000 03273cam a22003614i 4500
999 _c5490
_d5490
001 14075962
005 20210906093122.0
008 050816s2005 riua b 001 0 eng
010 _a 2005052661
020 _a082183732X (alk. paper)
040 _aDLC
_cDLC
_dDLC
_erda
041 1 _aeng
_hrus
050 0 0 _aQA276.16
_b.L5513 2005
082 0 0 _a519.5
_bL.Y.L
_222
100 1 _aLinʹkov, I͡U︡. N.
_925599
_eauthor
240 1 0 _aLekt͡s︡ii po matematicheskoi statistike.
_lEnglish
245 1 0 _aLectures in mathematical statistics :
_bparts 1 and 2 /
_cYu. N. Linʹkov ; translated by Oleg Klesov and Vladmir Zayats.
264 1 _aProvidence, R.I. :
_bAmerican Mathematical Society,
_cc2005.
264 4 _cc2005.
300 _avii, 321 pages :
_billustrations ;
_c27 cm.
336 _2rdacontent
_atext
337 _2rdamedia
_aunmediated
338 _2rdacarrier
_avolume
440 0 _aTranslations of mathematical monographs,
_x0065-9282 ;
_vv. 229
_925600
504 _aIncludes bibliographical references and index.
505 0 _a pt. 1. Samples from one-dimensional distributions -- Empirical distribution function and its asymptotic behavior -- Sample characteristics and their properties -- Order statistics and their properties -- The distributions of some functions of Gaussian random vectors -- Samples from multidimensional distributions -- Empirical distribution function, sampling moments, and their properties -- Sampling regression and its properties -- Estimation of unknown parameters of distributions -- Statistical estimators and their quality measures -- Estimation of a location parameter -- Estimation of a scale parameter -- The Cramér-Rao inequality and efficient estimators -- The Cramér-Rao inequality for a multidimensional parameter -- Integral inequalities of Cramér-Rao type -- Sufficient statistics -- Sufficient statistics and a theorem on factorization -- Sufficient statistics and optimal estimators -- General methods for constructing estimators -- Method of moments -- The maximum likelihood method -- Bayes and minimax methods -- Confidence intervals and regions -- pt. 2. General theory of hypotheses testing -- Testing two simple hypotheses -- Distinguishing a finite number of simple hypotheses -- Distinguishing composite hypotheses -- Asymptotic distinguishability of simple hypotheses -- Statistical hypotheses and tests -- Types of the asymptotic distinguishability of families of hypotheses. The characterization of types -- Complete asymptotic distinguishability under the strong law of large numbers -- Complete asymptotic distinguishability under the weak convergence -- Contiguous families of hypotheses -- Goodness-of-fit tests -- The setting of the problem. Kolmogorov test -- The Pearson test -- Smirnov test -- Other goodness-of-fit tests -- Sequential tests -- Bayes sequential tests of hypotheses -- Wald sequential tests -- The optimality of a sequential Wald test.
650 0 _aMathematical statistics.
_925601
856 4 1 _3Table of contents
_uhttp://www.loc.gov/catdir/toc/fy0604/2005052661.html
856 4 1 _3Abstract
_uhttp://repository.fue.edu.eg/xmlui/handle/123456789/2692
942 _cBK
_2ddc