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Adaptive Rejection Sampling from Log‐Concave Density Functions

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  • P. Wild
  • W. R. Gilks

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  • P. Wild & W. R. Gilks, 1993. "Adaptive Rejection Sampling from Log‐Concave Density Functions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 42(4), pages 701-709, December.
    • Handle: RePEc:bla:jorssc:v:42:y:1993:i:4:p:701-709
    DOI: 10.2307/2986186
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    Cited by:

    1. Radu Tunaru, 2015. "Model Risk in Financial Markets:From Financial Engineering to Risk Management," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 9524, August.
    2. Carmen Broto & Esther Ruiz, 2004. "Estimation methods for stochastic volatility models: a survey," Journal of Economic Surveys, Wiley Blackwell, vol. 18(5), pages 613-649, December.
    3. Geweke, John, 1996. "Monte carlo simulation and numerical integration," Handbook of Computational Economics, in: H. M. Amman & D. A. Kendrick & J. Rust (ed.), Handbook of Computational Economics, edition 1, volume 1, chapter 15, pages 731-800, Elsevier.
    4. Jeffrey Rouder & Jordan Province & Richard Morey & Pablo Gomez & Andrew Heathcote, 2015. "The Lognormal Race: A Cognitive-Process Model of Choice and Latency with Desirable Psychometric Properties," Psychometrika, Springer;The Psychometric Society, vol. 80(2), pages 491-513, June.
    5. Font, Begoña, 1998. "Modelización de series temporales financieras. Una recopilación," DES - Documentos de Trabajo. Estadística y Econometría. DS 3664, Universidad Carlos III de Madrid. Departamento de Estadística.
    6. Alston, C.L. & Mengersen, K.L., 2010. "Allowing for the effect of data binning in a Bayesian Normal mixture model," Computational Statistics & Data Analysis, Elsevier, vol. 54(4), pages 916-923, April.

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