Institute of Mathematics
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Item type:Publication, PROPRETIES OF THE K-TH UPPER ORDER STATISTICS PROCESS THROUGH AN EXAMPLE(Union of Mathematicians of Macedonia, 2019)Aneta Gacovska-BarandovskaThe author has previously considered the asymptotic be havior of upper order statistics with central rank of a sample with deterministic size and of randomly indexed upper order statistics. In this paper, by using regular norming time-space changes, a theoretical example has been constructed in order to illustrate some of the ob tained properties of the k-th upper order statistics process. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, On limit laws for central order statistics under power normalization(Bulgarian Academy of Sciences, Institute of Mathematics and Informatics, 2015)Elisaveta I. Pancheva, Aneta Gacovska-BarandovskaSmirnov (1949) derived four limit classes of distributions for linearly normalized central order statistics. In this paper we investigate the possible limit distributions of the k-th upper order statistics with central rank using regular power norming sequences and obtain twelve limit classes. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Asymptotic behavior of central order statistics under monotone normalization(Elsevier, SIAM, 2014)Pancheva, E.I. Gacovska, A.Smirnov [Trudy Mat. Inst. Steklov., 25 (1949), pp. 3-60 (in Russian); Amer. Math. Transl., 67 (1952) (in English)] derived four limit types of distributions for linearly normalized central order statistics under the weak convergence. In this paper we investigate the possible limit distributions of the kth upper order statistics with central rank using monotone regular norming sequences and obtain 13 possible types. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Randomly Indexed Central Order Statistics(Bulgarian Academy of Sciences, 2013)Gacovska, Aneta Pancheva, Elisaveta I.In our paper from 2012 we have considered the upper order statistics with central rank of sample with deterministic size. Here we investigate the asymptotic behaviour of randomly indexed upper order statistics using regular norming time-space changes.