Bahari Fayyaz, Parsi Safar, Ganjali Mojtaba
Department of Statistics, Faculty of Mathematical Sciences, University of Mohaghegh Ardabil, Ardabil, Iran.
Department of Statistics, Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran.
J Appl Stat. 2020 Feb 4;48(2):285-300. doi: 10.1080/02664763.2020.1723504. eCollection 2021.
In this paper, we study the performance of a soccer player based on analysing an incomplete data set. To achieve this aim, we fit the bivariate Rayleigh distribution to the soccer dataset by the maximum likelihood method. In this way, the missing data and right censoring problems, that usually happen in such studies, are considered. Our aim is to inference about the performance of a soccer player by considering the stress and strength components. The first goal of the player of interest in a match is assumed as the stress component and the second goal of the match is assumed as the strength component. We propose some methods to overcome incomplete data problem and we use these methods to inference about the performance of a soccer player.
在本文中,我们通过分析一个不完整的数据集来研究一名足球运动员的表现。为实现这一目标,我们采用最大似然法将二元瑞利分布拟合到足球数据集上。通过这种方式,考虑到了此类研究中通常会出现的缺失数据和右删失问题。我们的目标是通过考虑压力和力量成分来推断一名足球运动员的表现。一场比赛中感兴趣球员的第一个进球被假定为压力成分,比赛的第二个进球被假定为力量成分。我们提出了一些方法来克服不完整数据问题,并使用这些方法来推断一名足球运动员的表现。