Multinomial probability estimation by wavelet thresholding
Document Type
Article
Publication Date
1-1-2009
Abstract
In this article, we introduce a wavelet threshold estimator to estimate multinomial probabilities. The advantages of the estimator are its adaptability to the roughness and sparseness of the data. The asymptotic behavior of the estimator is investigated through an often-used criteria: the mean sum of squared error (MSSE). We show that the MSSE of the estimator achieves the optimal rate of convergence. Its performance on finite samples is examined through simulation studies which show favorable results for the new estimator over the commonly used kernel estimator.
Publication Title
Communications in Statistics - Theory and Methods
Recommended Citation
Dong, J.,
&
Jiang, R.
(2009).
Multinomial probability estimation by wavelet thresholding.
Communications in Statistics - Theory and Methods,
38(9), 1486-1507.
http://doi.org/10.1080/03610920802455043
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/9228
