L-Moments Method: Introducing Novel Approach of Mixture Parameters Estimation and Its Implementation in Python Library Pysatl-Mpest

Standard

L-Moments Method: Introducing Novel Approach of Mixture Parameters Estimation and Its Implementation in Python Library Pysatl-Mpest. / Гориховский, Вячеслав Игоревич ; Тотьмянин, Данил Денисович.

2025 37th Conference of Open Innovations Association (FRUCT). Institute of Electrical and Electronics Engineers Inc., 2025. p. 317-322 (Conference of Open Innovation Association, FRUCT).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Гориховский, ВИ & Тотьмянин, ДД 2025, L-Moments Method: Introducing Novel Approach of Mixture Parameters Estimation and Its Implementation in Python Library Pysatl-Mpest. in 2025 37th Conference of Open Innovations Association (FRUCT). Conference of Open Innovation Association, FRUCT, Institute of Electrical and Electronics Engineers Inc., pp. 317-322, The 37th FRUCT conference, Kufstein, Austria, 14/05/25. https://doi.org/10.23919/fruct65909.2025.11008126

BibTeX

@inproceedings{511db5ecfd1e4b9bb1922004bffa213f,

title = "L-Moments Method: Introducing Novel Approach of Mixture Parameters Estimation and Its Implementation in Python Library Pysatl-Mpest",

abstract = "This paper addresses the problem of estimating the parameters of a mixture of distributions. One of the most popular ways to solve this problem is the Expectation Maximization algorithm. We introduce a novel alternative method for estimating the parameters of a mixture of distributions, based on numerical characteristics of distribution known as L-moments. Experimental results demonstrate significant speedup and comparable accuracy compared to classical methods.",

author = "Гориховский, {Вячеслав Игоревич} and Тотьмянин, {Данил Денисович}",

year = "2025",

month = may,

day = "14",

doi = "10.23919/fruct65909.2025.11008126",

language = "English",

isbn = "9789526524634",

series = "Conference of Open Innovation Association, FRUCT",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "317--322",

booktitle = "2025 37th Conference of Open Innovations Association (FRUCT)",

address = "United States",

note = "null ; Conference date: 14-05-2025 Through 16-05-2025",

url = "https://www.fruct.org/conferences/37/registration/",

}

RIS

TY - GEN

T1 - L-Moments Method: Introducing Novel Approach of Mixture Parameters Estimation and Its Implementation in Python Library Pysatl-Mpest

AU - Гориховский, Вячеслав Игоревич

AU - Тотьмянин, Данил Денисович

PY - 2025/5/14

Y1 - 2025/5/14

N2 - This paper addresses the problem of estimating the parameters of a mixture of distributions. One of the most popular ways to solve this problem is the Expectation Maximization algorithm. We introduce a novel alternative method for estimating the parameters of a mixture of distributions, based on numerical characteristics of distribution known as L-moments. Experimental results demonstrate significant speedup and comparable accuracy compared to classical methods.

AB - This paper addresses the problem of estimating the parameters of a mixture of distributions. One of the most popular ways to solve this problem is the Expectation Maximization algorithm. We introduce a novel alternative method for estimating the parameters of a mixture of distributions, based on numerical characteristics of distribution known as L-moments. Experimental results demonstrate significant speedup and comparable accuracy compared to classical methods.

UR - https://www.mendeley.com/catalogue/f2d5874e-b201-3155-af77-b201b36351a2/

U2 - 10.23919/fruct65909.2025.11008126

DO - 10.23919/fruct65909.2025.11008126

M3 - Conference contribution

SN - 9789526524634

T3 - Conference of Open Innovation Association, FRUCT

SP - 317

EP - 322

BT - 2025 37th Conference of Open Innovations Association (FRUCT)

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 14 May 2025 through 16 May 2025

ER -

ID: 137266961