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Volumn 77, Issue 9, 2007, Pages 925-930

Asymptotic properties of a double penalized maximum likelihood estimator in logistic regression

Author keywords

Logistic regression; Maximum likelihood; Penalized maximum likelihood; Ridge regression

Indexed keywords


EID: 34047276652     PISSN: 01677152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.spl.2007.01.004     Document Type: Article
Times cited : (30)

References (22)
  • 1
    • 0002662712 scopus 로고
    • On the existence of maximum likelihood estimates in logistic regression models
    • Albert A., and Anderson J.A. On the existence of maximum likelihood estimates in logistic regression models. Biometrika 71 (1984) 1-10
    • (1984) Biometrika , vol.71 , pp. 1-10
    • Albert, A.1    Anderson, J.A.2
  • 2
    • 0002467271 scopus 로고
    • Logistic discrimination and bias correction in maximum likelihood estimation
    • Anderson J.A., and Richardson S.C. Logistic discrimination and bias correction in maximum likelihood estimation. Technometrics 21 (1979) 71-78
    • (1979) Technometrics , vol.21 , pp. 71-78
    • Anderson, J.A.1    Richardson, S.C.2
  • 3
    • 0037187858 scopus 로고    scopus 로고
    • A modified score function estimator for multinomial logistic regression in small samples
    • Bull S.B., Mak C., and Greenwood C.M.T. A modified score function estimator for multinomial logistic regression in small samples. Comput. Statist. Data Anal. 39 1 (2002) 57-74
    • (2002) Comput. Statist. Data Anal. , vol.39 , Issue.1 , pp. 57-74
    • Bull, S.B.1    Mak, C.2    Greenwood, C.M.T.3
  • 4
    • 0000889845 scopus 로고
    • Binary regression models for contaminated data, with discussuion
    • Copas J.B. Binary regression models for contaminated data, with discussuion. J. Roy. Statist. Soc. Ser. B 50 (1988) 225-265
    • (1988) J. Roy. Statist. Soc. Ser. B , vol.50 , pp. 225-265
    • Copas, J.B.1
  • 6
    • 80053264999 scopus 로고
    • How biased is the apparent error rate of a prediction rule?
    • Efron B. How biased is the apparent error rate of a prediction rule?. J. Amer. Statist. Assoc. 81 (1986) 461-470
    • (1986) J. Amer. Statist. Assoc. , vol.81 , pp. 461-470
    • Efron, B.1
  • 7
    • 34047264696 scopus 로고    scopus 로고
    • Firth, D., 1992. Bias reduction, the Jeffreys prior and GLIM. In: Fahrmeir, L., Francis, B., Gilchrist, R., Tutz, G., (Eds.), Advances in GLIM and Statistical Modelling. Springer, NY.
  • 8
    • 0002178053 scopus 로고
    • Bias reduction of maximum likelihood estimates
    • Firth D. Bias reduction of maximum likelihood estimates. Biometrika 80 1 (1993) 27-38
    • (1993) Biometrika , vol.80 , Issue.1 , pp. 27-38
    • Firth, D.1
  • 9
    • 16344365619 scopus 로고    scopus 로고
    • Classification using partial least squares with penalized logistic regression
    • Fort G., and Lambert-Lacroix S. Classification using partial least squares with penalized logistic regression. Bioinformatics 21 7 (2005) 1104-1111
    • (2005) Bioinformatics , vol.21 , Issue.7 , pp. 1104-1111
    • Fort, G.1    Lambert-Lacroix, S.2
  • 10
    • 34047258930 scopus 로고    scopus 로고
    • Harrell,F.E., Lee, K.L., 1985. The practical value of logistic regression. Proceedings of the Tenth Annual SAS Users Groups International Conference, SAS Institute Inc., Cary, North Carolina, pp. 1031-1036.
  • 11
    • 0037199788 scopus 로고    scopus 로고
    • A solution to the problem of separation in logistic regression
    • Heinze G., and Schemper M. A solution to the problem of separation in logistic regression. Statist. Med. 21 16 (2002) 2409-2419
    • (2002) Statist. Med. , vol.21 , Issue.16 , pp. 2409-2419
    • Heinze, G.1    Schemper, M.2
  • 12
    • 84942484786 scopus 로고
    • Ridge regression: biased estimation for nonorthogonal problems
    • Hoerl A.E., and Kennard R.W. Ridge regression: biased estimation for nonorthogonal problems. Technometrics 12 (1970) 55-67
    • (1970) Technometrics , vol.12 , pp. 55-67
    • Hoerl, A.E.1    Kennard, R.W.2
  • 13
    • 34047265718 scopus 로고    scopus 로고
    • Hoerl, A.E., Kennard, R.W. 1988. Ridge Regression. Encyclopedia of Statistical Sciences 9 vols., vol. 8 (Suppl.). Wiley, New York, pp. 129-136.
  • 14
    • 79960450252 scopus 로고
    • On Bayesian analysis of generalized linear models using Jeffrey's prior
    • Ibrahim J.G., and Laud P.W. On Bayesian analysis of generalized linear models using Jeffrey's prior. J. Amer. Statist. Assoc. 86 (1991) 981-986
    • (1991) J. Amer. Statist. Assoc. , vol.86 , pp. 981-986
    • Ibrahim, J.G.1    Laud, P.W.2
  • 15
    • 84873751778 scopus 로고
    • An invariant form for the prior probability in estimation problems
    • Jeffreys H. An invariant form for the prior probability in estimation problems. Proc. Roy. Soc. A. 186 (1946) 453-461
    • (1946) Proc. Roy. Soc. A. , vol.186 , pp. 453-461
    • Jeffreys, H.1
  • 16
    • 0033234636 scopus 로고    scopus 로고
    • Conditional inference about generalized linear mixed models
    • Jiang J. Conditional inference about generalized linear mixed models. Ann. Statist. 27 (1999) 1974-2007
    • (1999) Ann. Statist. , vol.27 , pp. 1974-2007
    • Jiang, J.1
  • 18
    • 0002322488 scopus 로고
    • A note on bias correction in maximum likelihood estimation with logistic discrimination
    • McLachlan G. A note on bias correction in maximum likelihood estimation with logistic discrimination. Technometrics 22 (1980) 621-627
    • (1980) Technometrics , vol.22 , pp. 621-627
    • McLachlan, G.1
  • 19
    • 34047266866 scopus 로고    scopus 로고
    • McCullagh, P., Nelder, J.A., 1989. Generalized linear models, second ed. Chapman & Hall, London.
  • 21
    • 0020623772 scopus 로고
    • Bias correction in maximum likelihood logistic regression
    • Schaefer R.L. Bias correction in maximum likelihood logistic regression. Statist. Med. 2 (1983) 71-78
    • (1983) Statist. Med. , vol.2 , pp. 71-78
    • Schaefer, R.L.1
  • 22
    • 34047273082 scopus 로고    scopus 로고
    • Shen, J., Gao, S., 2006. A solution to separation and multicollinearity in multiple logistic regression. J. Data Sci., in press.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.