Get Conceptual Modelling and Its Theoretical Foundations: Essays PDF

By Antje Düsterhöft, Meike Klettke, Klaus-Dieter Schewe

ISBN-10: 3642282784

ISBN-13: 9783642282782

ISBN-10: 3642282792

ISBN-13: 9783642282799

This Festschrift, released in honor of Bernhard Thalheim at the social gathering of his sixtieth birthday provides 20 articles by means of colleagues from around the globe with whom Bernhard Thalheim had cooperation in a number of respects; additionally integrated is a systematic biography contributed via the quantity editors. The 20 contributions mirror the breadth and the intensity of the paintings of Bernhard Thalheim in conceptual modeling and database idea in the course of his medical occupation spanning greater than 35 years of lively learn. particularly, ten articles are targeting issues like database dependency conception, object-oriented databases, triggers, summary kingdom machines, database and data structures layout, net semantics, and enterprise processes.

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Extra info for Conceptual Modelling and Its Theoretical Foundations: Essays Dedicated to Bernhard Thalheim on the Occasion of His 60th Birthday

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Problems Infor. Transmiss. : U -Statistics: Theory and Practice. : A class of R´enyi information estimators for multidimensional densities. Ann. Stat. 36, 2153–2182 (2008); Corrections, Ann. Stat. : Statistical inference for the -entropy and the quadratic R´enyi entropy. Jour. : Statistical Inference Based on Divergence Measures. : On measures of entropy and information. In: Proc. 4th Berkeley Symp. Math. Statist. , vol. : Probability Theory. : Average case analysis in database problems. Methodol.

In: Proc. of the 4th Berkeley Symposium on Mathematics, Statistics and Probability, pp. 547–561 (1960/1961) 6. : Average Case Analysis in Database Problems. Methodology and Computing in Applied Probability 5(4), 395–418 (2003) 7. : Random Databases with Approximate Record Matching. Methodology and Computing in Applied Probability 12(1), 63–89 (2010) Statistical Inference for R´ enyi Entropy Functionals David K¨allberg1 , Nikolaj Leonenko2 , and Oleg Seleznjev1 1 Department of Mathematics and Mathematical Statistics, Ume˚ a University, SE-901 87 Ume˚ a, Sweden 2 School of Mathematics, Cardiff University, Senghennydd Road, Cardiff CF24 4YH, UK Abstract.

K¨ allberg, N. Leonenko, and O. Seleznjev volume b (d) = probability d b1 (d), b1 (d) = 2π d/2 /(dΓ (d/2)). Denote by pX, (x) the -ball pX, (x) := P {X ∈ B (x)}. We write I(C) for the indicator of an event C, and |D| for the cardinality of a finite set D. Next we define estimators of qr when r1 and r2 are non-negative integers with r1 + r2 ≥ 2. In order to include the one-sample case, we assume without loss of generality that r1 ≥ r2 . So, we have that r1 ≥ 1. Denote n := (n1 , n2 ), n := n1 + n2 , and say that n → ∞ if n1 , n2 → ∞.

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Conceptual Modelling and Its Theoretical Foundations: Essays Dedicated to Bernhard Thalheim on the Occasion of His 60th Birthday by Antje Düsterhöft, Meike Klettke, Klaus-Dieter Schewe

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