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Nonlinear Estimation - Gavin J. S. Ross

Anglų
2011-10-08
63,51 € 84,68 €

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Non-Linear Estimation is a handbook for the practical statistician or modeller interested in fitting and interpreting non-linear models with the aid of a computer. A major theme of the book is the use of 'stable parameter systems'; these provide rapid convergence of optimization algorithms, more reliable dispersion matrices and confidence regions for parameters, and easier comparison of rival models. The bo ... Visas aprašymas

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Non-Linear Estimation is a handbook for the practical statistician or modeller interested in fitting and interpreting non-linear models with the aid of a computer. A major theme of the book is the use of 'stable parameter systems'; these provide rapid convergence of optimization algorithms, more reliable dispersion matrices and confidence regions for parameters, and easier comparison of rival models. The book provides insights into why some models are difficult to fit, how to combine fits over different data sets, how to improve data collection to reduce prediction variance, and how to program particular models to handle a full range of data sets. The book combines an algebraic, a geometric and a computational approach, and is illustrated with practical examples. A final chapter shows how this approach is implemented in the author's Maximum Likelihood Program, MLP.

Daugiau informacijos

Autorius Gavin J. S. Ross
Leidėjas Springer US
Series Springer Series in Statistics
Išleidimo metai 2011
Viršelio tipas Minkšti viršeliai
EAN 9781461280019
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63,51 € 84,68 €