Thanks for your quick reply. It was helpful. Now I understand. We need to get the LN-mean and LN-standard-deviation in order to get the mean ('mu') and standard deviation ('sqrt(si2)' ) from LNRVs.
Dear Prof. Antonio Trujillo-Ortiz,
Thanks for your quick reply. It was helpful. Now I understand. We need to get the LN-mean and LN-standard-deviation in order to get the mean ('mu') and standard deviation ('sqrt(si2)' ) from LNRVs.
Thank you very much/Muchos gracias,
Mike
Dear Michael,
Thanks for your interest of this m-file. As you know, we only generated the Matlab computational algorithm from the original published paper. If you have any mathematical or statistical fundamentals inquiry you must refer to the author(s). I give you the Dr. Norbert Henze's email address
henze@stoch.uni-karlsruhe.de
and/or
N.Henze@math.uni-karlsruhe.de
However, we don't need the lognormal cdf (logncdf) neither the mean and variance of the lognormal distribution (longnstat) functions. For the used mean (mu) and variance (si2), which are the Henze-Zirkler mean and variance, must, as the author establish, to be converted to the lognormal Henze-Zirkler mean and variance. As you can see, using the provied Iris data example. The mean(mu)=0.7635 and variance(si2)=0.0112. With a Henze-Zirkler lognormal mean: -0.279408 and Henze-Zirkler lognormal variance: 0.1379069. But, if you try to use te mu and si2 values by the longnstat function, you get the incorrect lognormal values of 2.1459 and 5.7768e-004, respecively.
Yours,
Prof. Antonio Trujillo-Ortiz
Dear Sir Antonio,
Could you explain/describe the mean and standard deviation arguments to the Log normal cdf? Why not use 'mu' and 'sqrt(si2)' directly?
Thanks/Gracias,
Mike
Nice implemetation and sample data to test the file on. However, it runs a bit slow. I recompted the variable Djk by avoiding loops and it runs much faster:
Djk = - 2*Y' + diag(Y')*ones(1,n) + ones(n,1)*diag(Y')';
/J.D.
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