Abstract
In this paper, we present three algorithms for simulation of intervals of stationary vector and scalar sequences with partial distributions of their subsequences of fixed length in the form of a mixture of Gaussian distributions. The first algorithm is based on superposition of two Gaussian vector processes and the second and third ones use the method of conditional distributions and the method of superpositions to simulate the mixtures and to select realizations for approximate construction of conditional realizations. Some properties of these algorithms are presented.
Funding statement: The research was carried out within the framework of the State Assignment ICM & MG SB RAS FWNM–2022–0002.
References
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- Simulation algorithms for stationary sequences with distributions in the form of a mixture of Gaussian distributions
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Articles in the same Issue
- Frontmatter
- Simulation algorithms for stationary sequences with distributions in the form of a mixture of Gaussian distributions
- Monte Carlo simulation of polarized lidar returns for atmospheric clouds sensing
- Stochastic simulation of exciton transport in semiconductor heterostructures
- Semi-Lagrangian approximations of the transfer operator in divergent form
- Numerical modelling of large elasto-plastic multi-material deformations on Eulerian grids