NAOC Open IR
Estimating red noise in quasi-periodic signals with MCMC-based Bayesian
Liang, Bo1,2,3; Meng, Yao1,3; Feng, Song1,2; Yang, Yunfei1,3
2020-02-21
Source PublicationASTROPHYSICS AND SPACE SCIENCE
ISSN0004-640X
Volume365Issue:2Pages:6
AbstractMulti-parameter Bayesian inferences based on Markov chain Monte Carlo (MCMC) samples have been widely used to estimate red noise in solar period-periodic signals. To MCMC, proper priors and sufficient iterations are prerequisites ensuring the accuracy of red noise estimation. We used MCMC-based Bayesian inferences to estimate 100 groups of red noise synthesized randomly for evaluating its accuracy. At the same time, the Brooks-Gelman algorithm was employed to precisely diagnose the convergence of the Markov chains generated by MCMC. The root-mean-square error of parameter inferences to the synthetic data is only 1.14. Furthermore, we applied the algorithm to analyze the oscillation modes in a sunspot and a flare. A 70 s period is detected in the sunspot umbra in addition to 3- and 5-minute periods, and a 40 s period is detected in the flare. The results prove that estimating red noise with MCMC-based Bayesian has more high accuracy in the case of proper priors and convergence. We also find that the number of iterations increases dramatically to achieve convergence as the number of parameters grows. Therefore, we strongly recommend that when estimating red noise with MCMC-based Bayesian, different initial values must be selected to ensure that the entire posterior distribution is covered.
KeywordMethod data analysis Method statistical Sun oscillations Sun sunspots Sun flares
Funding OrganizationNational Natural Science Foundation of China ; National Natural Science Foundation of China ; Key Applied Basic Research Program of Yunnan Province ; Key Applied Basic Research Program of Yunnan Province ; Key Laboratory of Solar Activity of National Astronomical Observatory of China ; Key Laboratory of Solar Activity of National Astronomical Observatory of China ; NSFC ; NSFC ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Key Applied Basic Research Program of Yunnan Province ; Key Applied Basic Research Program of Yunnan Province ; Key Laboratory of Solar Activity of National Astronomical Observatory of China ; Key Laboratory of Solar Activity of National Astronomical Observatory of China ; NSFC ; NSFC ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Key Applied Basic Research Program of Yunnan Province ; Key Applied Basic Research Program of Yunnan Province ; Key Laboratory of Solar Activity of National Astronomical Observatory of China ; Key Laboratory of Solar Activity of National Astronomical Observatory of China ; NSFC ; NSFC ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Key Applied Basic Research Program of Yunnan Province ; Key Applied Basic Research Program of Yunnan Province ; Key Laboratory of Solar Activity of National Astronomical Observatory of China ; Key Laboratory of Solar Activity of National Astronomical Observatory of China ; NSFC ; NSFC
DOI10.1007/s10509-020-3744-4
Language英语
Funding ProjectNational Natural Science Foundation of China[U1931107] ; Key Applied Basic Research Program of Yunnan Province[2018FA035] ; Key Laboratory of Solar Activity of National Astronomical Observatory of China[KLSA202007] ; NSFC[11763004]
Funding OrganizationNational Natural Science Foundation of China ; National Natural Science Foundation of China ; Key Applied Basic Research Program of Yunnan Province ; Key Applied Basic Research Program of Yunnan Province ; Key Laboratory of Solar Activity of National Astronomical Observatory of China ; Key Laboratory of Solar Activity of National Astronomical Observatory of China ; NSFC ; NSFC ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Key Applied Basic Research Program of Yunnan Province ; Key Applied Basic Research Program of Yunnan Province ; Key Laboratory of Solar Activity of National Astronomical Observatory of China ; Key Laboratory of Solar Activity of National Astronomical Observatory of China ; NSFC ; NSFC ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Key Applied Basic Research Program of Yunnan Province ; Key Applied Basic Research Program of Yunnan Province ; Key Laboratory of Solar Activity of National Astronomical Observatory of China ; Key Laboratory of Solar Activity of National Astronomical Observatory of China ; NSFC ; NSFC ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Key Applied Basic Research Program of Yunnan Province ; Key Applied Basic Research Program of Yunnan Province ; Key Laboratory of Solar Activity of National Astronomical Observatory of China ; Key Laboratory of Solar Activity of National Astronomical Observatory of China ; NSFC ; NSFC
WOS Research AreaAstronomy & Astrophysics
WOS SubjectAstronomy & Astrophysics
WOS IDWOS:000518026200001
PublisherSPRINGER
Citation statistics
Document Type期刊论文
Identifierhttp://ir.bao.ac.cn/handle/114a11/54520
Collection中国科学院国家天文台
Corresponding AuthorFeng, Song
Affiliation1.Kunming Univ Sci & Technol, Fac Informat Engn & Automat, Kunming 650500, Yunnan, Peoples R China
2.Natl Astron Observ, CAS Key Lab Solar Act, Beijing 100012, Peoples R China
3.Yunnan Key Lab Comp Technol Applicat, Kunming 650500, Yunnan, Peoples R China
Recommended Citation
GB/T 7714
Liang, Bo,Meng, Yao,Feng, Song,et al. Estimating red noise in quasi-periodic signals with MCMC-based Bayesian[J]. ASTROPHYSICS AND SPACE SCIENCE,2020,365(2):6.
APA Liang, Bo,Meng, Yao,Feng, Song,&Yang, Yunfei.(2020).Estimating red noise in quasi-periodic signals with MCMC-based Bayesian.ASTROPHYSICS AND SPACE SCIENCE,365(2),6.
MLA Liang, Bo,et al."Estimating red noise in quasi-periodic signals with MCMC-based Bayesian".ASTROPHYSICS AND SPACE SCIENCE 365.2(2020):6.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Liang, Bo]'s Articles
[Meng, Yao]'s Articles
[Feng, Song]'s Articles
Baidu academic
Similar articles in Baidu academic
[Liang, Bo]'s Articles
[Meng, Yao]'s Articles
[Feng, Song]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Liang, Bo]'s Articles
[Meng, Yao]'s Articles
[Feng, Song]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.