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Abstract
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The methods of estimation of nonparametric regression function are quite in statistical application.
Using wavelets is one of ways of estimating regression. In this paper, the new mixture prior distri-
butions and new bayesian wavelet thresholding estimator of nonparametric regression function are
considered. We used the reversible jump algorithm to obtain the appropriate prior distributions and
value of thresholding . We surveyed theoretical outcomes with numerical computation and simulation
by using R software based on real data. At the end, we compare convergence ratio of given estimator
with another by evaluate of average mean square error.
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