Original title: Divergences between models and data under hypothetical and empirical quantizations
Translated title: Divergence mezi modely a daty pri hypotetickém a empirickém kvantování
Authors: Vajda, Igor ; van der Meulen, Edward
Document type: Research reports
Year: 2010
Language: eng
Series: Research Report, volume: 2275
Abstract: [eng] [cze]
It is shown that the hypothetical quantization generates classical Pearson-type statistical criteria while the empirical quantization generates criteria asymptotically equivalent to the classical spacings-type statistical criteria. Asymptotic properties of the empirically generated criteria are derived and optimality of the quadratic criterion is proved. Je ukazáno, že hypotetické kvantování generuje clasická statistická kriteria Pearsonova typu, zatim co empirické kvantování generuje kriteria asymptoticky ekvivalentní klasickým přírůstkovým statistickým kriteriím.Jsou odvozeny asymptotické vlastnosti empiricky generovaných kriterií a dokázána optimálnost kvadratického kriteria.
Keywords: Asymptotic normality; Asymptotic optimality; Consistency; Disparities; Divergences; Empirical quantization; Hypothetical quantization; Power divergences
Project no.: CEZ:AV0Z10750506 (CEP), 1M0572 (CEP), GA102/07/1131 (CEP)
Funding provider: GA MŠk, GA ČR

Institution: Institute of Information Theory and Automation AS ČR (web)
Document availability information: Fulltext is available at external website.
External URL: http://library.utia.cas.cz/separaty/2010/SI/vajda-divergences between models and data under hypothetical and empirical quantizations.pdf
Original record: http://hdl.handle.net/11104/0181315

Permalink: http://www.nusl.cz/ntk/nusl-41138


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