English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
 
 
DownloadE-Mail
  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.

Item is

Basic

show hide
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

Files

show Files
hide Files
:
ExAstro37_109.pdf (Any fulltext), 2MB
Name:
ExAstro37_109.pdf
Description:
-
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show

Creators

show
hide
 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, ou_24010              
2Observational Relativity and Cosmology, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society, ou_24011              

Content

show

Details

show
hide
Language(s):
 Dates: 2014
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.1007/s10686-014-9372-7
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Experimental Astronomy
  Other : Exp. Astron.
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Dordrecht : Springer
Pages: - Volume / Issue: 37 (1) Sequence Number: - Start / End Page: 109 - 125 Identifier: ISSN: 0922-6435
CoNE: /journals/resource/954925382054