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429 pages. 9.19x6.13x1.30 inches. In Stock. N° de réf. du vendeur __1032477636
In many ways, estimation by an appropriate minimum distance method is one of the most natural ideas in statistics. However, there are many different ways of constructing an appropriate distance between the data and the model: the scope of study referred to by "Minimum Distance Estimation" is literally huge. Filling a statistical resource gap, Statistical Inference: The Minimum Distance Approach comprehensively overviews developments in density-based minimum distance inference for independently and identically distributed data. Extensions to other more complex models are also discussed.
Comprehensively covering the basics and applications of minimum distance inference, this book introduces and discusses:
Statistical Inference: The Minimum Distance Approach gives a thorough account of density-based minimum distance methods and their use in statistical inference. It covers statistical distances, density-based minimum distance methods, discrete and continuous models, asymptotic distributions, robustness, computational issues, residual adjustment functions, graphical descriptions of robustness, penalized and combined distances, weighted likelihood, and multinomial goodness-of-fit tests. This carefully crafted resource is useful to researchers and scientists within and outside the statistics arena.
À propos de l?auteur: Ayanendranath Basu, Hiroyuki Shioya, Chanseok Park
Titre : Statistical Inference: The Minimum Distance ...
Éditeur : CRC Pr I Llc
Date d'édition : 2023
Reliure : Paperback
Etat : Brand New
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Etat : New. Ayanendranath Basu, Hiroyuki Shioya, Chanseok ParkIn many ways, estimation by an appropriate minimum distance method is one of the most natural ideas in statistics. However, there are many different ways of constructing an appropriate dist. N° de réf. du vendeur 801266711
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Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
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Paperback / softback. Etat : New. New copy - Usually dispatched within 4 working days. 185. N° de réf. du vendeur B9781032477633
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Taschenbuch. Etat : Neu. Neuware - In many ways, estimation by an appropriate minimum distance method is one of the most natural ideas in statistics. However, there are many different ways of constructing an appropriate distance between the data and the model: the scope of study referred to by 'Minimum Distance Estimation' is literally huge. Filling a statistical resource gap, Statistical Inference: The Minimum Distance Approach comprehensively overviews developments in density-based minimum distance inference for independently and identically distributed data. Extensions to other more complex models are also discussed. N° de réf. du vendeur 9781032477633
Quantité disponible : 2 disponible(s)