Estimation for Hidden Processes: symexp(sigma,n,p) - File Exchange

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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
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from Estimation for Hidden Processes by Yves Rozenholc
Nonparametric estimation of density, regression or variance functions for hidden processes using mod

symexp(sigma,n,p)
function X = symexp(sigma,n,p) if nargin<3, p=1; end; X = exprnd(1/sqrt(2),n,p); X = sign(rand(size(X))-0.5).X; X = sigmaX;

Highlights from Estimation for Hidden Processes

Highlights from
Estimation for Hidden Processes