soxumis saxelmwifo universitetis S r o m e b i VII

Remark 1. While proving the theorem, we see that a or b may beinfinite. The case a and b correspond to the case of leftcensoring, whereas for a and b we have the right censoring.Example 1. If a and b 0 , then we obtain the following equationfor defining ˆ : 2n 1 ln 1 X i. n n i1Example 2. As has been shown in proving the theorem, forn1the equation (8) implies the classical case ˆ .X in i1b aREFERENCES1. G. Kulldorff. To the theory of estimation from grouped and partiallygrouped samples. Nauka. Moscow, 1966.2. L. Weiss, J. Wolfowitz. Maximum likelihood estimation of a translationparameter of a truncated distribution. – Ann. Statist. 1 (1973),944-947.3. N. Balakrishnan, Sh. Gupta, S. Panchapakesan. Estimation of thelocation and scale parameters of the extreme value distribution basedon multiply type-II censored samples. – Comm. Statist. TheoryMethods. 24 (1995), No. 8, 2105-2125.4. J. M. Wooldridge. Econometric analysis of cross section and paneldata. – Cambridge, MA: MIT Press, 2002.5. Zh. Zhang, H. E. Rockette. Semiparametric maximum likelihoodfor missing covariates in parametric regression. – Ann. Inst. Statist.Math. 58 (2006), No. 4, 687-706.6. T. S. Ferguson. A course in large sample theory. – Texts in StatisticalScience Series. Chapman & Hall. London, 1996.7. J. V. Dillon, G. Lebanon. Statistical and computational tradeoffs instochastic compose likelihood. ArXiv: 1003.0691v1., 2010, 29 p.42