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Hopcroft, Peter O., Gallagher, Kerry, Pain, Chris C. (2007) Inference of past climate from borehole temperature data using Bayesian Reversible Jump Markov chain Monte Carlo. Geophysical Journal International, 171 (3) 1430-1439 doi:10.1111/j.1365-246x.2007.03596.x

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Reference TypeJournal (article/letter/editorial)
TitleInference of past climate from borehole temperature data using Bayesian Reversible Jump Markov chain Monte Carlo
JournalGeophysical Journal International
AuthorsHopcroft, Peter O.Author
Gallagher, KerryAuthor
Pain, Chris C.Author
Year2007 (October 4)Volume171
Issue3
PublisherOxford University Press (OUP)
DOIdoi:10.1111/j.1365-246x.2007.03596.xSearch in ResearchGate
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Mindat Ref. ID884507Long-form Identifiermindat:1:5:884507:2
GUID0
Full ReferenceHopcroft, Peter O., Gallagher, Kerry, Pain, Chris C. (2007) Inference of past climate from borehole temperature data using Bayesian Reversible Jump Markov chain Monte Carlo. Geophysical Journal International, 171 (3) 1430-1439 doi:10.1111/j.1365-246x.2007.03596.x
Plain TextHopcroft, Peter O., Gallagher, Kerry, Pain, Chris C. (2007) Inference of past climate from borehole temperature data using Bayesian Reversible Jump Markov chain Monte Carlo. Geophysical Journal International, 171 (3) 1430-1439 doi:10.1111/j.1365-246x.2007.03596.x
In(2007, October) Geophysical Journal International Vol. 171 (3) Oxford University Press (OUP)

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Hopcroft, Peter O., Gallagher, Kerry, Pain, Christopher C. (2009) A Bayesian partition modelling approach to resolve spatial variability in climate records from borehole temperature inversion. Geophysical Journal International, 178 (2) 651-666 doi:10.1111/j.1365-246x.2009.04192.x
Luo, Xiaolin (2010) Constraining the shape of a gravity anomalous body using reversible jump Markov chain Monte Carlo. Geophysical Journal International, 180 (3) 1067-1079 doi:10.1111/j.1365-246x.2009.04479.x
Hopcroft, Peter O., Gallagher, Kerry, Pain, Christopher C., Fang, Fangxin (2009) Three-dimensional simulation and inversion of borehole temperatures for reconstructing past climate in complex settings. Journal of Geophysical Research, 114. doi:10.1029/2008jf001165
Minsley, Burke J. (2011) A trans-dimensional Bayesian Markov chain Monte Carlo algorithm for model assessment using frequency-domain electromagnetic data. Geophysical Journal International, 187 (1) 252-272 doi:10.1111/j.1365-246x.2011.05165.x
Malinverno, A. (2002) Parsimonious Bayesian Markov chain Monte Carlo inversion in a nonlinear geophysical problem. Geophysical Journal International, 151 (3) 675-688 doi:10.1046/j.1365-246x.2002.01847.x
Robert, C. P., Ryden, T., Titterington, D. M. (2000) Bayesian inference in hidden Markov models through the reversible jump Markov chain Monte Carlo method. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 62 (1). 57-75 doi:10.1111/1467-9868.00219
Tesson, J., Benedetti, L. (2019) Seismic history from in situ 36Cl cosmogenic nuclide data on limestone fault scarps using Bayesian reversible jump Markov chain Monte Carlo. Quaternary Geochronology, 52. 1-20 doi:10.1016/j.quageo.2019.02.004
Deng, Tianqi, Ambía, Joaquín, Torres‐Verdín, Carlos (2023) Efficient Bayesian inversion of borehole geophysical measurements with a gradient‐based Markov chain Monte Carlo method. Geophysical Prospecting, 71 (3) 471-494 doi:10.1111/1365-2478.13311
(2007) Forthcoming papers. Geophysical Journal International, 170 (3) 1439 doi:10.1111/j.1365-246x.2007.03574.x
Bebbington, Mark S. (2007) Identifying volcanic regimes using Hidden Markov Models. Geophysical Journal International, 171 (2) 921-942 doi:10.1111/j.1365-246x.2007.03559.x
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