메뉴 건너뛰기




Volumn 3, Issue , 2009, Pages 1-17

Statistical models: Conventional, penalized and hierarchical likelihood

Author keywords

Bayes estimators; Cross validation; H likelihood; Incomplete data; Kullback leibler risk; Likelihood; Penalized likelihood; Sieves; Statistical models

Indexed keywords


EID: 77951093768     PISSN: None     EISSN: 19357516     Source Type: Journal    
DOI: 10.1214/08-SS039     Document Type: Article
Times cited : (10)

References (45)
  • 1
    • 0000501656 scopus 로고
    • Information theory and an extension of maximumlikelihood principle
    • Akademia Kiado
    • Akaike, H. (1973). Information theory and an extension of maximumlikelihood principle. Second International Symposium on Information Theory, Akademia Kiado. 267-281.
    • (1973) Second International Symposium on Information Theory , pp. 267-281
    • Akaike, H.1
  • 2
    • 0011241944 scopus 로고
    • Approximate Inference in Generalized Linear Mixed Models
    • Breslow, N.E. and Clayton, D.G. (1993). Approximate Inference in Generalized Linear Mixed Models. J. Amer. Statist. Assoc. 88, 9-25.
    • (1993) J. Amer. Statist. Assoc. , vol.88 , pp. 9-25
    • Breslow, N.E.1    Clayton, D.G.2
  • 3
    • 8744307994 scopus 로고    scopus 로고
    • Multimodel inference: Understanding AIC and BIC in model selection
    • Burnham, K.P. and Anderson, D.R. (2004). Multimodel inference: understanding AIC and BIC in model selection. Sociol. Methods Res. 33, 261-304.
    • (2004) Sociol. Methods Res. , vol.33 , pp. 261-304
    • Burnham, K.P.1    Anderson, D.R.2
  • 6
    • 34547288139 scopus 로고    scopus 로고
    • Likelihood for generally coarsened observations from multi-state or counting process models
    • Commenges, D. and Gégout-Petit, A. (2007). Likelihood for generally coarsened observations from multi-state or counting process models. Scand. J. Statist. 34, 432-450.
    • (2007) Scand. J. Statist. , vol.34 , pp. 432-450
    • Commenges, D.1    Gégout-Petit, A.2
  • 7
    • 33847411839 scopus 로고    scopus 로고
    • Choice between semi-parametric estimators of Markov and non-Markov multi-statemodels from generally coarsened observations
    • Commenges, D., Joly, P., Gégout-Petit, A. and Liquet, B. (2007). Choice between semi-parametric estimators of Markov and non-Markov multi-statemodels from generally coarsened observations. Scand. J. Statist. 34, 33-52.
    • (2007) Scand. J. Statist. , vol.34 , pp. 33-52
    • Commenges, D.1    Joly, P.2    Gégout-Petit, A.3    Liquet, B.4
  • 9
    • 70349969933 scopus 로고    scopus 로고
    • Estimating a difference of Kullback-Leibler risks using a normalized difference of AIC
    • Commenges, D., Sayyareh, A., Letenneur, L., Guedj, J. and Bar- Hen, A. (2008). Estimating a difference of Kullback-Leibler risks using a normalized difference of AIC. Ann. Appl. Statist. 2, 1123-1142.
    • (2008) Ann. Appl. Statist. , vol.2 , pp. 1123-1142
    • Commenges, D.1    Sayyareh, A.2    Letenneur, L.3    Guedj, J.4    Bar-Hen, A.5
  • 10
    • 5444232913 scopus 로고    scopus 로고
    • Nonlinear models for repeated measurement data: An overview and update
    • Davidian, M. and Giltinan, D.M. (2003). Nonlinear models for repeated measurement data: an overview and update, J. Agric. Biol. Environ. Statist. 8, 387-419.
    • (2003) J. Agric. Biol. Environ. Statist. , vol.8 , pp. 387-419
    • Davidian, M.1    Giltinan, D.M.2
  • 12
    • 0033243858 scopus 로고    scopus 로고
    • Convergence of a Stochastic Approximation Version of the EM Algorithm
    • Delyon B., Lavielle, M. and Moulines, E. (1999). Convergence of a Stochastic Approximation Version of the EM Algorithm. Ann. Statist. 27, 94-128.
    • (1999) Ann. Statist. , vol.27 , pp. 94-128
    • Delyon, B.1    Lavielle, M.2    Moulines, E.3
  • 13
    • 0033233732 scopus 로고    scopus 로고
    • Optimal convergence rates for Good's nonparametric likelihood density estimator
    • Eggermont, P. and Lariccia, V. (1999). Optimal convergence rates for Good's nonparametric likelihood density estimator. Ann. Statist. 27, 1600-1615.
    • (1999) Ann. Statist. , vol.27 , pp. 1600-1615
    • Eggermont, P.1    Lariccia, V.2
  • 15
    • 0002468162 scopus 로고
    • Maximum likelihood estimation for continuous-time stochastic processes
    • Feigin, P.D. (1976). Maximum likelihood estimation for continuous-time stochastic processes. Adv. Appl. Prob. 8, 712-736.
    • (1976) Adv. Appl. Prob. , vol.8 , pp. 712-736
    • Feigin, P.D.1
  • 16
    • 0001735517 scopus 로고
    • On the Mathematical Foundations of Theoretical Statistics
    • Fisher, R.A. (1922). On the Mathematical Foundations of Theoretical Statistics. Phil. Trans. Roy. Soc. A 222, 309-368.
    • (1922) Phil. Trans. Roy. Soc. A , vol.222 , pp. 309-368
    • Fisher, R.A.1
  • 17
    • 0000451036 scopus 로고
    • Nonparametric roughness penalty for probability densities
    • Good, I.J. and Gaskin, R.A. (1971). Nonparametric roughness penalty for probability densities. Biometrika 58, 255-277.
    • (1971) Biometrika , vol.58 , pp. 255-277
    • Good, I.J.1    Gaskin, R.A.2
  • 18
    • 0036975172 scopus 로고    scopus 로고
    • Penalized likelihood regression.: General formulation and efficient approximation
    • Gu, C. and Kim, Y. J. (2002). Penalized likelihood regression.: general formulation and efficient approximation. Can. J. Stat. 30, 619-628.
    • (2002) Can. J. Stat. , vol.30 , pp. 619-628
    • Gu, C.1    Kim, Y.J.2
  • 19
    • 35648934561 scopus 로고    scopus 로고
    • Maximum likelihood estimation in dynamical models of HIV
    • Guedj, J., Thiébaut, R. and Commenges, D. (2007). Maximum likelihood estimation in dynamical models of HIV. Biometrics 63, 1198-1206.
    • (2007) Biometrics , vol.63 , pp. 1198-1206
    • Guedj, J.1    Thiébaut, R.2    Commenges, D.3
  • 20
    • 0000993483 scopus 로고
    • Ignorability and coarse data
    • Heitjan, D.F. and Rubin, D.B. (1991). Ignorability and coarse data. Ann. Statist. 19, 2244-2253.
    • (1991) Ann. Statist. , vol.19 , pp. 2244-2253
    • Heitjan, D.F.1    Rubin, D.B.2
  • 23
    • 0000531113 scopus 로고
    • Multivariate point processes: Predictable projection; Radon-Nikodym derivative, representation of martingales
    • Jacod, J. (1975). Multivariate point processes: predictable projection; Radon-Nikodym derivative, representation of martingales. Z. Wahrsch. Verw. Geb. 31, 235-253.
    • (1975) Z. Wahrsch. Verw. Geb. , vol.31 , pp. 235-253
    • Jacod, J.1
  • 25
    • 0032887315 scopus 로고    scopus 로고
    • A penalized likelihood approach for a progressive three-state model with censored and truncated data: Application to AIDS
    • Joly, P. and Commenges, D. (1999). A penalized likelihood approach for a progressive three-state model with censored and truncated data: Application to AIDS. Biometrics 55, 887-890.
    • (1999) Biometrics , vol.55 , pp. 887-890
    • Joly, P.1    Commenges, D.2
  • 26
    • 0030327756 scopus 로고    scopus 로고
    • The selection of prior distributions by formal rules
    • Kass, R.E. and Wasserman, L. (1996). The selection of prior distributions by formal rules J. Amer. Statist. Assoc. 91, 1343-1370.
    • (1996) J. Amer. Statist. Assoc. , vol.91 , pp. 1343-1370
    • Kass, R.E.1    Wasserman, L.2
  • 30
    • 0000002459 scopus 로고
    • Maximum Likelihood: An Introduction
    • Le Cam, L. (1990). Maximum Likelihood: An Introduction. Int. Statist. Rev. 58, 153-171.
    • (1990) Int. Statist. Rev. , vol.58 , pp. 153-171
    • le Cam, L.1
  • 31
    • 0000676017 scopus 로고
    • Likelihood, Quasi-Likelihood and Pseudolikelihood: Some Comparisons
    • Lee, Y. and Nelder, J.A. (1992) Likelihood, Quasi-Likelihood and Pseudolikelihood: Some Comparisons. J. Roy. Statist. Soc. B 54, 273-284.
    • (1992) J. Roy. Statist. Soc. B , vol.54 , pp. 273-284
    • Lee, Y.1    Nelder, J.A.2
  • 32
    • 0000312997 scopus 로고    scopus 로고
    • Hierarchical Generalized Linear Models
    • Lee, Y. and Nelder, J.A. (1996). Hierarchical Generalized Linear Models. J. Roy. Statist. Soc. B 58, 619-678.
    • (1996) J. Roy. Statist. Soc. B , vol.58 , pp. 619-678
    • Lee, Y.1    Nelder, J.A.2
  • 33
    • 0012342630 scopus 로고    scopus 로고
    • Hierarchical generalised linear models: A synthesis of generalised linear models, random-effect models and structured dispersions
    • Lee, Y. and Nelder, J.A. (2001). Hierarchical generalised linear models: A synthesis of generalised linear models, random-effect models and structured dispersions. Biometrika 88, 987-1006.
    • (2001) Biometrika , vol.88 , pp. 987-1006
    • Lee, Y.1    Nelder, J.A.2
  • 36
    • 0001831031 scopus 로고
    • Consistent estimates based on partially consistent observations
    • Neymann, J. and Scott, E.L. (1988).Consistent estimates based on partially consistent observations. Econometrika 16, 1-32.
    • (1988) Econometrika , vol.16 , pp. 1-32
    • Neymann, J.1    Scott, E.L.2
  • 37
    • 0001047094 scopus 로고
    • Fast computation of fully automated log-density and log-hazard estimators
    • O'Sullivan, F. (1988). Fast computation of fully automated log-density and log-hazard estimators. SIAM J. Scient. Statist. Comput. 9, 363-379.
    • (1988) SIAM J. Scient. Statist. Comput. , vol.9 , pp. 363-379
    • O'Sullivan, F.1
  • 38
    • 0017133178 scopus 로고
    • Inference and missing data
    • Rubin, D.B. (1976). Inference and missing data. Biometrika 63, 581-592.
    • (1976) Biometrika , vol.63 , pp. 581-592
    • Rubin, D.B.1
  • 39
    • 62849120031 scopus 로고    scopus 로고
    • Approximate Bayesian inference for latent Gaussian models using integrated nested Laplace approximations
    • Rue, H., Martino, S. and Chopin, N. (2009). Approximate Bayesian inference for latent Gaussian models using integrated nested Laplace approximations. J. Roy. Statist. Soc. B 71, 1-35.
    • (2009) J. Roy. Statist. Soc. B , vol.71 , pp. 1-35
    • Rue, H.1    Martino, S.2    Chopin, N.3
  • 40
    • 0031321079 scopus 로고    scopus 로고
    • On methods of sieves and penalization
    • Shen, X. (1997). On methods of sieves and penalization. Ann. Statist. 25, 2555-2591.
    • (1997) Ann. Statist. , vol.25 , pp. 2555-2591
    • Shen, X.1
  • 44
    • 0000939344 scopus 로고
    • Bayesian "Confidence Intervals" for the Cross- Validated Smoothing Spline
    • Wahba, G. (1983). Bayesian "Confidence Intervals" for the Cross- Validated Smoothing Spline J. Roy. Statist. Soc. B 45, 133-150.
    • (1983) J. Roy. Statist. Soc. B , vol.45 , pp. 133-150
    • Wahba, G.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.