Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
On Applying Optimal Design of Experiments when Functional Observations Occur Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Likelihood-Free Extensions for Bayesian Sequentially Designed Experiments

Authors : Markus Hainy, Christopher C. Drovandi, James M. McGree

Published in: mODa 11 - Advances in Model-Oriented Design and Analysis

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

When considering a Bayesian sequential design framework, sequential Monte Carlo (SMC) algorithms are a natural approach. However, these algorithms require the likelihood function to be evaluated. Therefore, they cannot be applied in cases where the likelihood is not available or is intractable. To overcome this limitation, we propose likelihood-free extensions of the standard SMC algorithm. We also investigate a specific simulation-based approximation of the likelihood known as the synthetic likelihood. The algorithms are applied and tested on a well-studied sequential design problem for estimating a non-linear function of linear regression parameters.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter Regular Fractions of Factorial Arrays
next chapter A Confidence Interval Approach in Self-Designing Clinical Trials
Literature
1.
Blum, M.G.B.: Approximate Bayesian computation: a nonparametric perspective. J. Am. Stat. Assoc. 105 (491), 1178–1187 (2010). doi:10.1198/jasa.2010.tm09448CrossRefMATHMathSciNet
2.
Drovandi, C.C., McGree, J.M., Pettitt, A.N.: Sequential Monte Carlo for Bayesian sequentially designed experiments for discrete data. Comput. Stat. Data Anal. 57, 320–335 (2013). doi:10.1016/j.csda.2012.05.014CrossRefMathSciNet
3.
Drovandi, C.C., Pettitt, A.N.: Estimation of parameters for macroparasite population evolution using approximate Bayesian computation. Biometrics 67 (1), 225–233 (2011). doi:10.1111/j.1541-0420.2010.01410.xCrossRefMATHMathSciNet
4.
Ford, I., Silvey, S.D.: A sequentially constructed design for estimating a nonlinear parametric function. Biometrika 67, 381–388 (1980)CrossRefMATHMathSciNet
5.
Hainy, M., Müller, W.G., Wagner, H.: Likelihood-free simulation-based optimal design with an application to spatial extremes. Stoch. Environ. Res. Risk A. Stoch. Environ. Res. Risk A. 30 (2), 481–492 (2016). doi:10.1007/s00477-015-1067-8CrossRef
6.
Liu, J.S.: Monte Carlo Strategies in Scientific Computing. Springer, New York (2001)MATH
7.
Sisson, S.A., Fan, Y.: Likelihood-free Markov chain Monte Carlo. In: Brooks, S.P., Gelman, A., Jones, G., Meng, X.L. (eds.) Handbook of Markov Chain Monte Carlo, Handbooks of Modern Statistical Methods, pp. 319–341. Chapman & Hall/CRC Press, Boca Raton (2011)
8.
Wood, S.N.: Statistical inference for noisy nonlinear ecological dynamic systems. Nature 466, 1102–1104 (2010). doi:10.1038/nature09319CrossRef
Metadata
Title
Likelihood-Free Extensions for Bayesian Sequentially Designed Experiments
Authors
Markus Hainy
Christopher C. Drovandi
James M. McGree
Copyright Year
2016
Book
mODa 11 - Advances in Model-Oriented Design and Analysis

Print ISBN: 978-3-319-31264-4

Electronic ISBN: 978-3-319-31266-8

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-31266-8_18

Premium Partner

    Image Credits