发帖
雷达卡
These workshop notes, written in 2008, cover statistical methods available in public domain software.
The workshop uses the statistical package 'R' and is based on 'spatstat', an add-on library for 'R' for the analysis of spatial data.
Topics covered include:
- statistical formulation and methodological issues
- data input and handling
- R concepts such as classes and methods
- nonparametric intensity estimates
- goodness-of-fit testing for Complete Spatial Randomness
- maximum likelihood inference for Poisson processes
- model validation for Poisson processes
- distance methods and summary functions such as Ripley’s K function
- non-Poisson point process models
- simulation techniques
- fitting models using summary statistics
- Gibbs point process models
- fitting, simulating and validating Gibbs models
- multitype and marked point patterns
- exploratory analysis of marked point patterns
- multitype Poisson process models and maximum likelihood inference
- multitype Gibbs process models and maximum pseudolikelihood
- line segment data.
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