GitHub - NarmadhaMM/Bayesian-ML-for-occupancy-data: Includes the R code and the supporting materials for our paper "Using machine learning to identify nontraditional spatial dependence in occupancy data"

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Includes the R code and the supporting materials for our paper "Using machine learning to identify nontraditional spatial dependence in occupancy data"

arxiv.org/abs/2006.09983

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Name		Name	Last commit message	Last commit date
Latest commit History 1 Commit
Occupancy data.csv		Occupancy data.csv
Readme.txt		Readme.txt
Sampling grid.dbf		Sampling grid.dbf
Sampling grid.prj		Sampling grid.prj
Sampling grid.shp		Sampling grid.shp
Sampling grid.shx		Sampling grid.shx
Serengeti_data_example.R		Serengeti_data_example.R
Synthetic_data_examples.R		Synthetic_data_examples.R

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This Supporting_files folder contains,

The R code for the MCMC algorithm discussed in Appendix A (MCMC.R).
The R code associated with the synthetic data example presented in the manuscript (Synthetic_data_example.R).
The R code associated with the Thomson's gazelle data example presented in the manuscript (Serengeti_data_example.R).
The data and the required shapefiles for Thomson's gazelle data example.

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Includes the R code and the supporting materials for our paper "Using machine learning to identify nontraditional spatial dependence in occupancy data"

arxiv.org/abs/2006.09983

machine-learning-algorithms bayesian spatio-temporal support-vector-regression regression-trees occupancy-modeling bayesian-hierarchical-models

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