Standard

The model of time series as a piecewise-stationary process. / Prasolov, A. V.; Иванов, Никита.

Proceedings of the 3rd International Conference on Applications in Information Technology, ICAIT 2018. ed. / Klyuev Vitaly; Pyshkin Evgeny; Natalia Bogach. Association for Computing Machinery, 2018. p. 150-153.

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

Harvard

Prasolov, AV & Иванов, Н 2018, The model of time series as a piecewise-stationary process. in K Vitaly, P Evgeny & N Bogach (eds), Proceedings of the 3rd International Conference on Applications in Information Technology, ICAIT 2018. Association for Computing Machinery, pp. 150-153, 3rd International Conference on Applications in Information Technology, ICAIT 2018, Aizu-Wakamatsu, Japan, 1/11/18. https://doi.org/10.1145/3274856.3274888

APA

Prasolov, A. V., & Иванов, Н. (2018). The model of time series as a piecewise-stationary process. In K. Vitaly, P. Evgeny, & N. Bogach (Eds.), Proceedings of the 3rd International Conference on Applications in Information Technology, ICAIT 2018 (pp. 150-153). Association for Computing Machinery. https://doi.org/10.1145/3274856.3274888

Vancouver

Prasolov AV, Иванов Н. The model of time series as a piecewise-stationary process. In Vitaly K, Evgeny P, Bogach N, editors, Proceedings of the 3rd International Conference on Applications in Information Technology, ICAIT 2018. Association for Computing Machinery. 2018. p. 150-153 https://doi.org/10.1145/3274856.3274888

Author

Prasolov, A. V. ; Иванов, Никита. / The model of time series as a piecewise-stationary process. Proceedings of the 3rd International Conference on Applications in Information Technology, ICAIT 2018. editor / Klyuev Vitaly ; Pyshkin Evgeny ; Natalia Bogach. Association for Computing Machinery, 2018. pp. 150-153

BibTeX

@inproceedings{ce0abeadcb96463d91fb0ce509a3c49a,
title = "The model of time series as a piecewise-stationary process",
abstract = "This work is devoted to determining the space-time area that contains a time-series trend to address mathematical expectations. A time series trajectory represents the realization of a stochastic process in discrete time; thus, its approximation is random and cannot be considered a trend valuation. We offer to interpret an arbitrary time series as a trajectory of a piecewise-stationary process. This allows for us to describe an algorithm that constructs the area where the trend is located.",
keywords = "Piecewise-stationary process, Time series, Trend",
author = "Prasolov, {A. V.} and Никита Иванов",
year = "2018",
month = nov,
day = "1",
doi = "10.1145/3274856.3274888",
language = "English",
pages = "150--153",
editor = "Klyuev Vitaly and Pyshkin Evgeny and Natalia Bogach",
booktitle = "Proceedings of the 3rd International Conference on Applications in Information Technology, ICAIT 2018",
publisher = "Association for Computing Machinery",
address = "United States",
note = "3rd International Conference on Applications in Information Technology, ICAIT 2018 ; Conference date: 01-11-2018 Through 03-11-2018",

}

RIS

TY - GEN

T1 - The model of time series as a piecewise-stationary process

AU - Prasolov, A. V.

AU - Иванов, Никита

PY - 2018/11/1

Y1 - 2018/11/1

N2 - This work is devoted to determining the space-time area that contains a time-series trend to address mathematical expectations. A time series trajectory represents the realization of a stochastic process in discrete time; thus, its approximation is random and cannot be considered a trend valuation. We offer to interpret an arbitrary time series as a trajectory of a piecewise-stationary process. This allows for us to describe an algorithm that constructs the area where the trend is located.

AB - This work is devoted to determining the space-time area that contains a time-series trend to address mathematical expectations. A time series trajectory represents the realization of a stochastic process in discrete time; thus, its approximation is random and cannot be considered a trend valuation. We offer to interpret an arbitrary time series as a trajectory of a piecewise-stationary process. This allows for us to describe an algorithm that constructs the area where the trend is located.

KW - Piecewise-stationary process

KW - Time series

KW - Trend

UR - http://www.scopus.com/inward/record.url?scp=85058614633&partnerID=8YFLogxK

U2 - 10.1145/3274856.3274888

DO - 10.1145/3274856.3274888

M3 - Conference contribution

AN - SCOPUS:85058614633

SP - 150

EP - 153

BT - Proceedings of the 3rd International Conference on Applications in Information Technology, ICAIT 2018

A2 - Vitaly, Klyuev

A2 - Evgeny, Pyshkin

A2 - Bogach, Natalia

PB - Association for Computing Machinery

T2 - 3rd International Conference on Applications in Information Technology, ICAIT 2018

Y2 - 1 November 2018 through 3 November 2018

ER -

ID: 37031274