Optimally adaptive Bayesian spectral density estimation for stationary and nonstationary processes-Reference-Cited by-同舟云学术

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Optimally adaptive Bayesian spectral density estimation for stationary and nonstationary processes

Published:2022-05-29 Issue:3 Volume:32 Page:
ISSN:0960-3174
Container-title:Statistics and Computing
language:en
Short-container-title:Stat Comput

Author:

James Nick,Menzies Max^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Computational Theory and Mathematics,Statistics, Probability and Uncertainty,Statistics and Probability,Theoretical Computer Science

Link

https://link.springer.com/content/pdf/10.1007/s11222-022-10103-4.pdf

Reference45 articles.

1. Adak, S.: Time-dependent spectral analysis of nonstationary time series. J. Am. Stat. Assoc. 93(444), 1488–1501 (1998). https://doi.org/10.1080/01621459.1998.10473808

2. Barbe, K., Pintelon, R., Schoukens, J.: Welch method revisited: nonparametric power spectrum estimation via circular overlap. IEEE Trans. Signal Process. 58(2), 553–565 (2010). https://doi.org/10.1109/tsp.2009.2031724

3. Box, G.E.P., Jenkins, G.M., Reinsel, G.C., Ljung, G.M.: Time Series Analysis: Forecasting and Control. Wiley, Hoboken (2015)

4. Brockwell, P.J., Davis, R.A.: Time Series: Theory and Methods. Springer, New York (1991). https://doi.org/10.1007/978-1-4419-0320-4

5. Carter, C.K., Kohn, R.: Semiparametric Bayesian inference for time series with mixed spectra. J. R. Stat. Soc.: Ser. B (Stat. Methodol.) 59(1), 255–268 (1997). https://doi.org/10.1111/1467-9868.00067

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