Space-time point processes an applied statistics course Frederic Schoenberg

Format:

Book

Author/Creator:

Schoenberg, Frederic Paik, author.

Series:

Springer texts in statistics

Springer texts in statistics 2197-4136

Language:

English

Subjects (All):

Point processes.

Physical Description:

1 online resource

Place of Publication:

Cham, Switzerland Springer [2026]

Summary:

"The book focuses on applied methodology, and summarizes the main issues in the practical applications associated with space-time point processes. Applied examples are used throughout the book, and the text includes R code for implementing all the techniques discussed in the book. The book covers standard, classical methods for point processes, such as Poisson processes, Cox processes, Neyman-Scott processes, Hawkes models, conditional intensities, kernel smoothing, and Ripley's K-function, and also describes important recent advances for space-time point processes, such as Model-Independent Stochastic Declustering (MISD), Stoyan-Grabarnik parameter estimation, Voronoi deviance residuals, and super-thinned residuals.The book is meant to be used for teaching at the graduate or undergraduate levels. Sample exercises are given at the end of each chapter, and these problems are not too difficult and thus suitable for undergraduate or graduate students in applied statistics. The goal is to educate and train students in the practical aspects of the summary, description and forecasting of spatial-temporal point process data"-- Springer Nature Link

Contents:

Models

Estimation

Adjectives

Model evaluation

Notes:

Includes bibliographical references

Online resource; title from PDF title page (Springer Nature Link, viewed June 18, 2026)

Other Format:

Print version Schoenberg, Frederic Paik Space-time point processes

ISBN:

9783032207906

3032207908

OCLC:

1596201848

Access Restriction:

Restricted for use by site license