Statistical Science

Optimal scaling for various Metropolis-Hastings algorithms

Gareth O. Roberts and Jeffrey S. Rosenthal

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Abstract

We review and extend results related to optimal scaling of Metropolis–Hastings algorithms. We present various theoretical results for the high-dimensional limit. We also present simulation studies which confirm the theoretical results in finite-dimensional contexts.

Article information

Source
Statist. Sci., Volume 16, Number 4 (2001), 351-367.

Dates
First available in Project Euclid: 5 March 2002

Permanent link to this document
https://projecteuclid.org/euclid.ss/1015346320

Digital Object Identifier
doi:10.1214/ss/1015346320

Mathematical Reviews number (MathSciNet)
MR1888450

Zentralblatt MATH identifier
1127.65305

Subjects
Primary: Adaptive triangulations AIC density estimation extended linear models finite elements free knot splines GCV linear splines multivariate splines regression

Citation

Roberts, Gareth O.; Rosenthal, Jeffrey S. Optimal scaling for various Metropolis-Hastings algorithms. Statist. Sci. 16 (2001), no. 4, 351--367. doi:10.1214/ss/1015346320. https://projecteuclid.org/euclid.ss/1015346320


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References

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