What is the difference between the lines (in meaning):

* expr := expr0 / c;

* mean := int(x * expr, x = interval);

Are they both a numeric value or are they a constant?

What is the difference between the lines (in meaning):

* expr := expr0 / c;

* mean := int(x * expr, x = interval);

Are they both a numeric value or are they a constant?

Thanks! It works well.

Thanks! It works well.

Thanks a lot. I am trying it out...

Thanks a lot. I am trying it out...

Thank you that is much appreciated. I will have a look at it shortly...

Thank you that is much appreciated. I will have a look at it shortly...

@epostma 

Hi Erik,

Thank you for your reply. I have a function on which I want to determine its "peakiness". I was told that Kurtosis is a method I could use for this. I am able to calculate it for numerical data but am unsure for a continuous function.

The thougthts I have for doing it is:

* Calculate the mean (intergrate and divide by length on x-axis)

* Calculate a function that is equal to the standard deviation for each point (using the mean calculated above).

* Use the previous sdv function above to calculate the kurtosos at each point in the form of a continuous function.

You may be interested to see some code I used for numerical data:

        % Calculating Kurtosis
        % where Z is a row, the output is the kurtosis in a row
        Z = cforce(i,:);
        meanZ = sum(Z) / length(Z);
        stdZ = sqrt(sum(Z' * Z) / (length(Z)-1));
        kurtosisZ = ( meanZ.*(Z-meanZ).^4 ) ./ ( stdZ.^4 );
        cf_kur(i,:) = kurtosisZ;

Do you have some ideas how I could do this for a continuous function?

I have found that this function does not always locate the maximum (i.e. by visual observation of 3D graph). Is there any way to correct this or improve its searching by increasing the tolerance? Does anyone have experience with this?

I have found that this function does not always locate the maximum (i.e. by visual observation of 3D graph). Is there any way to correct this or improve its searching by increasing the tolerance? Does anyone have experience with this?

Thanks, that's great!

Thanks, that's great!

Thanks for reply.

I tried it and could not get it going. Maybe it needs with(___)?

I plotted the original function for t=0..20 - can you let me know if you get the fourier transform working and if the plot for omega=0..20 looks similar?

Thanks.

Thanks for reply.

I tried it and could not get it going. Maybe it needs with(___)?

I plotted the original function for t=0..20 - can you let me know if you get the fourier transform working and if the plot for omega=0..20 looks similar?

Thanks.