An approximate algorithm for simulating stationary discrete random processes with bivariate distributions of their consecutive components in the form of mixtures of Gaussian distributions
V.A. Ogorodnikov1,2, M.S. Akenteva1, N.A. Kargapolova1,2
1Institute of Computational Mathematics and Mathematical Geophysics of Siberian Branch of Russian Academy of Sciences, Novosibirsk, Russia
2Novosibirsk State University, Novosibirsk, Russia
Keywords: stochastic simulation, bivariate distribution, mixture of Gaussian distributions, maximum daily temperature
Abstract
The paper presents an approximate algorithm for modeling a stationary discrete random process with marginal and bivariate distributions of its consecutive components in the form of a mixture of two Gaussian distributions. The algorithm is based on a combination of the conditional distribution method and the rejection method. An example of application of the proposed algorithm for simulating time series of daily maximum air temperatures is given.
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