找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Wavelets and Statistics; Anestis Antoniadis,Georges Oppenheim Book 1995 Springer-Verlag New York 1995 Gaussian process.Hypothese.Markov ra

[復(fù)制鏈接]
61#
發(fā)表于 2025-4-1 05:53:37 | 只看該作者
Discretized Wavelet Density Estimators for Continuous Time Stochastic Processes,ch are satisfied for rather general diffusion processes, the. . error of the linear wavelet estimator of. constructed from the observation . converges with the rate . when . In this work we study two discretized versions of this estimator, constructed from the dicrete observations . We show that the
62#
發(fā)表于 2025-4-1 07:24:47 | 只看該作者
63#
發(fā)表于 2025-4-1 10:47:15 | 只看該作者
64#
發(fā)表于 2025-4-1 16:51:50 | 只看該作者
65#
發(fā)表于 2025-4-1 20:57:01 | 只看該作者
66#
發(fā)表于 2025-4-2 02:42:19 | 只看該作者
Choice of the Threshold Parameter in Wavelet Function Estimation, data. The choice of threshold is crucial to the success of the method and is currently subject to an intense research effort. We describe how we have applied the statistical technique of cross-validation to choose a threshold and we present results that indicate that its performance for correlated
67#
發(fā)表于 2025-4-2 03:29:02 | 只看該作者
Choice of the Threshold Parameter in Wavelet Function Estimation, data. The choice of threshold is crucial to the success of the method and is currently subject to an intense research effort. We describe how we have applied the statistical technique of cross-validation to choose a threshold and we present results that indicate that its performance for correlated
68#
發(fā)表于 2025-4-2 08:23:43 | 只看該作者
The Stationary Wavelet Transform and some Statistical Applications,useful subsequently in the paper. A ‘stationary wavelet transform’, where the coefficient sequences are not decimated at each stage, is described. Two different approaches to the construction of an inverse of the stationary wavelet transform are set out. The application of the stationary wavelet tra
69#
發(fā)表于 2025-4-2 11:57:17 | 只看該作者
70#
發(fā)表于 2025-4-2 18:05:01 | 只看該作者
Wavelet Thresholding: Beyond the Gaussian I.I.D. Situation, of these applications are based on. of the empirical coefficients. For regression and density estimation with independent observations, we establish joint asymptotic normality of the empirical coefficients by means of strong approximations. Then we describe how one can prove asymptotic normality un
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評(píng) 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-11 23:03
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
白银市| 巴彦县| 南平市| 商南县| 荔浦县| 子洲县| 鱼台县| 中宁县| 安丘市| 柞水县| 三河市| 儋州市| 温宿县| 富阳市| 宜昌市| 竹北市| 闻喜县| 营山县| 祥云县| 西青区| 德安县| 登封市| 惠州市| 瑞丽市| 德保县| 万盛区| 黔西县| 温宿县| 广州市| 蒙自县| 高淳县| 镶黄旗| 晋江市| 广饶县| 瑞丽市| 桂东县| 新野县| 开原市| 山阴县| 景德镇市| 永州市|