论文标题
用于统计建模的灵活的准孔子分布
A Flexible Quasi-Copula Distribution for Statistical Modeling
论文作者
论文摘要
Copulas，广义估计方程和广义线性混合模型促进了非正常响应相关的分组数据的分析。不幸的是，在这三个框架中，参数估计仍然具有挑战性。基于TONDA的先前工作，我们得出了一类新的概率密度函数，这些函数允许对矩，边际和条件分布的明确计算以及最大似然估计所需的分数和观察信息。我们还说明了新分布如何灵活地对非高斯分布后的纵向数据进行建模。最后，我们对英国二分的二分法收缩期和舒张压和舒张压和体重指数数据进行了三变量的全基因组关联分析，从而展示了新分布的建模实力和计算可扩展性。
Copulas, generalized estimating equations, and generalized linear mixed models promote the analysis of grouped data where non-normal responses are correlated. Unfortunately, parameter estimation remains challenging in these three frameworks. Based on prior work of Tonda, we derive a new class of probability density functions that allow explicit calculation of moments, marginal and conditional distributions, and the score and observed information needed in maximum likelihood estimation. We also illustrate how the new distribution flexibly models longitudinal data following a non-Gaussian distribution. Finally, we conduct a tri-variate genome-wide association analysis on dichotomized systolic and diastolic blood pressure and body mass index data from the UK-Biobank, showcasing the modeling prowess and computational scalability of the new distribution.
