V. A. Ogorodnikov, M. S. Akenteva, N. A. Kargapolova
{"title":"模拟具有高斯分布混合物形式连续成分双变量分布的静态离散随机过程的近似算法","authors":"V. A. Ogorodnikov, M. S. Akenteva, N. A. Kargapolova","doi":"10.1134/s199542392402006x","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>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.</p>","PeriodicalId":43697,"journal":{"name":"Numerical Analysis and Applications","volume":"49 1","pages":""},"PeriodicalIF":0.4000,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Approximate Algorithm for Simulating Stationary Discrete Random Processes with Bivariate Distributions of Their Consecutive Components in the Form of Mixtures of Gaussian Distributions\",\"authors\":\"V. A. Ogorodnikov, M. S. Akenteva, N. A. Kargapolova\",\"doi\":\"10.1134/s199542392402006x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<h3 data-test=\\\"abstract-sub-heading\\\">Abstract</h3><p>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.</p>\",\"PeriodicalId\":43697,\"journal\":{\"name\":\"Numerical Analysis and Applications\",\"volume\":\"49 1\",\"pages\":\"\"},\"PeriodicalIF\":0.4000,\"publicationDate\":\"2024-05-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Numerical Analysis and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1134/s199542392402006x\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"MATHEMATICS, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Numerical Analysis and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1134/s199542392402006x","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
An Approximate Algorithm for Simulating Stationary Discrete Random Processes with Bivariate Distributions of Their Consecutive Components in the Form of Mixtures of Gaussian Distributions
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.
期刊介绍:
Numerical Analysis and Applications is the translation of Russian periodical Sibirskii Zhurnal Vychislitel’noi Matematiki (Siberian Journal of Numerical Mathematics) published by the Siberian Branch of the Russian Academy of Sciences Publishing House since 1998.
The aim of this journal is to demonstrate, in concentrated form, to the Russian and International Mathematical Community the latest and most important investigations of Siberian numerical mathematicians in various scientific and engineering fields.
The journal deals with the following topics: Theory and practice of computational methods, mathematical physics, and other applied fields; Mathematical models of elasticity theory, hydrodynamics, gas dynamics, and geophysics; Parallelizing of algorithms; Models and methods of bioinformatics.