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  Improving Bayesian analysis for LISA Pathfinder using an efficient Markov Chain Monte Carlo method

Ferraioli, L., Porter, E. K., Armano, M., Audley, H., Congedo, G., Diepholz, I., et al. (2014). Improving Bayesian analysis for LISA Pathfinder using an efficient Markov Chain Monte Carlo method. Experimental Astronomy, 37(1), 109-125. doi:10.1007/s10686-014-9372-7.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-002A-805B-7 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-002A-805C-5
Genre: Journal Article

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ExAstro37_109.pdf (Any fulltext), 2MB
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 Creators:
Ferraioli, Luigi, Author
Porter, Edward K., Author
Armano, Michele, Author
Audley, Heather1, Author              
Congedo, Giuseppe, Author
Diepholz, Ingo1, Author              
Gibert, Ferran, Author
Hewitson, Martin2, Author              
Hueller, Mauro, Author
Karnesis, Nikolaos, Author
Korsakova, Natalia1, Author
Nofrarias, Miquel, Author
Plagnol, Eric, Author
Vitale, Stefano, Author
Affiliations:
1Laser Interferometry & Gravitational Wave Astronomy, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society, escidoc:24010              
2Observational Relativity and Cosmology, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society, escidoc:24011              

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 Dates: 2014
 Publication Status: Published in print
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 Rev. Method: -
 Identifiers: DOI: 10.1007/s10686-014-9372-7
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Title: Experimental Astronomy
  Other : Exp. Astron.
Source Genre: Journal
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Publ. Info: Dordrecht : Springer
Pages: - Volume / Issue: 37 (1) Sequence Number: - Start / End Page: 109 - 125 Identifier: ISSN: 0922-6435
CoNE: http://pubman.mpdl.mpg.de/cone/journals/resource/954925382054