Maximum Penalized Likelihood Estimate in a Sobolev Space

  • Park, Young J. (Research Institute of Statistics, Seoul National University, Seoul, 151-742) ;
  • Lee, Young H. (Department of Mathematic Education, Ewha Womens University, Seoul, 120-750)
  • Published : 1997.03.01

Abstract

We show that the Maximum Penalized Likelihood Estimate uniquely exits in a Sobolve spece which consists of bivariate density functions. The Maximum Penalized Likehood Estimate is represented as the square of the sum of the solutions of the Modified Helmholtz's equation on the compact subset of R$^{2}$.

Keywords

References

  1. Mathematical Methods for Physicists Arfken, G.
  2. Nonparametric Density Estimation : The $L_1$ view Devroye, L.;Gyorfi, L.
  3. Biometrica v.58 Nonparametric roughness penalties for probability density Good, I.J.;Gaskin, R.A.
  4. Journal of the American Statistical Association v.86 recent Developments in Nonparametric Density Estimation Izenman, A.J.
  5. Density Estimation for Statistics and Data Analysis Silverman, B.W.
  6. Nonparametric Probability Density Estimation Tapia, R.A.;Thompson, J.R.
  7. Journal of the American Statistical Association v.78 Splines in Statistics Wegman, E.J.;Wright, I. W.