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Title: Nonparametric Method of Least Squares: Accounting for Seasonality

Abstract

We consider the problem of restoring a nonparametric dependence described by the sum of linear trend and seasonal component, i.e., a periodic function with the known period. We obtain the asymptotic distribution of the parameter estimates and the trend component. We find the mathematical expectation of the residual sum of squares. We also develop the methods of estimation of the seasonal component and construction of the interval forecast.

Authors:
 [1]
  1. Bauman Moscow State Technical University and Moscow Physics-Technical Institute (Russian Federation)
Publication Date:
OSTI Identifier:
22771595
Resource Type:
Journal Article
Journal Name:
Journal of Mathematical Sciences
Additional Journal Information:
Journal Volume: 228; Journal Issue: 5; Conference: International seminar on stability problems for stochastic models, Zakopane (Poland), 31 May - 5 Jun 2009; Other Information: Copyright (c) 2018 Springer Science+Business Media, LLC, part of Springer Nature; http://www.springer-ny.com; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 1072-3374
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICAL METHODS AND COMPUTING; ASYMPTOTIC SOLUTIONS; FUNCTIONS; LEAST SQUARE FIT; PERIODICITY

Citation Formats

Orlov, A. I., E-mail: prof-orlov@mail.ru. Nonparametric Method of Least Squares: Accounting for Seasonality. United States: N. p., 2018. Web. doi:10.1007/S10958-017-3639-2.
Orlov, A. I., E-mail: prof-orlov@mail.ru. Nonparametric Method of Least Squares: Accounting for Seasonality. United States. doi:10.1007/S10958-017-3639-2.
Orlov, A. I., E-mail: prof-orlov@mail.ru. Thu . "Nonparametric Method of Least Squares: Accounting for Seasonality". United States. doi:10.1007/S10958-017-3639-2.
@article{osti_22771595,
title = {Nonparametric Method of Least Squares: Accounting for Seasonality},
author = {Orlov, A. I., E-mail: prof-orlov@mail.ru},
abstractNote = {We consider the problem of restoring a nonparametric dependence described by the sum of linear trend and seasonal component, i.e., a periodic function with the known period. We obtain the asymptotic distribution of the parameter estimates and the trend component. We find the mathematical expectation of the residual sum of squares. We also develop the methods of estimation of the seasonal component and construction of the interval forecast.},
doi = {10.1007/S10958-017-3639-2},
journal = {Journal of Mathematical Sciences},
issn = {1072-3374},
number = 5,
volume = 228,
place = {United States},
year = {2018},
month = {2}
}