Asta-Advances in Statistical Analysis最新文献_第6页

Multiple imputation of ordinal missing not at random data 非随机数据序号缺失的多重插补

IF 1.4 4区数学

Asta-Advances in Statistical Analysis Pub Date : 2022-08-22 DOI: 10.1007/s10182-022-00461-9

Angelina Hammon

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引用次数: 0

Testing for the presence of treatment effect under selection on observables 在可观察器上选择下治疗效果的存在性测试

IF 1.4 4区数学

Asta-Advances in Statistical Analysis Pub Date : 2022-08-09 DOI: 10.1007/s10182-022-00454-8

Pier Luigi Conti, Livia De Giovanni

引用次数: 0

Authors’ response: on the role of data, statistics and decisions in a pandemic 作者的回应:关于数据、统计和决策在大流行中的作用

IF 1.4 4区数学

Asta-Advances in Statistical Analysis Pub Date : 2022-07-30 DOI: 10.1007/s10182-022-00460-w

Beate Jahn, Sarah Friedrich, Joachim Behnke, Joachim Engel, Ursula Garczarek, Ralf Münnich, Markus Pauly, Adalbert Wilhelm, Olaf Wolkenhauer, Markus Zwick, Uwe Siebert, Tim Friede

引用次数: 1

A new price index for multi-period and multilateral comparisons 用于多时期和多边比较的新价格指数

IF 1.4 4区数学

Asta-Advances in Statistical Analysis Pub Date : 2022-07-12 DOI: 10.1007/s10182-022-00457-5

Mario Faliva, Consuelo Rubina Nava, Maria Grazia Zoia

引用次数: 0

Editorial special issue: Statistics in sports 社论特刊:体育统计

IF 1.4 4区数学

Asta-Advances in Statistical Analysis Pub Date : 2022-07-11 DOI: 10.1007/s10182-022-00453-9

Andreas Groll, Dominik Liebl

引用次数: 3

Integration of model-based recursive partitioning with bias reduction estimation: a case study assessing the impact of Oliver’s four factors on the probability of winning a basketball game 基于模型的递归划分与偏差减少估计的集成:一个评估奥利弗的四个因素对篮球比赛获胜概率影响的案例研究

IF 1.4 4区数学

Asta-Advances in Statistical Analysis Pub Date : 2022-07-04 DOI: 10.1007/s10182-022-00456-6

Manlio Migliorati, Marica Manisera, Paola Zuccolotto

{"title":"Integration of model-based recursive partitioning with bias reduction estimation: a case study assessing the impact of Oliver’s four factors on the probability of winning a basketball game","authors":"Manlio Migliorati, Marica Manisera, Paola Zuccolotto","doi":"10.1007/s10182-022-00456-6","DOIUrl":"10.1007/s10182-022-00456-6","url":null,"abstract":"<div><p>In this contribution, we investigate the importance of Oliver’s Four Factors, proposed in the literature to identify a basketball team’s strengths and weaknesses in terms of shooting, turnovers, rebounding and free throws, as success drivers of a basketball game. In order to investigate the role of each factor in the success of a team in a match, we applied the MOdel-Based recursive partitioning (MOB) algorithm to real data concerning 19,138 matches of 16 National Basketball Association (NBA) regular seasons (from 2004–2005 to 2019–2020). MOB, instead of fitting one global Generalized Linear Model (GLM) to all observations, partitions the observations according to selected partitioning variables and estimates several ad hoc local GLMs for subgroups of observations. The manuscript’s aim is twofold: (1) in order to deal with (quasi) separation problems leading to convergence problems in the numerical solution of Maximum Likelihood (ML) estimation in MOB, we propose a methodological extension of GLM-based recursive partitioning from standard ML estimation to bias-reduced (BR) estimation; and (2) we apply the BR-based GLM trees to basketball analytics. The results show models very easy to interpret that can provide useful support to coaching staff’s decisions.</p></div>","PeriodicalId":55446,"journal":{"name":"Asta-Advances in Statistical Analysis","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10182-022-00456-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9114892","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: 0

Correction to: Local spatial log-Gaussian Cox processes for seismic data 校正: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 : 2022-06-30 DOI: 10.1007/s10182-022-00455-7

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

引用次数: 0

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":null,"pages":null},"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