Improved variance estimation along sample eigenvectors
نویسندگان
چکیده
Second order statistics estimates in the form of sample eigenvalues and sample eigenvectors give a sub optimal description of the population density. So far only attempts have been made to reduce the bias in the sample eigenvalues. However, because the sample eigenvectors differ from the population eigenvectors as well, the population eigenvalues are biased estimates of the variances along the sample eigenvectors. Therefore correction of the sample eigenvalues towards the population eigenvalues is not sufficient. The experiments in this paper show that replacing the sample eigenvalues with the variances along the sample eigenvectors often results in better estimates of the population density than replacing the sample eigenvalues with the population eigenvalues.
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