Eikosstatistics & data science

Advanced & Applied Topics · Spatial Statistics & Geostatistics

Spatial Statistics: Spatial Point Patterns

Public introduction · full guide in Eikos

Introduction

What this guide covers

Introduction Introduction Spatial Statistics and Stochastic Processes

Overview

Topics covered

  • Introduction
  • Point Pattern Theory in the Plane
  • Space Point Pattern Fundamentals
  • The Spatial Point Process as a Random Measure
  • The Complete Spatial Randomness (CSR) Hypothesis
  • The Inhomogeneous Poisson Process (IPP)

Related concepts

Main connections

  • Poisson distribution
  • Maximum likelihood estimation
  • Calculus & differentiation
  • Variance & standard deviation
  • Residual analysis & diagnostics
  • Conditional probability & independence

Compatible notation

Mathematical sample in LaTeX

The expression is rendered accessibly, with its LaTeX source preserved below.

P(N(B)<∞)=1YP(∃x∈W:N({x})>1)=0
View LaTeX sourceP\big(N(B) < \infty\big) = 1 \qquad \text{Y} \qquad P\big(\exists\, x \in W : N(\{x\}) > 1\big) = 0