Comments and Ratings

I might point out that this is identical to what the already existing function consolidator does. In addition, consolidator allows a tolerance for floating point data.

http://www.mathworks.com/matlabcentral/fileexchange/8354

What are the units for Sen's slope for a time series with annual observations?

You shouldn’t need to modify the function to not input the “xdata”. If you don’t input it, the function will perform just not that task. If that is the case, don’t specify the “xy” as part of your output either.

The “dataout” variable contains the predicted y for each x- value supplied in the “datain” variable. The “xdata” is if you want a different set of y-predictions using the lowess function for other x-data not provided in the “datain” variable.

I don’t remember if the function I posted sorts or not, but if you are wanting to regress as a function of time, you may not want to sort.

I hope this helps.

- Jeff

Fantastic! Worked perfectly the first time. I did modify it just a bit to fit my purposes by suppressing the screen output and only returning the dataout variable, since don't want to plot the confidence limits. Thanks for the contribution.

- Jeff

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

I've updated the zip file to include an example mat file (ex1) and forgo the need for people to extract out a sample dataset from the example.mat file. I hope this helps, and expedite any need to fix a problem should it arise.

When I run the ex1 file, created as you specify from the examples.mat file, I get the same message as the previous post:

>>b17(ex1, .590537, 'c:\temp\test.png', 'Demo Station',1)

??? In an assignment A(I) = B, the number of elements in B and
 I must be the same.

Error in ==> b17>freqCurve at 444
        K(i) = lagrange([g k], G, 4);

Error in ==> b17 at 292
    [K floodfreq Gzero] = freqCurve(Xmean, S, G, ktable);

Any resolution to this issue?

Thanks
Greg

K R,
Hmm...not sure why you're getting unequal numbers. Assuming you open the example.mat file so it shows in your Workspace, then run these next for lines exactly:
  ex1 = examples(~isnan(examples(:,2)),1:2);
  ex2 = [examples(~isnan(examples(:,3)),1) examples(~isnan(examples(:,3)),3)];
  ex3 = [examples(~isnan(examples(:,4)),1) examples(~isnan(examples(:,4)),4)];
  ex4 = [examples(~isnan(examples(:,5)),1) examples(~isnan(examples(:,5)),5)];

Then run the function again pointing to either: ex1, ex2, ex3, or ex4. I hope this helps. Email me directly if you need more help. Regards,
jeff.

Sorry about that. It's more for legacy work done in the past, and I probably should take it out. I was working on a project where we were running hundreds of variants of metrics and differentiating by name gets messy, hence using a database to track which statistic was used. - Jeff

The program seems quite nice.
The latest version you download (4 July 2008) still doesn't have the correction to make s = S for small data sets.
I would like to make the taub calculation on a data set of length 8000. Unfortunately I keep getting the OUT OF MEMORY error. Any suggestions on this (besides the automatic suggestions Matlab gives - I've tried all of those).
One possibility - I've made a ktaub-a function which works quite quickly which is nice. I only have a handful of equal values for one of my 2 data sets - and when I perform the Matlab calculation [R,TIEADJ]=TIEDRANK(datain,1) I get

TIEADJ = 8 0 144

and this is also in a quick time.

Does anyone know how I can use these adjustment values for ties required in the
computation of Kendall's tau-b, as the Matlab documentation says? I cannot find any further documentation on it.

Thanks - and much appreciated, in advance.

Nick

Till Ruprecht(till.ruprecht@nexgo.de)
Is there an improvement in the code for the
large time series. if there is i will invaluably thank you for the improvement for a phd study of one of my friends i need this .
thanks in advance.

It works! This has saved me an hour or two of my life so thanks very much.

It would be excellent except I didn't find the comments that easy to follow. What is going on with this:

    % Set metric id for optional use. This is arbitrarily set to 1001
    % for this metric and used in other applications not associated to this
    % function. The user can either ignore or remove from the function.

?

Maybe it is just me being dim but I couldn't work out the point of that.

Thanks again for posting this.

I appologize. I did not see this comment until today (May 22, 2008). After conversing with Dr. Zhi, we agreed that the discrepancy was with the adjustments to S based on data set size. While my code adjusts S when n <= 10, it should adjust S when n >= 10. I also did note that many of the statistic packages out there adjust S regardless of dataset size (users choice at that point). This error does affect Z and p (at about the 3 significant digits or smaller). The correction has be uploaded. It should be live in a day or two. - Jeff (author)

I would like to thank everyone that has commented. I'm close to the seasonal kendall, homogeneity, global trend, others. I'm in the process of validating the code for the statistics. - Jeff (author)

It's great that it works without loops. Besides, now that W Vista allows to add RAM with flash-drives, the memory issue mentioned above does not seem such a problem. I'm excited about seeing the seasonal version of it.

Very simple and straightforward.
Easy to use.

Dear Jeff Burkey,
thank you for providing a Mann-Kendall-algorithm based on Matlab.
A disadvantage of the algorithm obviously
is, that for large time series (i.e. 25.0000 units) the ram gets out of memory easily.
(In the example 25.000 x 25.000 x 8Byte (Double Precision) = 5 GB are required to store the replicated matrix). It would be great, having a alternative algorithm in
your method, taking into account the size
of the input data.

Greetings