{"name": "Multicollinearity Test", "package_name": "multicollinearity_test", "description": "This plugin can calculate the Pearson correlation coefficient (r) to identify variables that exhibit multicollinearity", "about": "This plugin serves as a tool for calculating the level of multicollinearity among variables used in raster format (TIF or ASC). Users can select the category of absolute r values to be used. The results are presented in CSV format, containing the correlation values between variables. This plugin automatically aligns raw rasters and filters out NoData/NaN values directly, which may result in slight variations in correlation compared to previously manually processed datasets due to resampling effects and floating-point precision.", "homepage": "https://github.com/muhammad-parif/multicollinearity_test", "repository": "https://github.com/muhammad-parif/multicollinearity_test.git", "tracker": "https://github.com/muhammad-parif/multicollinearity_test/issues", "author": "Muhammad Parif", "tags": ["python", "forest", "multicollinearity", "raster"], "downloads": 20, "latest_version": "0.0.6", "versions": [{"version": "0.0.6", "experimental": false, "qgis_min": "3.0.0", "qgis_max": "3.99.0", "downloads": 20, "uploaded_by": "muhammad-parif", "upload_datetime": "2026-09-05T04:20:31.873875"}]}