شماره ركورد كنفرانس
5191
عنوان مقاله
Wavelet-Based Estimation for Bivariate Density Function Using NSDRandom Variables
پديدآورندگان
Shirazi Esmaeil Faculty of Science, Gonbad Kavous university, Gonbad Kavous, Iran , Ghanbari Bahareh Department of Statistics, Payame noor university, P. O. Box 19395-4697, Tehran, Iran
تعداد صفحه
5
كليدواژه
Bivariate density function , Negatively superadditive dependence , Nonparametricestimation , Wavelets.
سال انتشار
1401
عنوان كنفرانس
شانزدهمين كنفرانس آمار ايران
زبان مدرك
انگليسي
چكيده فارسي
In this paper, we study the asymptotic behavior of the wavelet bivariate density function estimator for a negatively superadditive dependent. The convergence rates for the non-linear wavelet estimator are investigated. We evaluate these theoretical performances via the minimax approach under the Lp risk with p ≥ 1 over a wide range of function classes: the Besov classes. Under mild assumptions on the model, we show that it enjoys powerful mean integrated squared error properties.
كشور
ايران
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