چکیده مقاله
Here we consider wavelet based identification and estimation of a quantile density function via block thresholding methods and investigate their asymptotic convergence rates We show that these estimators, based on block thresholding of empirical wavelet coefficients, achieve optimal convergence rates over a large range of Besov function classes, and in particular enjoy those rates without the extraneous logarithmic penalties that are usually suffered by term by term thresholding methods
کلیدواژهها
نویسندگان
Esmaeil Shirazi
Department of Statistics, Faculty of Science, Gonbad Kavous University, Gonbad Kavous, Iran
Abdolsaeed Toomaj
Department of Statistics, Faculty of Science, Gonbad Kavous University, Gonbad Kavous, Iran
شیوه ارجاع
Shirazi, Esmaeil and Toomaj, Abdolsaeed,1394,Wavelet-Based Quantile Density Estimation By Block Thresholding Method,1st National Conference on Soft Computing,Rasht
ارائهشده در
مجموعه مقالات نخستین کنفرانس ملی محاسبات نرم27 آبان 1394 · رشت