| 书目名称 | Data Analysis Using the Method of Least Squares |
| 副标题 | Extracting the Most |
| 编辑 | John Wolberg |
| 视频video | |
| 概述 | Develops the full power of the least-squares method.Enables engineers and scientists to apply the method to their specific problem.Deals with linear as well as with non-linear least-squares, parametri |
| 图书封面 |  |
| 描述 | Measurements through quantitative experiments are one of the most f- damental tasks in all areas of science and technology. Astronomers a- lyze data from asteroid sightings to predict orbits. Computer scientists - velop models for recognizing spam mail. Physicists measure properties of materials at low temperatures to understand superconductivity. Materials engineers study the reaction of materials to varying load levels to develop methods for prediction of failure. Chemical engineers consider reactions as functions of temperature and pressure. The list is endless. From the very small-scale work on DNA to the huge-scale study of black holes, quantitative experiments are performed and the data must be analyzed. Probably the most popular method of analysis of the data associated with quantitative experiments is least squares. It has been said that the method of least squares was to statistics what calculus was to mathematics. - though the method is hardly mentioned in most engineering and science undergraduate curricula, many graduate students end up using the method to analyze the data gathered as part of f their research. There is not a lot of available literature on the subject. V |
| 出版日期 | Book 2006 |
| 关键词 | Curve Fitting; Experiment; Least Squares; Nonlinear Models; Parametric Models; Regression; calculus; data a |
| 版次 | 1 |
| doi | https://doi.org/10.1007/3-540-31720-1 |
| isbn_softcover | 978-3-540-25674-8 |
| isbn_ebook | 978-3-540-31720-3 |
| copyright | Springer-Verlag Berlin Heidelberg 2006 |
发表于 2025-3-21 18:41:25
