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Methodology for inference on the Markov modulated Poisson process and theory for optimal scaling of the random walk Metropolis

Research output: Thesis › Doctoral Thesis

Unpublished

Standard

Methodology for inference on the Markov modulated Poisson process and theory for optimal scaling of the random walk Metropolis. / Sherlock, Chris.
Lancaster University, 2006. 245 p.

Research output: Thesis › Doctoral Thesis

Harvard

Sherlock, C 2006, 'Methodology for inference on the Markov modulated Poisson process and theory for optimal scaling of the random walk Metropolis', PhD, Lancaster University.

APA

Sherlock, C. (2006). Methodology for inference on the Markov modulated Poisson process and theory for optimal scaling of the random walk Metropolis. [Doctoral Thesis, Lancaster University]. Lancaster University.

Vancouver

Sherlock C. Methodology for inference on the Markov modulated Poisson process and theory for optimal scaling of the random walk Metropolis. Lancaster University, 2006. 245 p.

Author

Sherlock, Chris. / Methodology for inference on the Markov modulated Poisson process and theory for optimal scaling of the random walk Metropolis. Lancaster University, 2006. 245 p.

Bibtex

@phdthesis{a3bb43c4eae44e52aa6e6e22236c8c7f,
title = "Methodology for inference on the Markov modulated Poisson process and theory for optimal scaling of the random walk Metropolis",
keywords = "random walk Metropolis optimal scaling Markov modulated Poisson process",
author = "Chris Sherlock",
year = "2006",
language = "English",
publisher = "Lancaster University",
school = "Lancaster University",

}

RIS

TY - BOOK

T1 - Methodology for inference on the Markov modulated Poisson process and theory for optimal scaling of the random walk Metropolis

AU - Sherlock, Chris

PY - 2006

Y1 - 2006

KW - random walk Metropolis optimal scaling Markov modulated Poisson process

M3 - Doctoral Thesis

PB - Lancaster University

ER -