Computational procedure for maximum penalized likelihood estimate Footnote†

†This work was based on the Ph.D. Thesis of the first author at Purdue University.

References

• Box , G.E.P. and Tiao , G. 1964 . A Bayesian approach to the importance of assumptions applied to comparison of variances . Biometrika , 51 : 153 – 167 .
   Web of Science ®Google Scholar
• Breiman , L. , Miesel , W. and Purcell , E. 1977 . Variable kernel estimates of multivariate densities . Technometrics , 19 ( 2 ) : 135 – 144 .
   Web of Science ®Google Scholar
• Crockett , J.B. and Chernoff , H. 1955 . Gradiant methods of maximization . Pacific J. Math , 5 : 33 – 50 .
   Google Scholar
• Ghorai , J.K. 1977 . Unpublished Ph.D Thesis , Purdue University .
   Google Scholar
• Good , I.J. and Gaskin , R.A. 1971 . Nonparametric roughness penalties for probability densities . Biometrika , 58 : 255 – 277 .
   Web of Science ®Google Scholar
• Isaacson , E. and Keller , H.B. 1966 . Analysis of Numerical Methods , New York : John Wiley and Sons .
   Google Scholar
• Montricher , G.F. , Tapia , R.A. and Thompson , J.R. 1975 . Nonparametric maximum likelihood estimation of probability densities by penalty function methods . Anns. of Statist , 3 : 1329 – 1348 .
   Google Scholar