메뉴 건너뛰기




Volumn 51, Issue 9, 2007, Pages 4438-4449

Bayesian nearest-neighbor analysis via record value statistics and nonhomogeneous spatial Poisson processes

Author keywords

Nearest neighbor approaches; Nonhomogeneous spatial Poisson processes; Record value statistics

Indexed keywords

BAYESIAN NETWORKS; COMPUTER SIMULATION; MARKOV PROCESSES; MONTE CARLO METHODS; POISSON DISTRIBUTION; STATISTICS;

EID: 34147144104     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csda.2006.07.001     Document Type: Article
Times cited : (9)

References (20)
  • 2
    • 0032375671 scopus 로고    scopus 로고
    • Nearest-neighbor clutter removal for estimating features in spatial point processes
    • Byers S., and Raftery A. Nearest-neighbor clutter removal for estimating features in spatial point processes. J. Amer. Statist. Assoc. 93 (1998) 577-584
    • (1998) J. Amer. Statist. Assoc. , vol.93 , pp. 577-584
    • Byers, S.1    Raftery, A.2
  • 7
    • 84937650085 scopus 로고
    • Learning curve approach to reliability monitoring
    • Duane J.T. Learning curve approach to reliability monitoring. IEEE Trans. Aerospace. AS-2 2 (1964) 563-566
    • (1964) IEEE Trans. Aerospace. , vol.AS-2 , Issue.2 , pp. 563-566
    • Duane, J.T.1
  • 8
    • 0000887162 scopus 로고
    • Choice of the smoothing parameter and efficiency of k-nearest neighbor classification
    • Enas G.G., and Choi S.C. Choice of the smoothing parameter and efficiency of k-nearest neighbor classification. Comput. Math. Appl. 12 (1986) 235-244
    • (1986) Comput. Math. Appl. , vol.12 , pp. 235-244
    • Enas, G.G.1    Choi, S.C.2
  • 9
    • 0032269108 scopus 로고    scopus 로고
    • How many clusters? Which clustering method? Answers via model-based cluster analysis
    • Fraley C., and Raftery A. How many clusters? Which clustering method? Answers via model-based cluster analysis. Comput. J. 41 (1998) 578-588
    • (1998) Comput. J. , vol.41 , pp. 578-588
    • Fraley, C.1    Raftery, A.2
  • 10
    • 0035998835 scopus 로고    scopus 로고
    • Model-based clustering, discriminant analysis, and density estimation
    • Fraley C., and Raftery A. Model-based clustering, discriminant analysis, and density estimation. J. Amer. Statist. Assoc. 97 (2002) 611-631
    • (2002) J. Amer. Statist. Assoc. , vol.97 , pp. 611-631
    • Fraley, C.1    Raftery, A.2
  • 11
    • 84972492387 scopus 로고
    • Inference from iterative simulation using multiple sequences
    • Gelman A.E., and Rubin D. Inference from iterative simulation using multiple sequences. Statist. Sci. 7 (1992) 457-472
    • (1992) Statist. Sci. , vol.7 , pp. 457-472
    • Gelman, A.E.1    Rubin, D.2
  • 12
    • 0347771319 scopus 로고    scopus 로고
    • Bayesian computation for nonhomogeneous Poisson processes in software reliability
    • Kuo L., and Yang T.Y. Bayesian computation for nonhomogeneous Poisson processes in software reliability. J. Amer. Statist. Assoc. 91 (1996) 763-773
    • (1996) J. Amer. Statist. Assoc. , vol.91 , pp. 763-773
    • Kuo, L.1    Yang, T.Y.2
  • 15
    • 0021208648 scopus 로고    scopus 로고
    • Musa, J.D., Okumoto, K., 1984. A logarithmic Poisson execution time model for software reliability measurement. In: Proceedings of the Seventh International Conference on Software Engineering. Orlando, pp. 230-238.
  • 17
    • 21744460005 scopus 로고    scopus 로고
    • Practical Bayesian density estimation using mixtures of normals
    • Roeder K., and Wasserman L. Practical Bayesian density estimation using mixtures of normals. J. Amer. Statist. Assoc. 92 (1997) 894-902
    • (1997) J. Amer. Statist. Assoc. , vol.92 , pp. 894-902
    • Roeder, K.1    Wasserman, L.2
  • 19
    • 0034206635 scopus 로고    scopus 로고
    • Finding curvilinear features in spatial point pattern: principal curve clustering with noise
    • Stanford D., and Raftery A. Finding curvilinear features in spatial point pattern: principal curve clustering with noise. IEEE Trans. Pattern Anal. Machine Intell. 22 (2000) 601-609
    • (2000) IEEE Trans. Pattern Anal. Machine Intell. , vol.22 , pp. 601-609
    • Stanford, D.1    Raftery, A.2
  • 20
    • 0041305132 scopus 로고    scopus 로고
    • Bayesian computation for the superposition of nonhomogeneous Poisson processes
    • Yang T.Y., and Kuo L. Bayesian computation for the superposition of nonhomogeneous Poisson processes. Canad. J. Statist. 27 (1999) 547-556
    • (1999) Canad. J. Statist. , vol.27 , pp. 547-556
    • Yang, T.Y.1    Kuo, L.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.