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Statistical Inference in Stochastic Processes de N. U. Prabhu

Statistical Inference in Stochastic Processes: Probability: Pure and Applied

Editat de N. U. Prabhu
en Limba Engleză Paperback – 17 oct 2019
Covering both theory and applications, this collection of eleven contributed papers surveys the role of probabilistic models and statistical techniques in image analysis and processing, develops likelihood methods for inference about parameters that determine the drift and the jump mechanism of a di
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Specificații

ISBN-13: 9780367403072
ISBN-10: 0367403072
Pagini: 288
Dimensiuni: 152 x 229 mm
Greutate: 0.54 kg
Ediția:1
Editura: CRC Press
Colecția CRC Press
Seria Probability: Pure and Applied

Public țintă

Undergraduate

Cuprins

Preface -- 1 Statistical Models and Methods in Image Analysis: A Survey /Alan F. Karr -- 2 Edge-Preserving Smoothing and the Assessment of Point Process Models for GATE Rainfall Fields /Colin R. Goodall and Michael J. Phelan -- 3 Likelihood Methods for Diffusions with Jumps /Michael SVJrensen -- 4 Efficient Estimating Equations for Nonparametric Filtered Models /P. E. Greenwood and W. Wefelmeyer -- 5 Nonparametric Estimation of Trends in Linear Stochastic Systems /Jan W. McKeague and Tiziano Tofani -- 6 Weak Convergence of Two-Sided Stochastic Integrals, with an Application to Models for Left Truncated Survival Data /Michael Davidsen and Martin Jacobsen -- 7 Asymptotic Theory of Weighted Maximum Likelihood Estimation for Growth Models /B. L. S. Prakasa Rao -- 8 Markov Chain Models for Type-Token Relationships /D. J. Daley, J. M. Gani, and D. A. Ratkowsky -- 9 A State-Space Approach to Transfer-Function Modeling /P. J. Brockwell, R. A. Davis, and H. Salehi -- 10 Shrinkage Estimation for a Dynamic Input-Output Linear Model /Young-Won Kim, David M. Nickerson, and I. V. Basawa -- 11 Maximum Probability Estimation for an Autoregressive Process /Lionel Weiss -- Index.

Descriere

Covering both theory and applications, this collection of eleven contributed papers surveys the role of probabilistic models and statistical techniques in image analysis and processing, develops likelihood methods for inference about parameters that determine the drift and the jump mechanism of a di