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Homogeneity test of Global Trends using Chi-Square on Mann-Kendall

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Homogeneity test of Global Trends using Chi-Square on Mann-Kendall

by Jeff Burkey

 

14 Dec 2008 (Updated 19 Feb 2009)

Test for homogeneity of trends in different seasons-stations,and global trends using Chi-Square.

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Description

GlobalTrends- Homogeneity tests for multiple seasons and stations. This function will test for trends when seasonality is present and over multiple observation stations, all of which are Chi-square statistics. There are so many statistical tests being done, this function is more like a script or program than a function, but I prefer operating with functions.

This function relies heavily on Matlab's Statistical Toolbox for obtaining Chi-square values and ktaub.m function.

These tests will allow for ties, missing data, and multiple observations per time index, since it uses the enhanced ktaub.m function that was recently updated.

There are numerous narratives as part of the output to the screen providing supporting interpretation of the results.

This function is based on Chapter 17.5 in Gilbert.

Syntax:
      [ChiOutput K M sig] = GlobalTrends( datain, alpha )

Inputs:
To stay consistent with the previous trend statistics posted (ktaub, sktt, and SenT), data are expected to be in the following structure:
       datain(:,1) = Year
       datain(:,2) = season
       datain(:,3) = value
       datain(:,4) = station
       alpha = scaler (e.g. 0.05)

Outputs:
   ChiOutput structure is like the following (labels are not included)
        Total: Chi-square df p-value
        Homogeneity: Chi-square df p-value
        Season: Chi-square df p-value
        Station: Chi-square df p-value
        Station-Season: Chi-square df p-value
        Trend: Chi-square df p-value
    
And depending on significances of Stations, Seasons, and StationSeasons, one of three other outpus may occur:
        K: significance of Seasons per station
        M: significance of Stations for seasons

 And when seasonal trend tests should not be done
        sig: individual station-season p-values are given by row

There is a lot of output to the screen as well, but using fprintf, one could easily redirect output to a file.
    Requirements
       - Matlab Statistical Toolbox
       - ktaub.m

Reference:
      Richard O. Gilbert, Pacific Northwest National Laboratories,
      "Statistical methods for Environmental Pollution Monitoring", 1987, Van Nostrand Reinhold, New York Publishing, ISBN 0-442-23050-8.

One last note. I’ve posted enough functions that it makes sense to constitute forming a Matlab toolbox…so it’s in the works (slowly).

    Written by:
      Jeff Burkey
      King County- Department of Natural Resources and Parks
      email: Jeff.Burkey@kingcounty.gov
      12/13/2008

Required Products Statistics Toolbox
MATLAB release MATLAB 7.7 (R2008b)
Other requirements ktaub.m
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Comments and Ratings (1)
19 Feb 2009 Jeff Burkey

I've included a MAT file with example data to run the function. I hope this helps.

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Updates
08 Jan 2009

Updated description text. Data are not required to be linear per se, but formated like time-series. Up comming is a Log-person Type III function (aka USGS 17B) flood fequency analysis. Also, I've posted enough functions that a toolbox is coming.

05 Feb 2009

Updated Title to be more descriptive.

19 Feb 2009

I've gotten a couple of inquiries asking for an example dataset to use. I've added an example MAT file along with the m-file.

Tag Activity for this File
Tag Applied By Date/Time
statistics Cristina McIntire 15 Dec 2008 15:23:43
probability Cristina McIntire 15 Dec 2008 15:23:43
homogeneity Cristina McIntire 15 Dec 2008 15:23:43
season Cristina McIntire 15 Dec 2008 15:23:43
hydrology Cristina McIntire 15 Dec 2008 15:23:43
homogeneity Jeff Burkey 15 Dec 2008 15:23:52
statistics Jeff Burkey 15 Dec 2008 15:23:52
trends Jeff Burkey 15 Dec 2008 15:23:52
global trends Jeff Burkey 15 Dec 2008 15:23:52
mannkendall Jeff Burkey 15 Dec 2008 15:23:52
hydrology Jeff Burkey 15 Dec 2008 15:23:52
chisquare Jeff Burkey 15 Dec 2008 15:23:52
season Jeff Burkey 15 Dec 2008 15:23:52
climate Jeff Burkey 15 Dec 2008 15:23:52
chi Jeff Burkey 15 Dec 2008 15:23:53
probability Jeff Burkey 15 Dec 2008 15:23:53
homogeneity Isabella Osetinsky 05 Dec 2010 06:33:13
chi Isabella Osetinsky 05 Dec 2010 06:33:29
chisquare Isabella Osetinsky 05 Dec 2010 06:33:52
climate Isabella Osetinsky 05 Dec 2010 06:33:56
global trends Isabella Osetinsky 05 Dec 2010 06:34:01
hydrology Isabella Osetinsky 05 Dec 2010 06:34:06

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