File Exchange

image thumbnail

Nonstationary Extreme Value Analysis (NEVA) Toolbox

version 2.0.0.0 (5.2 MB) by HRL
Nonstationary Extreme Value Analysis (NEVA)

13 Downloads

Updated 20 Aug 2015

View License

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: http://amir.eng.uci.edu/publications/14_NEVA_CC.pdf
The toolbox includes a sample observation and simulation data sets. Run NEVA.m to see sample outputs.
Additional information:
http://amir.eng.uci.edu/neva.php

Comments and Ratings (6)

wave_buoys

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!

xy

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

HRL

Dear Royalos, trendpa.m is added to NEVA_GEV.

Royalos

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

Updates

2.0.0.0

The updated version of NEVA is faster and more efficient.

1.8.0.0

The input data file and trendpa.m are updated.

1.7.0.0

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

1.6.0.0

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

1.5.0.0

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

1.4.0.0

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

1.3.0.0

Toolbox Check-box Removed.

1.2.0.0

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

1.1.0.0

Toolbox check box removed

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

NEVA/NEVA_GEV/

NEVA/NEVA_GPD/