Bayesian Mixture Modelling in Geochronology via Markov Chain Monte Carlo (original) (raw)
References
Andersen, T., 2005, Detrital zircons as tracers of sedimentary provenance: Limiting conditions from statistics and numerical simulation: Chem. Geol., v. 216, p. 249–270. Google Scholar
Besag, J., 1986, On the statistical analysis of dirty pictures: J. R. Stat. Soc. B, v. 48, no. 3, p. 259–279. Google Scholar
Brandon, M. T., 1992, Decomposition of fission-track age distributions: Am. J. Sci. v. 292, p. 535–564. Article Google Scholar
Brandon, M. T., 1996, Probability density plot for fission-track grain-age samples: Rad. Meas., v. 26, no. 5, p. 663–676. Article Google Scholar
Brooks, S. P., Friel, N., and King, R., 2003, Classical model selection via simulated annealing: J. R. Stat. Soc. B, v. 65, no. 2, p. 503–520. ArticleMathSciNet Google Scholar
Carter, A., and Bristow, C. S., 2003, Linking hinterland evolution and continental basin sedimentation by using detrital zircon thermochronology: A study of the Khorat Plateau basin, Eastern Thailand: Basin Res., v. 15, no. 2, p. 271–285. Google Scholar
Carter, A., and Moss, S. J., 1999, Combined detrital-zircon fission track and U-Pb dating: A new approach to understanding hinterland evolution: Geology, v. 27, no. 3, p. 235–238. Google Scholar
Galbraith, R. F., 1998, Graphical display of estimates having differing standard errors: Technometrics, v. 30, p. 271–281. Article Google Scholar
Galbraith, R. F., 1998, The trouble with “probability density” plots of fission track ages: Radiat. Meas., v. 29, no. 2., p. 125–131. Article Google Scholar
Galbraith, R. F., and Green, P. F., 1990, Estimating the component ages in a finite mixture: Nucl. Track Radiat. Meas., v. 1, no. 3, p. 197–206. Article Google Scholar
Green, P. J., 1995, Reversible jump Markov chain Monte Carlo computation and Bayesian model determination: Biometrika, v. 82, no. 4, p. 711–732. Article Google Scholar
Green, P. J., and Mira, A., 2001, Delayed rejection in reversible jump Metropolis–Hastings: Biometrika, v. 88, no. 4, p. 1035–1053. MathSciNet Google Scholar
Ireland, T. R., Flöttmann, T., Fanning, C. M., Gibson, G. M., and Preiss, W. V., 1998, Development of the early Paleozoic Pacific margin of Gondwana from detrital-zircon ages across the delamerian orogen: Geology, v. 26, no. 3, p. 243–246. Article Google Scholar
Ireland, T. R., and Williams, I. S. 2003, Considerations in zircon geochronology by SIMS, in Hanchar, J. M., and Hoskin, P. W. O., eds., Zircon: Reviews in mineralogy and geochemistry: Mineralogical Society of America, Washington, DC, vol. 53, p. 215–241.
Jasra, A., Holmes, C. C., and Stephens, D. A., 2005, Markov chain Monte Carlo methods and the label switching problem in Bayesian mixture modelling: Stat. Sci., v. 20, no. 1, p. 50–67. Article Google Scholar
Jennison, C., 1997, Discussion of on Bayesian analysis of mixtures with an unknown number of components: J. R. Stat. Soc. B., v. 59, no. 4, p. 778–779. Google Scholar
Jones, M. C., and Faddy, M. J., 2003, A skew extension of the _t_-distribution, with applications: J. R. Stat. Soc. B., v. 65, no. 1, p. 159–174. Article Google Scholar
Lindley, D. V., 1957, A statistical paradox: Biometrika, v. 44, no. 1, p. 187–192. Article Google Scholar
McLachlan, G. J., and Peel, D., 2000, Finite mixture models: Wiley, Chichester, UK, 419 p. Google Scholar
Richardson, S., and Green, P. J., 1997, On Bayesian analysis of mixture models with an unknown number of components: J. R. Stat. Soc. B, v. 59, no. 4, p. 731–792. Article Google Scholar
Richardson, S., Leblond, L., Jaussent, I., and Green, P. J., 2002, Mixture models in measurement error problems, with reference to epidemiological studies: J. R. Stat. Soc. A, v. 165, no. 3, p. 549–566. Article Google Scholar
Robert, C. P., 2001, The Bayesian choice: From decision-theoretic foundations to computational implementation, 2nd ed.: Springer, New York, 604 p. Google Scholar
Robert, C. P., and Casella, G., 2004, Monte Carlo statistical methods, 2nd ed.: Springer, New York, 645 p. Google Scholar
Sambridge, M. S., and Compston, W., 1994, Mixture modelling of multi-component data sets with application to ion-probe zircon ages: Earth Planet. Sci. Lett., v. 128, no. 3, p. 373–390. Article Google Scholar
Sircombe, K. N., 2004, AGEDISPLAY: An EXCEL workbook to evaluate and display univariate geochronological data using binned frequency histograms and probability density distributions: Comp. Geosci., v. 30, p. 21–31. Google Scholar
Stephens, M., 2000, Dealing with label switching in mixture models: J. R. Stat. Soc. B, v. 62, no. 4, p. 795–809. Article Google Scholar
Stern, R. A., and Amelin, Y., 2003, Assessment of errors in SIMS zircon U-Pb geochronology using a natural zircon standard and NIST SRM 610 glass: Chem. Geol., v. 197, no. 1, p. 111–142. Article Google Scholar
Vermeesch, P., 2004. How many grains are needed for a provenance study?: Earth. Planet. Sci. Lett., v. 224. p. 441–451. Article Google Scholar