00442-y

Claudio Giovanni Borroni, Lucio De Capitani

{"title":"Some measures of kurtosis and their inference on large datasets","authors":"Claudio Giovanni Borroni, Lucio De Capitani","doi":"10.1007/s10182-022-00442-y","DOIUrl":"10.1007/s10182-022-00442-y","url":null,"abstract":"<div><p>This paper deals with the estimation of kurtosis on large datasets. It aims at overcoming two frequent limitations in applications: first, Pearson's standardized fourth moment is computed as a unique measure of kurtosis; second, the fact that data might be just samples is neglected, so that the opportunity of using suitable inferential tools, like standard errors and confidence intervals, is discarded. In the paper, some recent indexes of kurtosis are reviewed as alternatives to Pearson’s standardized fourth moment. The asymptotic distribution of their natural estimators is derived, and it is used as a tool to evaluate efficiency and to build confidence intervals. A simulation study is also conducted to provide practical indications about the choice of a suitable index. As a conclusion, researchers are warned against the use of classical Pearson’s index when the sample size is too low and/or the distribution is skewed and/or heavy-tailed. Specifically, the occurrence of heavy tails can deprive Pearson’s index of any meaning or produce unreliable confidence intervals. However, such limitations can be overcome by reverting to the reviewed alternative indexes, relying just on low-order moments.</p></div>","PeriodicalId":55446,"journal":{"name":"Asta-Advances in Statistical Analysis","volume":"106 4","pages":"573 - 607"},"PeriodicalIF":1.4,"publicationDate":"2022-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10182-022-00442-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42575110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1