Nonstationary Extreme Value Analysis (NEVA) Toolbox

Version (5.2 MB) by HRL
Nonstationary Extreme Value Analysis (NEVA)
Updated 20 Aug 2015

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Nonstationary Extreme Value Analysis (NEVA) Software Package, Version 2.0
By: Linyin Cheng, PhD, University of California, Irvine
Release: 09/14/2014
Source Code: Matlab
The Nonstationary Extreme Value Analysis (NEVA) software package has been developed to facilitate extreme value analysis under both stationary and nonstationary assumptions. In a Bayesian approach, NEVA estimates the extreme value parameters with a Differential Evolution Markov Chain (DE-MC) approach for global optimization over the parameter space. NEVA includes posterior probability intervals (uncertainty bounds) of estimated return levels through Bayesian inference, with its inherent advantages in uncertainty quantification. The software presents the results of non-stationary extreme value analysis using various exceedance probability methods. We evaluate both stationary and non-stationary components of the package for a case study consisting of annual temperature maxima for a gridded global temperature dataset. The results show that NEVA can reliably describe extremes and their return levels.
NEVA includes two components:
(1) The Generalized Extreme Value (GEV) distribution for analysis of annual maxima (block maxima).
(2) The Generalized Pareto Distribution (GPD) for analysis of extremes above a certain threshold (i.e., peak-over-threshold (POT) approach).
Both NEVA GEV and NEVA GPD can be used for stationary (time-independent) and nonstationary (transient) extreme value analysis.
Reference Publication:
Cheng L., AghaKouchak A., Gilleland E., Katz R.W., 2014, Non-stationary Extreme Value Analysis in a Changing Climate , Climatic Change, doi: 10.1007/s10584-014-1254-5.
Download Reference Paper:
The toolbox includes a sample observation and simulation data sets. Run NEVA.m to see sample outputs.
Additional information:

Cite As

HRL (2024). Nonstationary Extreme Value Analysis (NEVA) Toolbox (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2011b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes

The updated version of NEVA is faster and more efficient.

The input data file and trendpa.m are updated.

Minor Update: The updated version allows parameter estimation using the maximum likelihood method.

Minor Update: The updated version allows parameter estimation using the maximum likelihood method.

Major update: non-GEV, GEV and GPD codes are updated. Sample data is included.

The updated version allows both stationary and nonstationary runs for multiple data sets (e.g., multiple gauges or pixels).

Toolbox Check-box Removed.

'trendpa.m' added to NEVA_GEV;
'profilcS.m' added to NEVA_GPD

Toolbox check box removed