Spatial Modelling for Data Scientists
data-science
r
book
maps
cross-validation
spatial-analysis
multilevel-models
r-spatial
geographically-weighted-regression
spatial-econometrics
moran-i
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Apr 19, 2024 - TeX
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moran-i
Here are 11 public repositories matching this topic...
Course: Introduction to Geographic Data Science
mapping
spatial-data-analysis
rspatial
geographic-data-science
spatial-weights
spatial-econometrics
moran-i
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Updated
Aug 3, 2022 - HTML
Script do meu projeto de conclusão de curso no MBA em Data Science e Analytics pela USP/Esalq.
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Oct 12, 2023 - R
A basic tutorial on implementing Moran's I analysis in R
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Nov 15, 2019 - HTML
The study employs Moran’s I statistic and Local Indicators of Spatial Association (LISA) to analyze spatial patterns and dependencies in housing prices across U.S. counties.
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Jan 5, 2024 - Jupyter Notebook
Classifying Travel Mode choice in the Netherlands using KNN, XGBoost, RF and TabNet
travel
geospatial-data
spatial-data
lime
oversampling
undersampling
random-forest-classifier
explainable-ai
knn-algorithm
spatial-autocorrelation
shap
optuna
weight-matrix
tabnet
xgboost-classifier
moran-i
train-validation-test
mode-choice
smote-tomek
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Updated
May 20, 2024 - Jupyter Notebook
Create variograms, krige, and generate correlograms by utilizing gstat and spdep!
automation
spatial-analysis
kriging
variograms
correlogram
moran-i
kriging-models
kriging-simulations
variogram-clustering
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Apr 10, 2024 - R
Analysis of spatial distribution of income in Italy
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May 6, 2022 - R
Lattice Data with R (City of Cape Town)
autocorrelation
lattice
spatial-data-analysis
weight-matrix
moran-i
ordinary-least-square-regression
geographic-weighted-regression
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Updated
Sep 26, 2023 - Jupyter Notebook
R code for spatial correlogram analysis. Expanded functionality for binning pairs into distances lags, calculating autocorrelation coefficients (via spdep and vegan), and plotting correlograms. Beta 0.1
lag
bin
moran-i
geary-autocorrelation-descriptors
plot-correlograms
mantel-correlogram
plot-pair-counts
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Updated
Aug 6, 2024
The dataset records the total number of road traffic accidents in each state for the given period, categorizing the accidents into fatal, severe, and minor incidents. This comprehensive dataset is valuable for analyzing trends and patterns in road safety across the country, helping to identify regions with higher accident incidences.
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Aug 23, 2024
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