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Highlights from
Estimation for Hidden Processes

• (YX(1:(n-1)) + YX(2:n))*dX'/2... This is part of the package EstimHidden devoted to the estimation of
• CoefConv(W0,Dtab,M,s0,FTtrue) if FTtrue==0 compute empirical Fourier Transform
• DeconvCtr(wname,D,M,s02) % This is part of the package EstimHidden devoted to the estimation of
• DeconvEstimate(Z,W0,s0,Y) % This is part of the package EstimHidden devoted to the estimation of
• DeconvOrd(estimate,a) estimate defines an estimate model for the density (and regression) pb
• DeconvPen(Wname,s2,Dtab,n) Wname : type of the known noise
• DeconvPenCtr(D,wname,s02,M,c)
• DeconvSimul(name,n,W0,s0,B,s) Draw random observations for
• FTempiric(X,Z,Y) Fourier transform of the empirical data Z
• FTlogchi2(X,sigma2) Fourier transform of the log of the square of a N(0,1)
• FTnormal(X,sigma2) Fourier transform of the N(0,sigma2)
• FTsymexp(X,sigma2) Fourier transform of the symetric exponential
• GARCH(n,alpha,beta,stat)
• SinCardBasis(D,coef,X)
• drift(x,name)
• mcgama(x,y,kf) This program is an adaptation (by Yves) from the direct conversion of the
• normal(sigma,n,p)
• symexp(sigma,n,p)
• volatility(x,name)
• ExampleDensity.m
• ExampleRegression.m
• ReadMe.m
• View all files