메뉴 건너뛰기




Volumn 137, Issue 10, 2007, Pages 3151-3163

Bayesian mixture modeling for spatial Poisson process intensities, with applications to extreme value analysis

Author keywords

Bayesian nonparametrics; Bivariate Beta density; Dirichlet process mixture model; Random intensity function; Spatial point patterns

Indexed keywords


EID: 34250186433     PISSN: 03783758     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jspi.2006.05.022     Document Type: Article
Times cited : (78)

References (48)
  • 1
    • 0000708831 scopus 로고
    • Mixtures of Dirichlet processes with applications to nonparametric problems
    • Antoniak C.E. Mixtures of Dirichlet processes with applications to nonparametric problems. Ann. Statist. 2 (1974) 1152-1174
    • (1974) Ann. Statist. , vol.2 , pp. 1152-1174
    • Antoniak, C.E.1
  • 2
    • 67649373558 scopus 로고    scopus 로고
    • Reference analysis
    • Dey D.K., and Rao C.R. (Eds), Elsevier, Amsterdam
    • Bernardo J.M. Reference analysis. In: Dey D.K., and Rao C.R. (Eds). Handbook of Statistics 25 (2005), Elsevier, Amsterdam 17-90
    • (2005) Handbook of Statistics 25 , pp. 17-90
    • Bernardo, J.M.1
  • 3
    • 0442293860 scopus 로고    scopus 로고
    • Spatial Poisson regression for health and exposure data measured at disparate resolutions
    • Best N.G., Ickstadt K., and Wolpert R.L. Spatial Poisson regression for health and exposure data measured at disparate resolutions. J. Amer. Statist. Assoc. 95 (2000) 1076-1088
    • (2000) J. Amer. Statist. Assoc. , vol.95 , pp. 1076-1088
    • Best, N.G.1    Ickstadt, K.2    Wolpert, R.L.3
  • 4
    • 0002617436 scopus 로고
    • Ferguson distributions via Pólya urn schemes
    • Blackwell D., and MacQueen J.B. Ferguson distributions via Pólya urn schemes. Ann. Statist. 1 (1973) 353-355
    • (1973) Ann. Statist. , vol.1 , pp. 353-355
    • Blackwell, D.1    MacQueen, J.B.2
  • 5
    • 23444461724 scopus 로고    scopus 로고
    • Bayesian analysis of extremes values by mixture modeling
    • Bottolo L., Consonni G., Dellaportas P., and Lijoi A. Bayesian analysis of extremes values by mixture modeling. Extremes 6 (2003) 25-47
    • (2003) Extremes , vol.6 , pp. 25-47
    • Bottolo, L.1    Consonni, G.2    Dellaportas, P.3    Lijoi, A.4
  • 6
    • 0033333437 scopus 로고    scopus 로고
    • Generalized gamma measures and shot-noise Cox processes
    • Brix A. Generalized gamma measures and shot-noise Cox processes. Adv. in Appl. Prob. 31 (1999) 929-953
    • (1999) Adv. in Appl. Prob. , vol.31 , pp. 929-953
    • Brix, A.1
  • 7
    • 0036339976 scopus 로고    scopus 로고
    • Spatio-temporal modelling of weeds by shot-noise G Cox processes
    • Brix A., and Chadœuf J. Spatio-temporal modelling of weeds by shot-noise G Cox processes. Biometrical J. 44 (2002) 83-99
    • (2002) Biometrical J. , vol.44 , pp. 83-99
    • Brix, A.1    Chadœuf, J.2
  • 8
    • 0035649290 scopus 로고    scopus 로고
    • Spatiotemporal prediction for log-Gaussian Cox processes
    • Brix A., and Diggle P.J. Spatiotemporal prediction for log-Gaussian Cox processes. J. Roy. Statist. Soc. Ser. B 63 (2001) 823-841
    • (2001) J. Roy. Statist. Soc. Ser. B , vol.63 , pp. 823-841
    • Brix, A.1    Diggle, P.J.2
  • 9
    • 0035457521 scopus 로고    scopus 로고
    • Space-time multi type log Gaussian Cox processes with a view to modelling weeds
    • Brix A., and Møller J. Space-time multi type log Gaussian Cox processes with a view to modelling weeds. Scand. J. Statist. 28 (2001) 471-488
    • (2001) Scand. J. Statist. , vol.28 , pp. 471-488
    • Brix, A.1    Møller, J.2
  • 10
    • 0000340832 scopus 로고
    • Bayes methods for a symmetric unimodal density and its mode
    • Brunner L.J., and Lo A.Y. Bayes methods for a symmetric unimodal density and its mode. Ann. Statist. 17 (1989) 1550-1566
    • (1989) Ann. Statist. , vol.17 , pp. 1550-1566
    • Brunner, L.J.1    Lo, A.Y.2
  • 15
    • 84950937290 scopus 로고
    • Bayesian density estimation and inference using mixtures
    • Escobar M., and West M. Bayesian density estimation and inference using mixtures. J. Amer. Statist. Assoc. 90 (1995) 577-588
    • (1995) J. Amer. Statist. Assoc. , vol.90 , pp. 577-588
    • Escobar, M.1    West, M.2
  • 16
    • 0012890141 scopus 로고    scopus 로고
    • Computing nonparametric hierarchical models
    • Dey D., Müller P., and Sinha D. (Eds), Springer, New York
    • Escobar M.D., and West M. Computing nonparametric hierarchical models. In: Dey D., Müller P., and Sinha D. (Eds). Practical Nonparametric and Semiparametric Bayesian Statistics (1998), Springer, New York 1-22
    • (1998) Practical Nonparametric and Semiparametric Bayesian Statistics , pp. 1-22
    • Escobar, M.D.1    West, M.2
  • 17
    • 0001120413 scopus 로고
    • A Bayesian analysis of some nonparametric problems
    • Ferguson T.S. A Bayesian analysis of some nonparametric problems. Ann. Statist. 1 (1973) 209-230
    • (1973) Ann. Statist. , vol.1 , pp. 209-230
    • Ferguson, T.S.1
  • 18
    • 0000780135 scopus 로고
    • Prior distributions on spaces of probability measures
    • Ferguson T.S. Prior distributions on spaces of probability measures. Ann. Statist. 2 (1974) 615-629
    • (1974) Ann. Statist. , vol.2 , pp. 615-629
    • Ferguson, T.S.1
  • 19
    • 0001787029 scopus 로고
    • Bayesian density estimation by mixtures of normal distributions
    • Rizvi M.H., Rustagi J.S., and Siegmund D. (Eds), Academic Press, New York
    • Ferguson T.S. Bayesian density estimation by mixtures of normal distributions. In: Rizvi M.H., Rustagi J.S., and Siegmund D. (Eds). Recent Advances in Statistics (1983), Academic Press, New York 287-302
    • (1983) Recent Advances in Statistics , pp. 287-302
    • Ferguson, T.S.1
  • 20
    • 0036017464 scopus 로고    scopus 로고
    • A computational approach for full nonparametric Bayesian inference under Dirichlet process mixture models
    • Gelfand A.E., and Kottas A. A computational approach for full nonparametric Bayesian inference under Dirichlet process mixture models. J. Comput. Graph. Statist. 11 (2002) 289-305
    • (2002) J. Comput. Graph. Statist. , vol.11 , pp. 289-305
    • Gelfand, A.E.1    Kottas, A.2
  • 21
    • 0032364029 scopus 로고    scopus 로고
    • Non-parametric Bayesian estimation of a spatial Poisson intensity
    • Heikkinen J., and Arjas E. Non-parametric Bayesian estimation of a spatial Poisson intensity. Scand. J. Statist. 25 (1998) 435-450
    • (1998) Scand. J. Statist. , vol.25 , pp. 435-450
    • Heikkinen, J.1    Arjas, E.2
  • 22
    • 0032887428 scopus 로고    scopus 로고
    • Modeling a Poisson forest in variable elevations: a nonparametric Bayesian approach
    • Heikkinen J., and Arjas E. Modeling a Poisson forest in variable elevations: a nonparametric Bayesian approach. Biometrics 55 (1999) 738-745
    • (1999) Biometrics , vol.55 , pp. 738-745
    • Heikkinen, J.1    Arjas, E.2
  • 23
    • 0001484415 scopus 로고    scopus 로고
    • Spatial regression for marked point processes
    • Bernardo J.M., Berger J.O., Dawid P., and Smith A.F.M. (Eds), Oxford University Press, Oxford
    • Ickstadt K., and Wolpert R.L. Spatial regression for marked point processes. In: Bernardo J.M., Berger J.O., Dawid P., and Smith A.F.M. (Eds). Bayesian Statistics 6 (1999), Oxford University Press, Oxford 323-341
    • (1999) Bayesian Statistics 6 , pp. 323-341
    • Ickstadt, K.1    Wolpert, R.L.2
  • 24
    • 2142830935 scopus 로고    scopus 로고
    • Computational methods for multiplicative intensity models using weighted gamma processes: proportional hazards, marked point processes, and panel count data
    • Ishwaran H., and James L.F. Computational methods for multiplicative intensity models using weighted gamma processes: proportional hazards, marked point processes, and panel count data. J. Amer. Statist. Assoc. 99 (2004) 175-190
    • (2004) J. Amer. Statist. Assoc. , vol.99 , pp. 175-190
    • Ishwaran, H.1    James, L.F.2
  • 26
    • 34250177916 scopus 로고    scopus 로고
    • Kottas, A., 2006a. Dirichlet process mixtures of Bets distributions, with applications to density and intensity estimation. Proceedings of the Workshop on Learning with Nanparametric Baysian Methods, 23rd International Conference on Machine Learning, June 2006, Pittsburgh, PA
  • 27
    • 28044451526 scopus 로고    scopus 로고
    • Nonparametric Bayesian survival analysis using mixtures of Weibull distributions
    • Kottas A. Nonparametric Bayesian survival analysis using mixtures of Weibull distributions. J. Stat. Plann. Inference 136 (2006) 578-596
    • (2006) J. Stat. Plann. Inference , vol.136 , pp. 578-596
    • Kottas, A.1
  • 29
    • 0002033276 scopus 로고
    • Computations of mixtures of Dirichlet processes
    • Kuo L. Computations of mixtures of Dirichlet processes. SIAM J. Sci. Statist. Comput. 7 (1986) 60-71
    • (1986) SIAM J. Sci. Statist. Comput. , vol.7 , pp. 60-71
    • Kuo, L.1
  • 30
    • 0030487956 scopus 로고    scopus 로고
    • Nonparametric hierarchical Bayes via sequential imputations
    • Liu J.S. Nonparametric hierarchical Bayes via sequential imputations. Ann. Statist. 24 (1996) 911-930
    • (1996) Ann. Statist. , vol.24 , pp. 911-930
    • Liu, J.S.1
  • 31
    • 0001876649 scopus 로고
    • On a class of Bayesian nonparametric estimates: I. Density estimates
    • Lo A.Y. On a class of Bayesian nonparametric estimates: I. Density estimates. Ann. Statist. 12 (1984) 351-357
    • (1984) Ann. Statist. , vol.12 , pp. 351-357
    • Lo, A.Y.1
  • 32
    • 1842545720 scopus 로고    scopus 로고
    • Computational methods for mixture of Dirichlet process models
    • Dey D., Müller P., and Sinha D. (Eds), Springer, New York
    • MacEachern S.N. Computational methods for mixture of Dirichlet process models. In: Dey D., Müller P., and Sinha D. (Eds). Practical Nonparametric and Semiparametric Bayesian Statistics (1998), Springer, New York 23-43
    • (1998) Practical Nonparametric and Semiparametric Bayesian Statistics , pp. 23-43
    • MacEachern, S.N.1
  • 33
    • 0038524824 scopus 로고    scopus 로고
    • Efficient MCMC schemes for robust model extensions using encompassing dirichlet process mixture models
    • Ruggeri F., and Rios-Insua D. (Eds), Springer, New York
    • MacEachern S.N., and Müller P. Efficient MCMC schemes for robust model extensions using encompassing dirichlet process mixture models. In: Ruggeri F., and Rios-Insua D. (Eds). Robust Bayesian Analysis (2000), Springer, New York 295-316
    • (2000) Robust Bayesian Analysis , pp. 295-316
    • MacEachern, S.N.1    Müller, P.2
  • 34
    • 0041878892 scopus 로고    scopus 로고
    • Shot noise Cox processes
    • Møller J. Shot noise Cox processes. Adv. in Appl. Prob. 35 (2003) 614-640
    • (2003) Adv. in Appl. Prob. , vol.35 , pp. 614-640
    • Møller, J.1
  • 35
    • 17744365970 scopus 로고    scopus 로고
    • Generalised shot noise Cox processes
    • Møller J., and Torrisi G.L. Generalised shot noise Cox processes. Adv. in Appl. Prob. 37 (2005) 48-74
    • (2005) Adv. in Appl. Prob. , vol.37 , pp. 48-74
    • Møller, J.1    Torrisi, G.L.2
  • 38
    • 4043092820 scopus 로고    scopus 로고
    • Nonparametric Bayesian data analysis
    • Müller P., and Quintana F.A. Nonparametric Bayesian data analysis. Statist. Sci. 19 (2004) 95-110
    • (2004) Statist. Sci. , vol.19 , pp. 95-110
    • Müller, P.1    Quintana, F.A.2
  • 39
    • 77950032550 scopus 로고    scopus 로고
    • Markov chain sampling methods for Dirichlet process mixture models
    • Neal R.M. Markov chain sampling methods for Dirichlet process mixture models. J. Comput. Graph. Statist. 9 (2000) 249-265
    • (2000) J. Comput. Graph. Statist. , vol.9 , pp. 249-265
    • Neal, R.M.1
  • 40
    • 0002276858 scopus 로고
    • The two-dimensional Poisson process and extremal processes
    • Pickands J. The two-dimensional Poisson process and extremal processes. J. Appl. Prob. 8 (1971) 745-756
    • (1971) J. Appl. Prob. , vol.8 , pp. 745-756
    • Pickands, J.1
  • 41
    • 0000135848 scopus 로고
    • Modelling spatial patterns (with discussion)
    • Ripley B.D. Modelling spatial patterns (with discussion). J. Roy. Statist. Soc. Ser. B 39 (1977) 172-212
    • (1977) J. Roy. Statist. Soc. Ser. B , vol.39 , pp. 172-212
    • Ripley, B.D.1
  • 42
    • 0000720609 scopus 로고
    • A constructive definition of Dirichlet priors
    • Sethuraman J. A constructive definition of Dirichlet priors. Statist. Sinica 4 (1994) 639-650
    • (1994) Statist. Sinica , vol.4 , pp. 639-650
    • Sethuraman, J.1
  • 43
    • 0000971673 scopus 로고
    • Convergence of Dirichlet measures and the interpretation of their parameter
    • Gupta S., and Berger J.O. (Eds), Springer, New York
    • Sethuraman J., and Tiwari R.C. Convergence of Dirichlet measures and the interpretation of their parameter. In: Gupta S., and Berger J.O. (Eds). Statistical Decision Theory and Related Topics III (1982), Springer, New York 305-315
    • (1982) Statistical Decision Theory and Related Topics III , pp. 305-315
    • Sethuraman, J.1    Tiwari, R.C.2
  • 44
    • 84972496066 scopus 로고
    • Extreme value analysis of environmental time series: an application to trend detection in ground-level ozone with discussion
    • Smith R.L. Extreme value analysis of environmental time series: an application to trend detection in ground-level ozone with discussion. Statist. Sci. 4 (1989) 367-377
    • (1989) Statist. Sci. , vol.4 , pp. 367-377
    • Smith, R.L.1
  • 45
    • 84883878588 scopus 로고    scopus 로고
    • Smith, R.L., 2003. Statistics of extremes, with applications in environment, insurance and finance. Extreme Values in Finance, Telecommunications and the Environment. In: Finkenstadt, B., Rootzen, H. (Eds.), Chapman & Hall/CRC Press, London, pp. 1-78 (Chapter 1).
  • 46
    • 0002316151 scopus 로고    scopus 로고
    • Extremes of mixed environmental processes
    • Bernardo J.M., Berger J.O., Dawid P., and Smith A.F.M. (Eds), Oxford University Press, Oxford
    • Walshaw D. Extremes of mixed environmental processes. In: Bernardo J.M., Berger J.O., Dawid P., and Smith A.F.M. (Eds). Bayesian Statistics 6 (1999), Oxford University Press, Oxford 849-858
    • (1999) Bayesian Statistics 6 , pp. 849-858
    • Walshaw, D.1
  • 47
    • 0001121317 scopus 로고    scopus 로고
    • Poisson/Gamma random field models for spatial statistics
    • Wolpert R.L., and Ickstadt K. Poisson/Gamma random field models for spatial statistics. Biometrika 85 (1998) 251-267
    • (1998) Biometrika , vol.85 , pp. 251-267
    • Wolpert, R.L.1    Ickstadt, K.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.