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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 (2021). Nonstationary Extreme Value Analysis (NEVA) Toolbox (, MATLAB Central File Exchange. Retrieved .

Comments and Ratings (8)

Andre White

What is the effec variable? It is not defined in the user guide.

John Callahan

Does anybody know where I can find the actual data used to make the return level vs return period plots? Particularly in figure 701, using non-stationary. I'm looking for the 5%, median, and 95% data values. I see various mat files in the saveData folder (like nonsmp) but none look like the values being plotted. Perhaps I need to do some computations on the nonsmp data? Thanks.


Dear HRL,
Thanks for providing this toolbox, but I got this error message below running with Matlab 2018a. Could you please help? Thanks

Operands to the || and && operators must be convertible to logical scalar values.

Error in gevfit (line 74)
if n == 0 || ~isfinite(rangex)

Error in parap (line 5)
paramsg(id,:)= gevfit(DATA(1:Now,id));

Error in NEVA (line 106)
[mu_not,si_not,zi_not]= parap(siteNO,Now,DATA);

Bilal Khan

Great tool!


Alessandro Antonini

It is a great tool, moreover reading the suggested paper everything is quite clear. THANKS!


Dear Royalos, trendpa.m is added to NEVA_GEV.


It is a great tool.However, when I set Nonsta = 1, an error appears that Error in non_GEV (line 10) [mu_not,pcc]= trendpa(si,Now,DATA,mu_not,poly,plottrend). It seems that there is a missing file called trendpa. Please have a check. Thanks

MATLAB Release Compatibility
Created with R2011b
Compatible with any release
Platform Compatibility
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