Asta-Advances in Statistical Analysis最新文献_第10页

Small area estimation of socioeconomic indicators for sampled and unsampled domains 抽样和未抽样地区社会经济指标的小面积估计

IF 1.4 4区数学

Asta-Advances in Statistical Analysis Pub Date : 2021-11-19 DOI: 10.1007/s10182-021-00426-4

Jan Pablo Burgard, Domingo Morales, Anna-Lena Wölwer

{"title":"Small area estimation of socioeconomic indicators for sampled and unsampled domains","authors":"Jan Pablo Burgard, Domingo Morales, Anna-Lena Wölwer","doi":"10.1007/s10182-021-00426-4","DOIUrl":"10.1007/s10182-021-00426-4","url":null,"abstract":"<div><p>Socioeconomic indicators play a crucial role in monitoring political actions over time and across regions. Income-based indicators such as the median income of sub-populations can provide information on the impact of measures, e.g., on poverty reduction. Regional information is usually published on an aggregated level. Due to small sample sizes, these regional aggregates are often associated with large standard errors or are missing if the region is unsampled or the estimate is simply not published. For example, if the median income of Hispanic or Latino Americans from the American Community Survey is of interest, some county-year combinations are not available. Therefore, a comparison of different counties or time-points is partly not possible. We propose a new predictor based on small area estimation techniques for aggregated data and bivariate modeling. This predictor provides empirical best predictions for the partially unavailable county-year combinations. We provide an analytical approximation to the mean squared error. The theoretical findings are backed up by a large-scale simulation study. Finally, we return to the problem of estimating the county-year estimates for the median income of Hispanic or Latino Americans and externally validate the estimates.</p></div>","PeriodicalId":55446,"journal":{"name":"Asta-Advances in Statistical Analysis","volume":"106 2","pages":"287 - 314"},"PeriodicalIF":1.4,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10182-021-00426-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50038566","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

Small area estimation of socioeconomic indicators for sampled and unsampled domains 抽样和未抽样地区社会经济指标的小面积估计

IF 1.4 4区数学

Asta-Advances in Statistical Analysis Pub Date : 2021-11-19 DOI: 10.1007/s10182-021-00426-4

J. P. Burgard, D. Morales, Anna-Lena Wölwer

引用次数: 0

Introducing LASSO-type penalisation to generalised joint regression modelling for count data 在计数数据的广义联合回归模型中引入lasso型惩罚

IF 1.4 4区数学

Asta-Advances in Statistical Analysis Pub Date : 2021-11-12 DOI: 10.1007/s10182-021-00425-5

Hendrik van der Wurp, Andreas Groll

引用次数: 1

Density estimation via Bayesian inference engines 基于贝叶斯推理引擎的密度估计

IF 1.4 4区数学

Asta-Advances in Statistical Analysis Pub Date : 2021-11-01 DOI: 10.1007/s10182-021-00422-8

M. P. Wand, J. C. F. Yu

引用次数: 1

RR-classifier: a nonparametric classification procedure in multidimensional space based on relative ranks RR分类器：一种基于相对秩的多维空间非参数分类方法

IF 1.4 4区数学

Asta-Advances in Statistical Analysis Pub Date : 2021-10-21 DOI: 10.1007/s10182-021-00423-7

Ondrej Vencalek, Olusola Samuel Makinde

引用次数: 1

Hierarchical Bayes modelling of penalty conversion rates of Bundesliga players 德甲球员点球转化率的层次贝叶斯模型

IF 1.4 4区数学

Asta-Advances in Statistical Analysis Pub Date : 2021-10-05 DOI: 10.1007/s10182-021-00420-w

Christoph Hanck, Martin C. Arnold

引用次数: 1

Simultaneous inference for functional data in sports biomechanics 运动生物力学中功能数据的同时推理

IF 1.4 4区数学

Asta-Advances in Statistical Analysis Pub Date : 2021-10-01 DOI: 10.1007/s10182-021-00418-4

Todd Colin Pataky, Konrad Abramowicz, Dominik Liebl, Alessia Pini, Sara Sjöstedt de Luna, Lina Schelin

{"title":"Simultaneous inference for functional data in sports biomechanics","authors":"Todd Colin Pataky, Konrad Abramowicz, Dominik Liebl, Alessia Pini, Sara Sjöstedt de Luna, Lina Schelin","doi":"10.1007/s10182-021-00418-4","DOIUrl":"10.1007/s10182-021-00418-4","url":null,"abstract":"<div><p>The recent sports science literature conveys a growing interest in robust statistical methods to analyze smooth, regularly-sampled functional data. This paper focuses on the inferential problem of identifying the parts of a functional domain where two population means differ. We considered four approaches recently used in sports science: interval-wise testing (IWT), statistical parametric mapping (SPM), statistical nonparametric mapping (SnPM) and the Benjamini-Hochberg (BH) procedure for false discovery control. We applied these procedures to both six representative sports science datasets, and also to systematically varied simulated datasets which replicated ten signal- and/or noise-relevant parameters that were identified in the experimental datasets. We observed generally higher IWT and BH sensitivity for five of the six experimental datasets. BH was the most sensitive procedure in simulation, but also had relatively high false positive rates (generally > 0.1) which increased sharply (> 0.3) in certain extreme simulation scenarios including highly rough data. SPM and SnPM were more sensitive than IWT in simulation except for (1) high roughness, (2) high nonstationarity, and (3) highly nonuniform smoothness. These results suggest that the optimum procedure is both signal and noise-dependent. We conclude that: (1) BH is most sensitive but also susceptible to high false positive rates, (2) IWT, SPM and SnPM appear to have relatively inconsequential differences in terms of domain identification sensitivity, except in cases of extreme signal/noise characteristics, where IWT appears to be superior at identifying a greater portion of the true signal.</p></div>","PeriodicalId":55446,"journal":{"name":"Asta-Advances in Statistical Analysis","volume":"107 1-2","pages":"369 - 392"},"PeriodicalIF":1.4,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10182-021-00418-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48085902","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: 5

A Bayesian nonparametric multi-sample test in any dimension 任意维的贝叶斯非参数多样本检验

IF 1.4 4区数学

Asta-Advances in Statistical Analysis Pub Date : 2021-09-28 DOI: 10.1007/s10182-021-00419-3

Luai Al-Labadi, Forough Fazeli Asl, Zahra Saberi

引用次数: 1

Estimation of final standings in football competitions with a premature ending: the case of COVID-19 过早结束的足球比赛最终排名的估计:以COVID-19为例

IF 1.4 4区数学

Asta-Advances in Statistical Analysis Pub Date : 2021-09-02 DOI: 10.1007/s10182-021-00415-7

P. Gorgi, S. J. Koopman, R. Lit

{"title":"Estimation of final standings in football competitions with a premature ending: the case of COVID-19","authors":"P. Gorgi, S. J. Koopman, R. Lit","doi":"10.1007/s10182-021-00415-7","DOIUrl":"10.1007/s10182-021-00415-7","url":null,"abstract":"<div><p>We study an alternative approach to determine the final league table in football competitions with a premature ending. For several countries, a premature ending of the 2019/2020 football season has occurred due to the COVID-19 pandemic. We propose a model-based method as a possible alternative to the use of the incomplete standings to determine the final table. This method measures the performance of the teams in the matches of the season that have been played and predicts the remaining non-played matches through a paired-comparison model. The main advantage of the method compared to the incomplete standings is that it takes account of the bias in the performance measure due to the schedule of the matches in a season. Therefore, the resulting ranking of the teams based on our proposed method can be regarded as more fair in this respect. A forecasting study based on historical data of seven of the main European competitions is used to validate the method. The empirical results suggest that the model-based approach produces more accurate predictions of the true final standings than those based on the incomplete standings.</p></div>","PeriodicalId":55446,"journal":{"name":"Asta-Advances in Statistical Analysis","volume":"107 1-2","pages":"233 - 250"},"PeriodicalIF":1.4,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10182-021-00415-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9116379","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: 6

Component-based structural equation modeling for the assessment of psycho-social aspects and performance of athletes 基于组件的结构方程模型对运动员心理社会方面和表现的评估

IF 1.4 4区数学

Asta-Advances in Statistical Analysis Pub Date : 2021-08-31 DOI: 10.1007/s10182-021-00417-5

Rosa Fabbricatore, Maria Iannario, Rosaria Romano, Domenico Vistocco

{"title":"Component-based structural equation modeling for the assessment of psycho-social aspects and performance of athletes","authors":"Rosa Fabbricatore, Maria Iannario, Rosaria Romano, Domenico Vistocco","doi":"10.1007/s10182-021-00417-5","DOIUrl":"10.1007/s10182-021-00417-5","url":null,"abstract":"<div><p>Recent studies have pointed out the effect of personality traits on athletes’ performance and success; however, fewer analyses have focused the relation among these features and specific athletic behaviors, skills, and strategies to enhance performance. To fill this void, the present paper provides evidence on what personality traits mostly affect athletes’ mental skills and, in turn, their effect on the performance of a sample of elite swimmers. The main findings were obtained by exploiting a component-based structural equation modeling which allows to analyze the relationships among some psychological constructs, measuring personality traits and mental skills, and a construct measuring sports performance. The partial least squares path modeling was employed, as it is the most recognized method among the component-based approaches. The introduced method simultaneously encompasses latent and emergent variables. Rather than focusing only on objective behaviors or game/race outcomes, such an approach evaluates variables not directly observable related to sport performance, such as cognition and affect, considering measurement error and measurement invariance, as well as the validity and reliability of the obtained latent constructs. The obtained results could be an asset to design strategies and interventions both for coaches and swimmers establishing an innovative use of statistical methods for maximizing athletes’ performance and well-being.</p></div>","PeriodicalId":55446,"journal":{"name":"Asta-Advances in Statistical Analysis","volume":"107 1-2","pages":"343 - 367"},"PeriodicalIF":1.4,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10182-021-00417-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46089199","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: 3