Nonlinear Regression Analysis and Its Applications
Nonlinear Regression Analysis and Its Applications
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DOI：
10.1080/00401706.1990.10484638
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发表时间：
1990-05
期刊：
影响因子：
2.5
通讯作者：
G. Milliken
中科院分区：
文献类型：
--
作者：
G. Milliken
Wiley-Interscience平装本系列Wiley-Interscience平装本系列由精选书籍组成，这些书籍已变得更容易为消费者所接受，以提高全球吸引力和普遍发行量。威利希望通过这些新的未删节的软封面卷，将这些作品提供给子孙后代的统计学家、数学家和科学家，从而延长这些作品的生命力。“作者们对有关非线性回归模型的使用和分析的概念和方法进行了非凡的介绍。强烈推荐[艾德]。对于任何需要使用和/或理解有关非线性回归模型分析问题的人。“-Technometrics“[这本书]提供了一个很好的平衡相关理论和应用与许多例子. [and它]提供了最平衡的方法，理论和应用适合第一门课程，在非线性回归建模的研究生统计学生。“-数学评论“[这本书]加入了一个杰出的出版物名单，以平衡技术严谨性与可读性，理论与应用的声誉。[It]坚持传统[and是]一个值得参考的营销研究人员与严重的兴趣线性模型。这本书提供了非线性回归的理论，实践和计算方面的平衡介绍，并提供了线性回归的背景材料，包括线性和非线性最小二乘法的几何发展。作者自始至终都采用了真实的数据集，他们对几何构造和连续例子的广泛使用使思想的进展显得非常自然。这本书还包括计算算法的伪代码。
Wiley-Interscience Paperback Series The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "The authors have put together an extraordinary presentation of concepts and methods concerning the use and analysis of nonlinear regression models ...highly recommend[ed] ...for anyone needing to use and/or understand issues concerning the analysis of nonlinear regression models." -Technometrics "[This book] provides a good balance of relevant theory and application with many examples ...[and it] provides the most balanced approach to theory and application appropriate for a first course in nonlinear regression modeling for graduate statistics students." -Mathematical Reviews "[This book] joins a distinguished list of publications with a reputation for balancing technical rigor with readability, and theory with application. [It] upholds tradition ...[and is] a worthwhile reference for the marketing researcher with a serious interest in linear models. " -Journal of Marketing Research This book offers a balanced presentation of the theoretical, practical, and computational aspects of nonlinear regression and provides background material on linear regression, including the geometrical development for linear and nonlinear least squares. The authors employ real data sets throughout, and their extensive use of geometric constructs and continuing examples makes the progression of ideas appear very natural. The book also includes pseudocode for computing algorithms.