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Record Nr. |
UNINA9910461171903321 |
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Autore |
Basu Ayanendranath |
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Titolo |
Statistical inference : the minimum distance approach / / Ayanendranath Basu, Hiroyuki Shioya, Chanseok Park |
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Pubbl/distr/stampa |
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Boca Raton, Fla. : , : Chapman & Hall/CRC, , 2011 |
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ISBN |
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0-429-13390-1 |
1-283-31148-8 |
9786613311481 |
1-4200-9966-3 |
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Descrizione fisica |
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1 online resource (424 p.) |
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Collana |
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Monographs on statistics and applied probability ; ; 120 |
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Altri autori (Persone) |
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ShioyaHiroyuki |
ParkChanseok |
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Disciplina |
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Soggetti |
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Estimation theory |
Distances |
Electronic books. |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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Front Cover; Dedication; Contents; Preface; Acknowledgments; 1. Introduction; 2. Statistical Distances; 3. Continuous Models; 4. Measures of Robustness and Computational Issues; 5. The Hypothesis Testing Problem; 6. Techniques for Inlier Modification; 7. Weighted Likelihood Estimation; 8. Multinomial Goodness-of-Fit Testing; 9. The Density Power Divergence; 10. Other Applications; 11. Distance Measures in Information and Engineering; 12. Applications to Other Models; Bibliography |
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Sommario/riassunto |
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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. Compr |
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