Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
Versatile algorithm for economical simulating one-dimensional random variables with continuous, monotone densities over bounded, closed intervals. / Bryzgalov, Viktor; Seitmuratov, Ubaydulla; Voytishek, Anton.
в: Monte Carlo Methods and Applications, Том 32, № 1, 20.02.2026, стр. 69-79.Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
}
TY - JOUR
T1 - Versatile algorithm for economical simulating one-dimensional random variables with continuous, monotone densities over bounded, closed intervals
AU - Bryzgalov, Viktor
AU - Seitmuratov, Ubaydulla
AU - Voytishek, Anton
N1 - Bryzgalov, V. Versatile algorithm for economical simulating one-dimensional random variables with continuous, monotone densities over bounded, closed intervals / V. Bryzgalov, U. Seitmuratov, A. Voytishek // Monte Carlo Methods and Applications. – 2026. – Vol. 32, No. 1. – P. 69-79. – DOI 10.1515/mcma-2026-2003. – EDN RKTDET. The research was carried out under state contract with ICMMG SB RAS FWNM–2025–0002
PY - 2026/2/20
Y1 - 2026/2/20
N2 - This paper introduces the versatile double-sided rejection method for simulating one-dimensional random variables. Effective for variables with continuous monotone densities over bounded intervals, the method uses piecewise constant majorants and minorants. The new technique for probability equalization is developed, involving constraction of special non-uniform meshes. The custom-built computer system PrEMA (Probability Equalization Modelling Algorithms) – available at https://prema.andronix1.ru – is presented. PrEMA includes the “distributed-random” library with C and Rust code implementations of the method. It also features a dialog system for comparing the costs of the double-sided algorithm to the inverse distribution function method and the modified ziggurat algorithm. The impact of different standard pseudo-random number generators on the system’s performance is examined.
AB - This paper introduces the versatile double-sided rejection method for simulating one-dimensional random variables. Effective for variables with continuous monotone densities over bounded intervals, the method uses piecewise constant majorants and minorants. The new technique for probability equalization is developed, involving constraction of special non-uniform meshes. The custom-built computer system PrEMA (Probability Equalization Modelling Algorithms) – available at https://prema.andronix1.ru – is presented. PrEMA includes the “distributed-random” library with C and Rust code implementations of the method. It also features a dialog system for comparing the costs of the double-sided algorithm to the inverse distribution function method and the modified ziggurat algorithm. The impact of different standard pseudo-random number generators on the system’s performance is examined.
KW - Computer modelling (sampling, generating) of sample values of one-dimensional random variables
KW - computationally expensive formulas of the inverse distribution function method
KW - custom-built dialog computer system PrEMA
KW - economical double-sided rejection algorithm
KW - piecewise constant majorant and minorant
KW - probability equalization
KW - standard pseudo-random number generators
KW - Компьютерное моделирование (выборка, генерация) выборочных значений одномерных случайных величин
KW - вычислительно затратные формулы метода обратной функции распределения
KW - экономичный двусторонний алгоритм отбора (метод «отбраковки»)
KW - кусочно-постоянные мажоранта и миноранта
KW - выравнивание вероятностей
KW - специализированная диалоговая компьютерная система PrEMA
KW - стандартные генераторы псевдослучайных чисел
UR - https://www.mendeley.com/catalogue/42eb67b9-19eb-3607-8099-0455ba515a4f/
UR - https://www.scopus.com/pages/publications/105030663007
UR - https://elibrary.ru/item.asp?id=90939731
U2 - 10.1515/mcma-2026-2003
DO - 10.1515/mcma-2026-2003
M3 - Article
VL - 32
SP - 69
EP - 79
JO - Monte Carlo Methods and Applications
JF - Monte Carlo Methods and Applications
SN - 0929-9629
IS - 1
ER -
ID: 85086915