smoothing with Gaussian Kernel for loop problem

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im having a probelm with smoothing the data "ys" using gaussian kernel function everytime i run the for loop i recieve uhat = ys and kerf = 0 0 0 0 0 ... anyone can help me?
ns =length(ys);
nv =length(tv);
lambda = 0.05;
tv = (1:1:1000)';
for i = 1 : ns
k=(tv-tv(i));
kerf=exp(-k.*k/2*(lambda^2))/(sqrt(2*pi)*lambda);
uhat(i)=sum(kerf.*ys(i))/sum(kerf);
end

采纳的回答

Mathieu NOE
Mathieu NOE 2022-11-18
hello
try this
lambda = 0.05;
tv = (1:1:1000)';
nv =length(tv);
ys = sin(4*pi*tv./max(tv))+0.25*rand(nv,1);% dummy data
for i = 1 : nv
k=(tv-tv(i));
kerf=exp(-k.*k/2*(lambda^2))/(sqrt(2*pi)*lambda);
uhat(i)=sum(kerf(:).*ys(:))/sum(kerf);
end
plot(tv,ys,tv,uhat);
  8 个评论
KHOULOUD DABOUSSI
KHOULOUD DABOUSSI 2022-11-21
by chance,do you have any idea how to select the optimal bandwidth (lambda)? not using ksdensity?
Mathieu NOE
Mathieu NOE 2022-11-22
hello again
well, statistics are not my field of expertise
there are some publications that describe some methods for optimal tuning of lambda
but then i's up to you to code that as a matlab function (would basically be your own version of ksdensity)

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