Standard

Time Series Analysis of Unequally Spaced Data: Intercomparison between estimators of Power Spectrum. / Vityazev, V.V.

Astronomical Data Analysis Software and Systems VI . Том 125 Astronomical Society of the Pacific, 1997. стр. 166-169.

Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборнике материалов конференции

Harvard

Vityazev, VV 1997, Time Series Analysis of Unequally Spaced Data: Intercomparison between estimators of Power Spectrum. в Astronomical Data Analysis Software and Systems VI . Том. 125, Astronomical Society of the Pacific, стр. 166-169, Astronomical Data Analysis Software and Systems VI , Virginia, 22/09/96. <http://www.aspbooks.org/a/volumes/article_details?paper_id=14484>

APA

Vityazev, V. V. (1997). Time Series Analysis of Unequally Spaced Data: Intercomparison between estimators of Power Spectrum. в Astronomical Data Analysis Software and Systems VI (Том 125, стр. 166-169). Astronomical Society of the Pacific. http://www.aspbooks.org/a/volumes/article_details?paper_id=14484

Vancouver

Vityazev VV. Time Series Analysis of Unequally Spaced Data: Intercomparison between estimators of Power Spectrum. в Astronomical Data Analysis Software and Systems VI . Том 125. Astronomical Society of the Pacific. 1997. стр. 166-169

Author

Vityazev, V.V. / Time Series Analysis of Unequally Spaced Data: Intercomparison between estimators of Power Spectrum. Astronomical Data Analysis Software and Systems VI . Том 125 Astronomical Society of the Pacific, 1997. стр. 166-169

BibTeX

@inproceedings{f222857d3d844464ab9770c493e5e757,
title = "Time Series Analysis of Unequally Spaced Data: Intercomparison between estimators of Power Spectrum",
abstract = "It is shown that the likeness of the periodogram and the LS-spectrum (both estimators of the power spectrum are widely used in the spectral analysis of time series), depends on the properties of the spectral window W(omega ) corresponding to the distribution of time points. The main results are: a) all the estimators evaluated at frequency omega are identical if W(2omega )=0; b) the Schuster periodogram differs from the LS-spectra at the frequencies omega =hat ω_k/2, where hat ω_k are the frequencies at which the spectral window has large side peaks due to irregular distribution of time points. Two examples for situations typical in astronomy illustrate these conclusions.",
author = "V.V. Vityazev",
year = "1997",
language = "English",
volume = "125",
pages = "166--169",
booktitle = "Astronomical Data Analysis Software and Systems VI",
publisher = "Astronomical Society of the Pacific",
address = "United States",
note = "Astronomical Data Analysis Software and Systems VI ; Conference date: 22-09-1996 Through 25-09-1996",

}

RIS

TY - GEN

T1 - Time Series Analysis of Unequally Spaced Data: Intercomparison between estimators of Power Spectrum

AU - Vityazev, V.V.

PY - 1997

Y1 - 1997

N2 - It is shown that the likeness of the periodogram and the LS-spectrum (both estimators of the power spectrum are widely used in the spectral analysis of time series), depends on the properties of the spectral window W(omega ) corresponding to the distribution of time points. The main results are: a) all the estimators evaluated at frequency omega are identical if W(2omega )=0; b) the Schuster periodogram differs from the LS-spectra at the frequencies omega =hat ω_k/2, where hat ω_k are the frequencies at which the spectral window has large side peaks due to irregular distribution of time points. Two examples for situations typical in astronomy illustrate these conclusions.

AB - It is shown that the likeness of the periodogram and the LS-spectrum (both estimators of the power spectrum are widely used in the spectral analysis of time series), depends on the properties of the spectral window W(omega ) corresponding to the distribution of time points. The main results are: a) all the estimators evaluated at frequency omega are identical if W(2omega )=0; b) the Schuster periodogram differs from the LS-spectra at the frequencies omega =hat ω_k/2, where hat ω_k are the frequencies at which the spectral window has large side peaks due to irregular distribution of time points. Two examples for situations typical in astronomy illustrate these conclusions.

M3 - Conference contribution

VL - 125

SP - 166

EP - 169

BT - Astronomical Data Analysis Software and Systems VI

PB - Astronomical Society of the Pacific

T2 - Astronomical Data Analysis Software and Systems VI

Y2 - 22 September 1996 through 25 September 1996

ER -

ID: 4736856