Modeling spatial batting ability using a known covariance matrix
Modeling spatial batting ability using a known covariance matrix
复制标题
使用已知的协方差矩阵对空间击球能力进行建模
DOI：
10.1515/jqas-2014-0089
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发表时间：
2015
影响因子：
0.8
通讯作者：
Sylvan Dana
中科院分区：
文献类型：
--
作者：
Cross Jared;Sylvan Dana
在棒球运动中，热图用于可视化击球手在好球区及其周围区域的能力，它在棒球解说和球探报告中起着重要作用。我们将这些热图背后的随机过程表示为具有各向同性协方差的空间高斯场。空间插值（克里金法）依赖于已知协方差函数的假设，但在实际中，协方差的参数通常是根据数据估算的。我们基于已知协方差函数进行的模拟研究有助于理解和解释该过程的空间依赖性，并使我们能够制作出更完善的热图。
In baseball, heat maps, which visualize a batter’s ability across regions in and around the strike zone, play an important role in baseball commentary and scouting reports. We represent the stochastic process underlying these heat maps as a spatial Gaussian field with isotropic covariance. Spatial interpolation (kriging) relies on the assumption of a known covariance function, but in reality the parameters of the covariance are typically estimated from the data. Our simulation study, based on a known covariance function, helps to understand and explain the spatial dependence of the process and allows us to produce improved heat maps.