The commonly used Standardized Precipitation Index (SPI) relies on a representative parametric probability distribution function (e.g., Gamma). However, a parametric distribution function may not fit the data, especially in continental/global scale studies. This code computes SPI based on a nonparametric framework that does not require assuming a representative parametric distribution. The most attractive feature of the framework is that it leads to statistically consistent drought indicators based on different variables. A user guide and sample inpute data are included in the package.
This code is also part of the Standardized Drought Analysis Toolbox (SDAT):
Hao Z., AghaKouchak A., Nakhjiri N., Farahmand A., 2014, Global Integrated Drought Monitoring and Prediction System, Scientific Data, 1:140001, 1-10, doi: 10.1038/sdata.2014.1.
Farahmand A., AghaKouchak A., 2015, A Generalized Framework for Deriving Nonparametric Standardized Drought Indicators, Advances in Water Resources, 76, 140-145, doi: 10.1016/j.advwatres.2014.11.012.
Hao Z., AghaKouchak A., 2014, A Nonparametric Multivariate Multi-Index Drought Monitoring Framework, Journal of Hydrometeorology, 15, 89-101, doi:10.1175/JHM-D-12-0160.1.
HRL (2023). Nonparametric Standardized Precipitation Index (SPI) (https://www.mathworks.com/matlabcentral/fileexchange/51080-nonparametric-standardized-precipitation-index-spi), MATLAB Central File Exchange. Retrieved .
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