A Statistical Study of two Diffusion Processes on Torus and Their Applications

Authors
M Rahimi
M Golalizazdedh
10.29252/mmr.1.1.37
Abstract
Diffusion Processes such as Brownian motions and Ornstein-Uhlenbeck processes are the classes of stochastic processes that have been investigated by researchers in various disciplines including biological sciences. It is usually assumed that the outcomes of these processes are laid on the Euclidean spaces. However, some data in physical, chemical and biological phenomena indicate that they cannot be considered as the observations in Euclidean spaces due to the various features such as the periodicity of the data. Hence, we cannot analyze them using the common mathematical methods available in Euclidean spaces. In addition, studying and analyzing them using common linear statistics are not possible. One of these typical data is the dihedral angles that are utilized in identifying, modeling and predicting the proteins backbones. Because these angles are representatives of points on the surface of torus, it seems that proper statistical modeling of diffusion processes on the torus could be of a great help for the research activities on dynamic molecular simulations in predicting the proteins backbones. In this article, using the Riemannian distance on the torus, the stochastic differential equations to describe the Brownian motions and Ornstein-Uhlenbeck processes on this geometrical object were derived. Then, in order to evaluate the proposed models, the statistical simulations were performed using the equilibrium distributions of aforementioned stochastic processes. Moreover, the link between the gained results with the available concepts in the non-linear statistics were highlighted.
Keywords
Diffusion Processes
Stochastic Differential Equations
Equilibrium Distributions
Non-linear Statistics
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