Peter Diggle is a Distinguished University Professor and group leader of CHICAS at Lancaster University. Dr. Diggle is also an adjunct professor of biostatistics at both Johns Hopkins University’s and Yale University’s Schools of Public Health, adjunct senior researcher in the International Research Institute for Climate and Society at Columbia University, professor of epidemiology and statistics at the University of Liverpool, a trustee for Biometrika, founding co-editor and advisory board member for Biostatistics, and chair of the Strategic Skills Fellowships Panel of the Medical Research Council. His research focuses on the development and application of statistical methods to the biomedical and health sciences.

• Introduction. Preliminary Testing. Methods for Sparsely Sampled Patterns. Spatial Point Processes. Nonparametric Methods. Models. Model-Fitting Using Summary Descriptions. Model-Fitting Using Likelihood-Based Methods. Point Process Methods in Spatial Epidemiology. Spatio-Temporal Point Processes. Exploratory Analysis. Empirical Models and Methods. Mechanistic Models and Methods. References.

"… a valuable addition to the existing literature as it covers a number of topics in point pattern analysis, ranging from the basics of spatial point pattern statistical analysis to more recent developments in the spatio-temporal context. A number of examples are discussed throughout the chapters, which should facilitate the reading for practitioners of applied statistics from various disciplines. Besides this, the fact that data sets and R codes are available online certainly constitutes a nice addition to this application-oriented textbook."—Mathematical Reviews, January 2015"… well written, concise, and handy. … there are remarkable changes in fundamentals [in this edition]. … All concepts are well illustrated using interesting examples. … an excellent introduction to point process statistics, in particular for beginners."—Biometrical Journal, 2014

Peter Diggle is a Distinguished University Professor and group leader of CHICAS at Lancaster University. Dr. Diggle is also an adjunct professor of biostatistics at both Johns Hopkins University’s and Yale University’s Schools of Public Health, adjunct senior researcher in the International Research Institute for Climate and Society at Columbia University, professor of epidemiology and statistics at the University of Liverpool, a trustee for Biometrika, founding co-editor and advisory board member for Biostatistics, and chair of the Strategic Skills Fellowships Panel of the Medical Research Council. His research focuses on the development and application of statistical methods to the biomedical and health sciences.

• Introduction. Preliminary Testing. Methods for Sparsely Sampled Patterns. Spatial Point Processes. Nonparametric Methods. Models. Model-Fitting Using Summary Descriptions. Model-Fitting Using Likelihood-Based Methods. Point Process Methods in Spatial Epidemiology. Spatio-Temporal Point Processes. Exploratory Analysis. Empirical Models and Methods. Mechanistic Models and Methods. References.

"… a valuable addition to the existing literature as it covers a number of topics in point pattern analysis, ranging from the basics of spatial point pattern statistical analysis to more recent developments in the spatio-temporal context. A number of examples are discussed throughout the chapters, which should facilitate the reading for practitioners of applied statistics from various disciplines. Besides this, the fact that data sets and R codes are available online certainly constitutes a nice addition to this application-oriented textbook."—Mathematical Reviews, January 2015"… well written, concise, and handy. … there are remarkable changes in fundamentals [in this edition]. … All concepts are well illustrated using interesting examples. … an excellent introduction to point process statistics, in particular for beginners."—Biometrical Journal, 2014

Peter Diggle is a Distinguished University Professor and group leader of CHICAS at Lancaster University. Dr. Diggle is also an adjunct professor of biostatistics at both Johns Hopkins University’s and Yale University’s Schools of Public Health, adjunct senior researcher in the International Research Institute for Climate and Society at Columbia University, professor of epidemiology and statistics at the University of Liverpool, a trustee for Biometrika, founding co-editor and advisory board member for Biostatistics, and chair of the Strategic Skills Fellowships Panel of the Medical Research Council. His research focuses on the development and application of statistical methods to the biomedical and health sciences.

• Introduction. Preliminary Testing. Methods for Sparsely Sampled Patterns. Spatial Point Processes. Nonparametric Methods. Models. Model-Fitting Using Summary Descriptions. Model-Fitting Using Likelihood-Based Methods. Point Process Methods in Spatial Epidemiology. Spatio-Temporal Point Processes. Exploratory Analysis. Empirical Models and Methods. Mechanistic Models and Methods. References.

"… a valuable addition to the existing literature as it covers a number of topics in point pattern analysis, ranging from the basics of spatial point pattern statistical analysis to more recent developments in the spatio-temporal context. A number of examples are discussed throughout the chapters, which should facilitate the reading for practitioners of applied statistics from various disciplines. Besides this, the fact that data sets and R codes are available online certainly constitutes a nice addition to this application-oriented textbook."—Mathematical Reviews, January 2015"… well written, concise, and handy. … there are remarkable changes in fundamentals [in this edition]. … All concepts are well illustrated using interesting examples. … an excellent introduction to point process statistics, in particular for beginners."—Biometrical Journal, 2014