An Introduction to the Theory of Point Processes - Volume II: General Theory and Structure

von: D.J. Daley, David Vere-Jones

Springer-Verlag, 2007

ISBN: 9780387498355 , 573 Seiten

2. Auflage

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Kopierschutz: Wasserzeichen

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An Introduction to the Theory of Point Processes - Volume II: General Theory and Structure


 

Preface to Volume II, Second Edition

7

Contents

9

Chapter Titles for Volume I

11

Principal Notation

12

Concordance of Statements from the First Edition

16

9 Basic Theory of Random Measures and Point Processes

18

9.1. Definitions and Examples

19

9.2. Finite-Dimensional Distributions and the Existence Theorem

42

9.3. Sample Path Properties: Atoms and Orderliness

55

9.4. Functionals: Definitions and Basic Properties

69

9.5. Moment Measures and Expansions of Functionals

82

10 Special Classes of Processes

93

10.1. Completely Random Measures

94

10.2. In.nitely Divisible Point Processes

104

10.3. Point Processes De.ned by Markov Chains

112

10.4. Markov Point Processes

135

11 Convergence Concepts and Limit Theorems

148

11.1. Modes of Convergence for Random Measures and Point Processes

149

11.2. Limit Theorems for Superpositions

163

11.3. Thinned Point Processes

172

11.4. Random Translations

183

12 Stationary Point Processes and Random Measures

193

12.1. Stationarity: Basic Concepts

194

12.2. Ergodic Theorems

211

12.3. Mixing Conditions

223

12.4. Stationary In.nitely Divisible Point Processes

233

12.5. Asymptotic Stationarity and Convergence to Equilibrium

239

12.6. Moment Stationarity and Higher- order Ergodic Theorems

253

12.7. Long-range Dependence

266

12.8. Scale-invariance and Self-similarity

272

13 Palm Theory

285

13.1. Campbell Measures and Palm Distributions

286

13.2. Palm Theory for Stationary Random Measures

301

13.3. Interval- and Point-stationarity

316

13.4. Marked Point Processes, Ergodic Theorems, and Convergence to Equilibrium

334

13.5. Cluster Iterates

351

13.6. Fractal Dimensions

357

14 Evolutionary Processes and Predictability

372

14.1. Compensators and Martingales

373

14.2. Campbell Measure and Predictability

393

14.3. Conditional Intensities

407

14.4. Filters and Likelihood Ratios

417

14.5. A Central Limit Theorem

429

14.6. Random Time Change

435

14.7. Poisson Embedding and Existence Theorems

443

14.8. Point Process Entropy and a Shannon – MacMillan Theorem

457

15 Spatial Point Processes

474

15.1. Descriptive Aspects: Distance Properties

475

15.2. Directional Properties and Isotropy

483

15.3. Stationary Line Processes in the Plane

488

15.4. Space–Time Processes

502

15.5. The Papangelou Intensity and Finite Point Patterns

523

15.6. Modi.ed Campbell Measures and Papangelou Kernels

535

15.7. The Papangelou Intensity Measure and Exvisibility

543

References with Index

554

Subject Index

574