Favretti Marco
Dipartimento di Matematica Tullio Levi-Civita, Università degli Studi di Padova, 35131 Padova, Italy.
Entropy (Basel). 2022 May 14;24(5):698. doi: 10.3390/e24050698.
In this paper we introduce a class of statistical models consisting of exponential families depending on additional parameters, called external parameters. The main source for these statistical models resides in the Maximum Entropy framework where we have thermal parameters, corresponding to the natural parameters of an exponential family, and mechanical parameters, here called external parameters. In the first part we we study the geometry of these models introducing a fibration of parameter space over external parameters. In the second part we investigate a class of evolution problems driven by a Fokker-Planck equation whose stationary distribution is an exponential family with external parameters. We discuss applications of these statistical models to thermodynamic length and isentropic evolution of thermodynamic systems and to a problem in the dynamic of quantitative traits in genetics.
在本文中,我们介绍了一类统计模型,这类模型由依赖于额外参数(称为外部参数)的指数族组成。这些统计模型的主要来源在于最大熵框架,在该框架中我们有热参数,它对应于指数族的自然参数,以及机械参数,在这里称为外部参数。在第一部分,我们研究这些模型的几何结构,引入参数空间关于外部参数的纤维化。在第二部分,我们研究一类由福克 - 普朗克方程驱动的演化问题,其平稳分布是具有外部参数的指数族。我们讨论这些统计模型在热力学长度和热力学系统的等熵演化以及遗传学中数量性状动态问题上的应用。