Abstract
В работе представлен приближенный алгоритм моделирования стационарного дискретного случайного процесса с одномерными и двумерными распределениями его последовательных компонент в виде смеси двух гауссовских распределений. Алгоритм основан на комбинации метода условных распределений и метода исключения. Приведен пример применения алгоритма для моделирования временных рядов максимальной за сутки температуры воздуха. 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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