PostGeoDa
  • PostGeoDa (beta)
  • 0. πŸ–₯️ Installation
  • 1. πŸ—ΊοΈ Choropleth Mapping
    • 1.1 Basic Mapping
    • 1.2 Rate Mapping
    • 1.3 Spatial Rate Mapping
  • 2. 🌐 Spatial Weights
    • 2.1 Contiguity-Based Weights
    • 2.2 Distance-Based Weights
    • 2.3 Kernel Weights
  • 3. πŸ’  Local Spatial Autocorrelation
    • 3.1 Local Moran
    • 3.2 Local Geary
    • 3.3 Local Getis-Ord G
    • 3.4 Local Join Count
    • 3.5 Quantile LISA
  • 4. πŸ’  Local Spatial Autocorrelation -Multivariate
    • 4.1 Local Neighbor Match Test
    • 4.2 Multivariate Local Geary
    • 4.3 Bivariate Local Join Count
    • 4.4 Multivariate Local Join Count
    • 4.5 Multivariate Quantile LISA
  • 5. 🌌 Spatial Clustering
    • 5.1 SKATER
    • 5.2 REDCAP
  • 6. ✨ Cluster Analysis
    • 6.1 HDBScan
    • 6.2 Fast K-Medoids
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1. πŸ—ΊοΈ Choropleth Mapping

Choropleth maps represent non-geographic attributes on a geographic map. PostGeoDa provides some common thematic map classifications, rate mapping, and spatial rate mapping.

For more information, please read https://geodacenter.github.io/workbook/3a_mapping/lab3a.html https://geodacenter.github.io/workbook/3b_rates/lab3b.html

Contents

  • Basic Mapping

    • Natural Breaks

    • Quantile Breaks

    • Percentile Breaks

    • Hinge Box Breaks

    • Standard Deviation

  • Rate Mapping

    • Excess Risk

    • Empirical Bayes (EB) Smoothed Rate

  • Spatial Rate Mapping

    • Spatially Lagged Variable

    • Spatial Rate

    • Spatial Empirical Bayes (EB) Smoothed Rate

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Last updated 4 years ago

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