Types of point pattern analysis

1. What is point pattern analysis used for?
2. What are the three common distributions encountered in point pattern analysis?
3. What is spatial point pattern analysis?
4. What is a pattern analysis?

What is point pattern analysis used for?

Point pattern analysis (PPA) focuses on the analysis, modeling, visualization, and interpretation of point data. With the increasing availability of big geo-data, such as mobile phone records and social media check-ins, more and more individual-level point data are generated daily.

What are the three common distributions encountered in point pattern analysis?

Commonly, spatial point pattern analysis is used to measure how individuals are located with respect to each other over the horizontal space within a region of interest. There are three fundamental spatial point patterns: complete spatial randomness (CSR), regularity and clustering.

What is spatial point pattern analysis?

Spatial point-pattern analysis has a long history in plant ecology and is based on a large set of test statistics known as summary statistics (Perry et al. 2006). They aim to evaluate and describe statistical properties and spatial structure of point patterns (Wiegand and Moloney 2014).

What is a pattern analysis?

Definition. Pattern analysis is an approach to neuropsychological test interpretation in which relationships among test scores are used to inform differential diagnosis.