找回密碼
 To register

QQ登錄

只需一步,快速開(kāi)始

掃一掃,訪問(wèn)微社區(qū)

打印 上一主題 下一主題

Titlebook: Maximum Penalized Likelihood Estimation; Volume II: Regressio Vincent N. LaRiccia,Paul P.‘Eggermont Book 2009 Springer-Verlag New York 2009

[復(fù)制鏈接]
查看: 43209|回復(fù): 53
樓主
發(fā)表于 2025-3-21 18:41:30 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Maximum Penalized Likelihood Estimation
副標(biāo)題Volume II: Regressio
編輯Vincent N. LaRiccia,Paul P.‘Eggermont
視頻videohttp://file.papertrans.cn/628/627913/627913.mp4
概述Fully develops the theory of convex minimization problems to obtain convergence rates.Includes simulation studies and analyses of classical data sets using fully automatic (data driven) procedures.Man
叢書(shū)名稱Springer Series in Statistics
圖書(shū)封面Titlebook: Maximum Penalized Likelihood Estimation; Volume II: Regressio Vincent N. LaRiccia,Paul P.‘Eggermont Book 2009 Springer-Verlag New York 2009
描述This is the second volume of a text on the theory and practice of maximum penalized likelihood estimation. It is intended for graduate students in s- tistics, operationsresearch, andappliedmathematics, aswellasresearchers and practitioners in the ?eld. The present volume was supposed to have a short chapter on nonparametric regression but was intended to deal mainly with inverse problems. However, the chapter on nonparametric regression kept growing to the point where it is now the only topic covered. Perhaps there will be a Volume III. It might even deal with inverse problems. But for now we are happy to have ?nished Volume II. The emphasis in this volume is on smoothing splines of arbitrary order, but other estimators (kernels, local and global polynomials) pass review as well. We study smoothing splines and local polynomials in the context of reproducing kernel Hilbert spaces. The connection between smoothing splines and reproducing kernels is of course well-known. The new twist is thatlettingtheinnerproductdependonthesmoothingparameteropensup new possibilities: It leads to asymptotically equivalent reproducing kernel estimators (without quali?cations) and thence, via uniform er
出版日期Book 2009
關(guān)鍵詞Confidence bands; Estimator; Kalman filter for smoothing splines; ; Likelihood; Local polynomials; Nonpara
版次1
doihttps://doi.org/10.1007/b12285
isbn_softcover978-1-4614-1712-5
isbn_ebook978-0-387-68902-9Series ISSN 0172-7397 Series E-ISSN 2197-568X
issn_series 0172-7397
copyrightSpringer-Verlag New York 2009
The information of publication is updating

書(shū)目名稱Maximum Penalized Likelihood Estimation影響因子(影響力)




書(shū)目名稱Maximum Penalized Likelihood Estimation影響因子(影響力)學(xué)科排名




書(shū)目名稱Maximum Penalized Likelihood Estimation網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱Maximum Penalized Likelihood Estimation網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱Maximum Penalized Likelihood Estimation被引頻次




書(shū)目名稱Maximum Penalized Likelihood Estimation被引頻次學(xué)科排名




書(shū)目名稱Maximum Penalized Likelihood Estimation年度引用




書(shū)目名稱Maximum Penalized Likelihood Estimation年度引用學(xué)科排名




書(shū)目名稱Maximum Penalized Likelihood Estimation讀者反饋




書(shū)目名稱Maximum Penalized Likelihood Estimation讀者反饋學(xué)科排名




單選投票, 共有 1 人參與投票
 

0票 0.00%

Perfect with Aesthetics

 

1票 100.00%

Better Implies Difficulty

 

0票 0.00%

Good and Satisfactory

 

0票 0.00%

Adverse Performance

 

0票 0.00%

Disdainful Garbage

您所在的用戶組沒(méi)有投票權(quán)限
沙發(fā)
發(fā)表于 2025-3-21 22:09:30 | 只看該作者
Vincent N. LaRiccia,Paul P.‘EggermontFully develops the theory of convex minimization problems to obtain convergence rates.Includes simulation studies and analyses of classical data sets using fully automatic (data driven) procedures.Man
板凳
發(fā)表于 2025-3-22 02:29:19 | 只看該作者
Springer Series in Statisticshttp://image.papertrans.cn/m/image/627913.jpg
地板
發(fā)表于 2025-3-22 08:13:47 | 只看該作者
5#
發(fā)表于 2025-3-22 09:57:04 | 只看該作者
6#
發(fā)表于 2025-3-22 16:06:52 | 只看該作者
7#
發(fā)表于 2025-3-22 18:33:32 | 只看該作者
978-1-4614-1712-5Springer-Verlag New York 2009
8#
發(fā)表于 2025-3-23 01:17:33 | 只看該作者
9#
發(fā)表于 2025-3-23 01:42:08 | 只看該作者
10#
發(fā)表于 2025-3-23 06:32:13 | 只看該作者
Book 2009nection between smoothing splines and reproducing kernels is of course well-known. The new twist is thatlettingtheinnerproductdependonthesmoothingparameteropensup new possibilities: It leads to asymptotically equivalent reproducing kernel estimators (without quali?cations) and thence, via uniform er
 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(ài)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(guó)際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-15 17:56
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
大城县| 南投市| 湟中县| 韩城市| 荣成市| 临泽县| 衢州市| 内江市| 逊克县| 敖汉旗| 冷水江市| 武义县| 宣汉县| 德州市| 南江县| 永年县| 天门市| 陇西县| 富裕县| 修水县| 赫章县| 清原| 鸡东县| 清丰县| 封开县| 旺苍县| 林周县| 巴楚县| 温泉县| 关岭| 宁国市| 信宜市| 晴隆县| 普宁市| 乐至县| 扶沟县| 怀集县| 南京市| 怀宁县| 罗定市| 冷水江市|