Page 146 - Invited Paper Session (IPS) - Volume 2

IPS192 Hukum C. et al.
small area estimation technique. Journal of Applied Statistics 38(11),
2413-2432.
4. Eilers, P. H. C. and B. D. Marx, 1996. Flexible smoothing with B-splines
and penalties. Statistical Science 11 (2), 89–121.
5. Fay, R. E. and Herriot, R. A., 1979. Estimation of income from small
places: an application of James-Stein procedures to census data. Journal
of the American Statistical Association 74, 269277.
6. Green, P.J. and Silverman, B.W., 1994. Nonparametric Regression and
Generalized Linear Models: A Roughness Penalty Approach. Chapman &
Hall Ltd.
7. Manteiga, G.W., Lombardìa, M.J., Molina, I., Morales, D., and
Santamarìa,L., 2007. Estimation of the mean squared error of predictors
of small area linear parameters under a logistic mixed model.
Computational Statistics and Data Analysis 51, 2720-2733.
8. Opsomer, J.D., Claeskens, G., Ranalli, M.G., Kauermann, G. and Breidt, F.J.,
2008. Nonparametric small area estimation using penalized spline
regression. Journal of the Royal Statistical Society B 70, 265-286.
9. Pratesi, M., Ranalli, M.G., Salvati, N., 2009. Nonparametric M-quantile
regression using penalised splines. Journal of Nonparametric Statistics
21, 287-304.
10. Ruppert D., Wand M.P., Carroll R.J., 2003. Semiparametric Regression.
Cambridge University Press, New York.

133 | I S I W S C 2 0 1 9