Displaying 3 results from an estimated 3 matches for "continuus".
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2000 May 04
0
About Omega in pda()
...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 eve...
2012 Jul 19
1
Change log(J) to log(J+1) to stop log(0) from occurring in harModel
...uot;ABDJumptest" ){
TQ = apply.daily(data, TQfun);
J = J[,1];
teststats = ABDJumptest(RV=RM1,BPV=RM2,TQ=TQ );
}else{ jtest = match.fun(jumptest); teststats = jtest(data,...) }
Jindicators = teststats > qnorm(1-alpha);
J[!Jindicators] = 0;
# Get continuus components if necessary RV measures if necessary:
Cmatrix = matrix( nrow = dim(RVmatrix1)[1], ncol = 1 );
Cmatrix[Jindicators,] = RVmatrix2[Jindicators,1]; #Fill with
robust one in case of jump
Cmatrix[(!Jindicators)] = RVmatrix1[(!Jindicators),1]; #Fill with
non-robust on...
2012 Jul 19
1
Switching log(J) to log(J+1) to avoid log(0) in HAR-RVJ model
...="ABDJumptest" ){
TQ = apply.daily(data, TQfun);
J = J[,1];
teststats = ABDJumptest(RV=RM1,BPV=RM2,TQ=TQ );
}else{ jtest = match.fun(jumptest); teststats = jtest(data,...) }
Jindicators = teststats > qnorm(1-alpha);
J[!Jindicators] = 0;
# Get continuus components if necessary RV measures if necessary:
Cmatrix = matrix( nrow = dim(RVmatrix1)[1], ncol = 1 );
Cmatrix[Jindicators,] = RVmatrix2[Jindicators,1]; #Fill with
robust one in case of jump
Cmatrix[(!Jindicators)] = RVmatrix1[(!Jindicators),1]; #Fill with
non-robust one...