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Synopsis
数据存在于特定的时间和空间中，其复杂的分层结构是一种普遍现象。充分借助于数据的这一特点，可以大大提高统计分析的有效性。本书致力于介绍复杂分层数据分析前沿知识，侧重于算法、仿真与实证研究。内容主要包括：分层线性模型、分层广义线性模型、分层非线性模型、分层半参数模型和分层分位回归模拟等。本书可作为统计学及其相关领域的本科生、研究生的教材，亦可供教师和科技人员参考。理论、方法与应用（应用统计工程前沿丛书）《现代分层分位回归：理论、方法与应用》主要介绍“分层复合分位回归模型”，而“分层复合分位回归模型”是大数据中的热点问题，当前大数据空前火热，而目前国内“分层复合分位回归模型”领域的研究成果寥寥无几，本书则囊括了“分层复合分位回归模型”近年来的最新科研成果和应用，是“十二五”国家重点图书出版规划项目，含金量十足。
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Modern delaminating Regression: Theory. Methods and Applications Applied Statistics Frontiers of Engineering Series(Chinese Edition)
ISBN 10: 7302394741
ISBN 13: 9787302394747
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paperback
Seller: liu xing, Nanjing, JS, China
Seller rating 5 out of 5 stars
paperback. Condition: New. Language:Chinese.Paperback. Pub Date: 2015-4-1 Pages: 348 Publisher: Tsinghua University Press of data present in a particular time and space. its complex layered structure is a universal phenomenon fully by means of this characteristic data. It can greatly improve the statistical analysis of the effectiveness of the book dedicated to introduce complex hierarchical data analysis the frontiers of knowledge. focusing on algorithms. simulation and empirical research includes: hierarchical linear. Seller Inventory # CS045717