** High Priority **
Hello R users
My issue is both theorical and technical.
I would like to run a penalised discriminant analysis with the fda() function,
but I don''t know all the details of splines theory.
I try on the example of the phonems from the article "Penalised
Discriminant Analysis" of Hastie, Buja and Tibshirani 1994 : 5 groups and
256 variables.
The 256 variables are from the discretisation of log-periodogram. Consequently,
we want the scores to be smoothed by the frequency.
in continuus writing, J(beta)= integral of the square second derivative of beta
upon the frequencies
and J(beta)=(beta)^T*OMEGA*beta
No function for producing one dimensional penalty object is providing with
gen.ridge function..
What is the best (and more efficient) function to use to fit OMEGA ? I have ever
tried to use the function ssanova in the gss package but the solution of my
program is not symetrical : I am definitly wrong in my approach.
Thank you in advance for the users of mda package that would answer me.
Damien Berlemont
student at : DESS Methodes Scientifiques de Gestion - Paris-X Nanterre
Damien.Berlemont at ccf.fr
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