Leszek Klukowski

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An earlier study of free-living male dark-eyed juncos found an increase in plasma corticosterone (B) in response to experimental elevation of plasma testosterone (T) (E. D. Ketterson et al., 1991, Horm. Behav. 25, 489-503). To investigate whether the increase was caused by enhanced secretion of corticosterone or by a slower clearance rate, or both, we(More)
The statistical procedure for determination of the type of relation – equivalence or tolerance – in a finite set of elements, estimated on the basis of pairwise comparisons with random errors, is presented. The procedure consists of two tests based on Chebyshev’s inequality for variance of a random variable; the test statistic is a mixture of some random(More)
The methods of tolerance relation estimation on the basis of pairwise comparisons with random errors, in the case of multiple comparisons for each pair, are proposed in the paper. Each comparison expresses the number of common features of both elements or the number of their missing features. The assumptions made about distributions of comparison errors are(More)
The volume is dedicated to Professor S. Panchapakesan, who has made an excellent and significant contribution to several different fields of statistics. The book is a collection of twenty papers divided into six parts: INFERENCE , RANKING AND SELECTION, MULTIPLE COMPARISONS AND TESTS, AGREEMENT ASSESSMENT ANALYSIS, RELIABILITY, BIOSTA-TISTICS. The authors(More)
This paper presents a review of results of the author in the area of estimation of the relations of equivalence, tolerance and preference within a finite set based on multiple, independent (in a stochastic way) pairwise comparisons with random errors, in binary and multivalent forms. These estimators require weaker assumptions than those used in the(More)
The statistical procedure for determination of the relation type – equivalence or tolerance – in a finite set on the basis of multiple pairwise comparisons with random errors is presented in the paper. The procedure consists of two tests; it is an extension of the approach presented in [3]. The test statistics is based on a mixture of some random variables(More)