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鲁棒统计，现代统计方法， Robust Statistics第二版，学习现代统计方法R○ BUST STAT|STCSSecond editionPeter j, huberProfessor of Statistics, retiredKlosters SwitzerlandEⅣ ezio m. RonchettiProfessor of StatisticsUniversity of Geneva, SwitzerlandWILEYA JOHn WileY SONS INC. PUBliCAtIONCopyrightc 2009 by John Wiley Sons, Inc. All rights reservedPublished by John Wiley sons, Inc, Hoboken, New JerseyPublished simultaneously in CanadaNo part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form orby any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except aspermitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the priorwritten permission of the Publisher, or authorization through payment of the appropriate per-copy fee tothe Copyright Clearance Center, Inc, 222 Rosewood Drive, Danvers, MA 01923, (978)750-8400, fax978)750-4470,oronthewebatwww.copyrigom. requests to the publisher for permission shouldbe addressed to the permissions department John Wiley sons, Inc., 11 1 River Street, Hoboken, NJ07030,(201)748-6011,fax(201)748-6008,oronlineathttp:/www.wileycom/go/permissionLimit of Liability /Disclaimer of Warranty: While the publisher and author have used their best efforts inpreparing this book, they make no representations or warranties with respect to the accuracy orcompleteness of the contents of this book and specifically disclaim any implied warranties ofmerchantability or fitness for a particular purpose. No warranty may be created or extended by salesrepresentatives or written sales materials. The advice and strategies contained herein may not be suitablefor your situation. You should consult with a professional where appropriate. Neither the publisher norauthor shall be liable for any loss of profit or any other commercial damages, including but not limitedto special, incidental, consequential, or other damagesFor general information on our other products and services or for technical support, please contact ourCustomer Care Department within the United States at(800)762-2974, outside the United States at(317)572-3993 or fax(317)572-4002.Wiley also publishes its books in a variety of electronic formats. Some content that appears in print maynot be available in electronic format. For information about wiley products, visit our web site atwww.wileycomLibrary of Congress Cataloging-in-Publication Data:Huber Peter JRobust statistics, second edition/ Peter J. Huber, Elvezio ronchettip. cnIncludes bibliographical references and indeISBN978-0-470-12990-6( cloth)1. Robust statistics. I. Ronchetti. elvezio. II. TitleQA276.H7852009519.5-dc222008033283Printed in the United States of america10987654321To the memory o1John w. tukeyThis Page Intentionally Left BlankCONTENTSPrefacePreface to first editionGeneralities1 Why robust Procedures1. 2 What Should a robust procedure achieve?1.2.1 Robust. Nonparametric and Distribution-Free1.2.2 Adaptive procedures1.2.3 Resistant Procedures1.2. 4 Robustness versus Diagnostics1.2.5 Breakdown point1.3 Qualitative Robustness567888911. 4 Quantitative Robustness1.5 Infinitesimal Aspects141.6 Optimal Robustness171.7 Performance Comparisons18CONTENTS1.8 Computation of robust estimates181.9 Limitations to Robustness Theory202 The Weak Topology and its Metrization23eneral remarks232.2 The Weak Topology232.3 Levy and prohorov metrics272.4 The bounded Lipschitz metric322.5 Frechet and Gateaux derivatives366 Hampels Theorem413 The Basic Types of Estimates453. 1 General Remarks453.2 Maximum Likelihood Type Estimates(M-Estimates)3.2.1 Influence Function of m-estimates73.2.2 Asymptotic Properties of M-Estimates483.2.3 Quantitative and Qualitative Robustness of MEstimates3.3 Linear Combinations of Order Statistics(L-Estimates)3.3.1 Influence Function of -Estimates3.3.2 Quantitative and Qualitative robustness of l-Estimates 593. 4 Estimates Derived from Rank Tests(R-estimates3.4.1 Influence Function of R-Estimates623.4.2 Quantitative and Qualitative robustness of R-Estimates 643.5 Asymptotically Efficient M-, L,and R-Estimates674 Asymptotic Minimax Theory for Estimating Location4.1 General remarks4.2 Minimax bias4.3 Minimax Variance: Preliminaries744. 4 Distributions minimizing fisher Information764.5 Determination of Fo by Variational Methods814.6 Asymptotically Minimax M-Estimates914.7 On the minimax Property for L-and R-estimates954.8 Redescending m-estimates74.9 Questions of Asymmetric Contamination101CONTENTSScale Estimates1055.1 General remarks1055.2 M-Estimates of scale1075.3 L-Estimates of scale5.4 R-Estimates of Scale1125.5 Asymptotically efficient Scale estimates1145.6 Distributions Minimizing fisher Information for Scale5.7 Minimax Properties116 Multiparameter Problemsin Particular Joint Estimationof Location and scale1256. 1 General remarks1256.2 Consistency of M-Estimates1266.3 Asymptotic Normality of M-Estimates1306. 4 Simultaneous m-Estimates of Location and scale1336.5 M-Estimates with Preliminary Estimates of Scale1376.6 Quantitative robustness of Joint Estimates of Location and Scale 1396.7 The Computation of M-Estimates of Scale14368Studentizing1457 Regression1497. 1 General remarks1497. 2 The Classical Linear Least Squares Case1547. 2.1 Residuals and Outliers1587.3 Robustizing the Least Squares Approach1607.4 Asymptotics of robust regression Estimates163741 The Cases hp2→0 and hp→07.5 Conjectures and Empirical Results1687.5.1 Symmetric Error Distributions1687.5.2 The Question of Bias1687.6 Asymptotic Covariances and Their estimation1707. 7 Concomitant Scale estimates1727.8 Computation of Regression M-Estimates1757.8.1 The Scale Step1767.8.2 The Location Step with Modified residuals1787.8.3 The Location Step with Modified Weights179CONTENTS7.9 The Fixed Carrier Case: What Size hi?1867. 10 Analysis of Variance1907. 11 LI-estimates and Median polish1937. 12 Other Approaches to Robust Regression1958 Robust Covariance and Correlation Matrices1998. 1 General remarks8.2 Estimation of Matrix Elements Through robust Variances2038.3 Estimation of Matrix Elements Through robust Correlation2048.4 An Affinely equivariant approach2108.5 Estimates Determined by Implicit Equations2128.6 Existence and Uniqueness of Solutions2148.6. 1 The Scatter estimate v2148.6.2 The Location estimate t2198.6.3 Joint Estimation of t and y2208.7 Influence Functions and Qualitative robustness2208.8 Consistency and asymptotic normality2238.9 Breakdown Point48.10 Least informative distributions2258.1058. 10.2 Covariance2278.11 Some Notes on Computation2339 Robustness of Design2399.1 General remarks2399.2 Minimax Global Fit9.3 Minimax Slope24610 Exact Finite Sample Results24910.1 General Remarks24910.2 Lower and Upper Probabilities and Capacities25010.2.1 2-Monotone and 2-Alternating Capacities25510.2.2 Monotone and Alternating Capacities of Infinite Order 25810.3 Robust Tests25910.3. 1 Particular Cases26510.4 Sequential Tests267

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阿里内部Java工程师所遵循的开发规范，涵盖编程规约、单元测试规约、异常日志规约、MySQL规约、工程规约、安全规约等，这是近万名阿里Java技术精英的经验总结.还包含java基础泛型、反射、注解，java高级特性、设计模式等介绍等

【实例简介】本科毕业论文 基于B/S的ERP人力资源管理子系统的设计与开发 目 录 摘要 III 关键词 III Abstract III Key Words III 前言 1 1 相关介绍 1 1.1框架介绍 1 1.2 Struts框架介绍 2 1.3 Hibernate框架介绍 2 1.4 Spring框架介绍 3 1.5开发工具及环境介绍 3 1.5.1 MyEclipse介绍 3 1.5.2 Tomcat介绍 4 1.6 Oracle数据库介绍 4 2 系统架构设计 5 2.1 Struts构建表示层 5 2.2 Spring构建业务逻辑层 5 2.3 Hibernate构建持久化层 5 2.4 系统架构设计 6 3 需求分析与总体设计 8 3.1 系统概述 8 3.2 需求分析 8 3.3 系统的功能结构 9 3.3.1 部门管理模块 9 3.3.2 员工管理模块 9 3.3.3 考勤管理模块 9 3.3.4 招聘管理模块 9 3.3.5 培训管理模块 9 3.3.6 绩效考评模块 9 3.3.7 合同管理模块 9 3.3.8 薪酬福利模块 9 3.3.9 辅助决策模块 10 3.3.10 系统管理模块 10 3.4 系统用户权限分类及描述 10 3.4.1 普通用户 10 3.4.2 管理员 10 3.4.3 超级管理员 10 3.5 系统业务流程图 11 3.6 系统主要用例描述 11 3.6.1 系统登录 11 3.6.2 员工管理 11 3.7 数据库设计 13 3.7.1 数据库表及表关系 13 3.7.2 数据表逻辑结构 14 4 系统实现 19 4.1 搭建SSH框架 19 4.2 目录及包介绍 21 4.3 表示层实现 22 4.4 业务逻辑层实现 24 4.5 持久层及域对象层实现 25 4.6 其他实现 26 4.7 主要实现界面 29 4.7.1 登陆界面 29 4.7.2 首页面 29 4.7.3 部门信息列表界面 29 4.7.4 登记考勤界面 31 4.7.5 更新员工信息界面 31 5 系统测试与评价 32 5.1 测试环境 32 5.2 测试结果 32 5.2.1 功能测试 32 5.2.2 安全测试 32 总结 33 参考文献 34 致谢 35 基于B/S的ERP人力资源管理子系统的设计与开发 摘 要 随着社会经济的发展，人们逐渐认识到，人力是一种资源，是社会经济财富创造必须具备的条件。人力资源是企业最重要的资源之一，对于企业来说,人力资源的管理关系到企业的生存与发展。现代企业管理迫切需求设计一个能够适应和满足企业发展规模的人力资源管理信息系统。本文设计并实现了基于Struts，Spring和Hibernate的ERP人力资源管理子系统。该子系统使用Struts实现MVC，Spring负责架构的结合，Hibernate进行数据的持久化，基本实现了部门管理、员工管理、招聘管理、考勤管理、培训管理、绩效考评管理、薪资管理、合同管理、辅助决策、系统管理等模块。论文对系统的设计和实现作出了详细的描述，并对系统进行了功能测试和安全测试。

水箱液位控制中的PID算法，详细介绍各系数的影响（LabVIEW开发环境）

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