Topic
Point pattern analysis
About: Point pattern analysis is a research topic. Over the lifetime, 270 publications have been published within this topic receiving 16347 citations.
Papers published on a yearly basis
Papers
Book•
1 Jan 1983
TL;DR: This book provides an introduction to statistical methods for analysing data in the form of spatial point distributions, described in intuitive terms and illustrated by many applications to real data drawn from the biological and biomedical sciences.
Abstract: A spatial point pattern is a set of data consisting of a map of points These points might represent, for example, cases of a disease in a human or animal population, or trees in a forest, or cells in a microscopic tissue section This book provides an introduction to statistical methods for analysing data in the form of spatial point distributions Theoretical results are described in intuitive terms and statistical methods are illustrated by many applications to real data drawn from the biological and biomedical sciences
3,339 citations
Book•
21 Oct 2008
TL;DR: Hello, world: handling spatial data in R.
Abstract: Hello, world: handling spatial data in R.- Classes for spatial data in R.- Visualizing spatial data.- Spatial data import and export.- Further methods for handling spatial data.- Customising spatial data classes and methods.- Spatial point pattern analysis.- Interpolation and geostatistics.- Areal data and spatial autocorrelation.- Modelling areal data.- Disease mapping.- Afterword.- References.
3,035 citations
TL;DR: This paper is a general description of spatstat and an introduction for new users.
Abstract: spatstat is a package for analyzing spatial point pattern data. Its functionality includes exploratory data analysis, model-fitting, and simulation. It is designed to handle realistic datasets, including inhomogeneous point patterns, spatial sampling regions of arbitrary shape, extra covariate data, and "marks" attached to the points of the point pattern.
A unique feature of spatstat is its generic algorithm for fitting point process models to point pattern data. The interface to this algorithm is a function ppm that is strongly analogous to lm and glm.
This paper is a general description of spatstat and an introduction for new users.
2,573 citations
2,403 citations
Book•
1 Jan 2000
TL;DR: In this article, the role of Geographic Information Systems Exploring Spatial Data Visually Local Analysis Point Pattern Analysis Spatial Regression and Geostatistical Models Statistical Inference for Spatial data Spatial Modelling and the Evolution of Spatial Theory Challenges in SPatial Data Analysis
Abstract: Establishing the Boundaries Spatial Data The Role of Geographic Information Systems Exploring Spatial Data Visually Local Analysis Point Pattern Analysis Spatial Regression and Geostatistical Models Statistical Inference for Spatial Data Spatial Modelling and the Evolution of Spatial Theory Challenges in Spatial Data Analysis
1,101 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2025 | 5 |
| 2024 | 10 |
| 2023 | 18 |
| 2022 | 25 |
| 2021 | 12 |
| 2020 | 13 |