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Скачать Selected Proceedings of the Symposium on Inference for Stochastic Processes бесплатно

25 апреля 2009 | Автор: Admin | Рубрика: Научная литература » Экономика | Комментариев: 0
094060051X

Selected Proceedings of the Symposium on Inference for Stochastic Processes: By Ishwar V. Basawa (Editor), Robert L. Taylor (Editor), C. C. Heyde (Editor)
Institute of Mathematical Statistics | ISBN: 094060051X | 2001 | 355 pages | djvu (ocr) | 7.34 Mb

CONTENTS:

Section 1: Introduction
An Overview of the Symposium (I. V. Basawa, C. C. Heyde, and R. L. Taylor; 3-8)
Shifting Paradigms in Inference (C. C. Heyde; 9-22)

Section 2: Stochastic Models: General
Modelling by Levy Processes (Ole E. Barndorff-Nielsen; 25-32)
Extreme Values for a Class of Shot-Noise Processes (W. P. McCormick, and Lynne Seymour; 33-46)
Statistical Inference for Stochastic Partial Differential Equations (B. L. S. Prakasa Rao; 47-70)
Fixed Design Regression Under Association (George G. Roussas; 71-90)
Dependent Bootstrap Confidence Intervals (Wendy D. Smith, and Robert L. Taylor; 91-108)

Section 3: Time Series
Kolmogorov-Smirnov Tests for AR Models Based on Autoregression Rank Scores (Faouzi El Bantli, and Marc Hallin; 111-124)
Estimation of the Long-Memory Parameter: A Review of Recent Developments and an Extension (Rajendra J. Bhansali, and Piota S. Kokoszka; 125-150)
Stability of Nonlinear Time Series: What Does Noise Have to Do With It? (Daren B. H. Cline, and Huay-min H. Pu; 151-170)

Section 4: Population Genetics
Testing Neutrality of mtDNA Using Multigeneration Cytonuclear Data (Susmita Datta; 173-184)
Inference on Random Coefficient Models for Haplotype Effects in Dynamic Mutation Using MCMC (Richard M. Huggins, Guoqi Qian, and Danuta Z. Loesch; 185-202)

Section 5: Semiparametric Inference
Semiparametric Inference for Synchronization of Population Cycles (P. E. Greenwood, and D. T. Haydon; 205-212)
Plug-In Estimators in Semiparametric Stochastic Process Models (Ursula U. Muller, Anton Sch?ck, and Wolfgang Wefelmeyer; 213-234)

Section 6: Estimating Functions
Nuisance Parameter Elimination and Optimal Estimating Functions (T. M. Durairajan, and Martin L. William; 237-246)
Optimal Estimating Equations for Mixed Effects Models with Dependent Observations (Jeong-gun Park, and I. V. Basawa; 247-268)

Section 7: Spatial Models
Reconstruction of a Stationary Spatial Process from a Systematic Sampling (Karim Benhenni; 271-280)
Estimating the Variance of the Maximum Pseudo-Likelihood Estimator (Lynne Seymour; 281-296)
A Review of Inhomogeneous Markov Point Processes (Eva B. Vedel Jensen, and Linda Stougaard Nielsen; 297-318)

Section 8: Perfect Simulation
Perfect Sampling for Posterior Landmark Distributions with an Application to the Detection of Disease Clusters (Marc A. Loizeaux, and Ian W. McKeague; 321-332)
A Review of Perfect Simulation in Stochastic Geometry (Jesper Moller; 333-356)

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