Spatial Point Patterns: Methodology and Applications with R
نویسندگان
چکیده
منابع مشابه
Modelling Spatial Point Patterns in R
This paper describes practical techniques for fitting stochastic models to spatial point pattern data using the statistical language R. The techniques are demonstrated with a detailed analysis of two real datasets. We have implemented the techniques as a package spatstat in the R language. Both spatstat and R are freely available from the R website [19]. Sections 2 and 3 introduce the spatstat ...
متن کاملspatstat: An R Package for Analyzing Spatial Point Patterns
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 gen...
متن کاملSpatial Point Patterns
In looking at ecological processes, interest in the pattern of occurrences of species, e.g., the pattern of trees in a forest, say junipers and pinions. In spatial epidemiology, we seek to find pattern in disease cases, perhaps different patterns for cases vs. controls. Exple: breast cancer cases; treatment option mastectomy or radiation In syndromic surveillance we seek to identify disease out...
متن کاملMultitype spatial point patterns with hierarchical interactions.
Multitype spatial point patterns with hierarchical interactions are considered. Here hierarchical interaction means directionality: points on a higher level of hierarchy affect the locations of points on the lower levels, but not vice versa. Such relations are common, for example, in ecological communities. Interacting point patterns are often modeled by Gibbs processes with pairwise interactio...
متن کاملSpatial Point Processes and their Applications
A spatial point process is a random pattern of points in d-dimensional space (where usually d = 2 or d = 3 in applications). Spatial point processes are useful as statistical models in the analysis of observed patterns of points, where the points represent the locations of some object of study (e..g. trees in a forest, bird nests, disease cases, or petty crimes). Point processes play a special ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Statistical Software
سال: 2016
ISSN: 1548-7660
DOI: 10.18637/jss.v075.b02