Standard

Deterministic noises that can be statistically distinguished from the random ones. / Davydov, Youri; Zitikis, Ričardas.

в: Statistical Inference for Stochastic Processes, Том 10, № 2, 07.2007, стр. 165-179.

Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование

Harvard

Davydov, Y & Zitikis, R 2007, 'Deterministic noises that can be statistically distinguished from the random ones', Statistical Inference for Stochastic Processes, Том. 10, № 2, стр. 165-179. https://doi.org/10.1007/s11203-006-0001-6

APA

Davydov, Y., & Zitikis, R. (2007). Deterministic noises that can be statistically distinguished from the random ones. Statistical Inference for Stochastic Processes, 10(2), 165-179. https://doi.org/10.1007/s11203-006-0001-6

Vancouver

Davydov Y, Zitikis R. Deterministic noises that can be statistically distinguished from the random ones. Statistical Inference for Stochastic Processes. 2007 Июль;10(2):165-179. https://doi.org/10.1007/s11203-006-0001-6

Author

Davydov, Youri ; Zitikis, Ričardas. / Deterministic noises that can be statistically distinguished from the random ones. в: Statistical Inference for Stochastic Processes. 2007 ; Том 10, № 2. стр. 165-179.

BibTeX

@article{35be223555634f7594318aa67907f153,
title = "Deterministic noises that can be statistically distinguished from the random ones",
abstract = "Empirical measures generated by random sequences with deterministic and random noises have same asymptotic distributions provided that the noises have same asymptotic distributions (cf., Davydov and Zitikis, 2004, Proc. Am. Math. Soc. 132, 1203-1210). This phenomenon has raised an intriguing question about the possibility of distinguishing the two types of noises based only on their asymptotic distributions. In the present paper we suggest an answer to the question by considering asymptotic variances, and distributions, of the appropriately centered and normalized empirical measures and processes.",
keywords = "Asymptotic normality, Deterministic noise, Empirical measures, Empirical processes, Random noise, Weak convergence, White noise",
author = "Youri Davydov and Ri{\v c}ardas Zitikis",
note = "Funding Information: Youri Davydov is supported by a grant from the French Academy of Sciences. Ricˇardas Zitikis is supported by an NSERC of Canada research grant at the University of Western Ontario. Copyright: Copyright 2006 Elsevier B.V., All rights reserved.",
year = "2007",
month = jul,
doi = "10.1007/s11203-006-0001-6",
language = "English",
volume = "10",
pages = "165--179",
journal = "Statistical Inference for Stochastic Processes",
issn = "1387-0874",
publisher = "Springer Nature",
number = "2",

}

RIS

TY - JOUR

T1 - Deterministic noises that can be statistically distinguished from the random ones

AU - Davydov, Youri

AU - Zitikis, Ričardas

N1 - Funding Information: Youri Davydov is supported by a grant from the French Academy of Sciences. Ricˇardas Zitikis is supported by an NSERC of Canada research grant at the University of Western Ontario. Copyright: Copyright 2006 Elsevier B.V., All rights reserved.

PY - 2007/7

Y1 - 2007/7

N2 - Empirical measures generated by random sequences with deterministic and random noises have same asymptotic distributions provided that the noises have same asymptotic distributions (cf., Davydov and Zitikis, 2004, Proc. Am. Math. Soc. 132, 1203-1210). This phenomenon has raised an intriguing question about the possibility of distinguishing the two types of noises based only on their asymptotic distributions. In the present paper we suggest an answer to the question by considering asymptotic variances, and distributions, of the appropriately centered and normalized empirical measures and processes.

AB - Empirical measures generated by random sequences with deterministic and random noises have same asymptotic distributions provided that the noises have same asymptotic distributions (cf., Davydov and Zitikis, 2004, Proc. Am. Math. Soc. 132, 1203-1210). This phenomenon has raised an intriguing question about the possibility of distinguishing the two types of noises based only on their asymptotic distributions. In the present paper we suggest an answer to the question by considering asymptotic variances, and distributions, of the appropriately centered and normalized empirical measures and processes.

KW - Asymptotic normality

KW - Deterministic noise

KW - Empirical measures

KW - Empirical processes

KW - Random noise

KW - Weak convergence

KW - White noise

UR - http://www.scopus.com/inward/record.url?scp=33750162140&partnerID=8YFLogxK

U2 - 10.1007/s11203-006-0001-6

DO - 10.1007/s11203-006-0001-6

M3 - Article

AN - SCOPUS:33750162140

VL - 10

SP - 165

EP - 179

JO - Statistical Inference for Stochastic Processes

JF - Statistical Inference for Stochastic Processes

SN - 1387-0874

IS - 2

ER -

ID: 73459726