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About this book
About this book
Data measured as angles or two-dimensional orientations are found almost everywhere in science. They commonly arise in biology, geography, geophysics, medicine, meteorology and oceanography, and many other areas. Examples of such data include departure directions of birds from release points, fracture plane orientations, the directional movement of animals after stimulation, wind and ocean current directions, and biorhythms. Statistical methods for handling such data have developed rapidly in the last twenty years, particularly data display, correlation, regression and analysis of tempered or spatially structured data. Further, some of the exciting modern developments in general statistical methodology, particularly nonparametric smoothing methods and bootstrap-based methods, have contributed significantly to relatively intractable data analysis problems. This book provides a unified and up-to-date account of techniques for handling circular data.
Preface; 1. The purpose of the book; 2. Survey of contents; 3. How to use the book; 4. Notation, terminology and conventions; 5. Acknowledgements; Part I. Introduction: Part II. Descriptive Methods: 2.1. Introduction; 2.2. Data display; 2.3. Simple summary quantities; 2.4. Modifications for axial data; Part III. Models: 3.1. Introduction; 3.2. Notation; trigonometric moments; 3.3. Probability distributions on the circle; Part IV. Analysis of a Single Sample of Data: 4.1. Introduction; 4.2. Exploratory analysis; 4.3. Testing a sample of unit vectors for uniformity; 4.4. Nonparametric methods for unimodal data; 4.5. Statistical analysis of a random sample of unit vectors from a von Mises distribution; 4.6. Statistical analysis of a random sample of unit vectors from a multimodal distribution; 4.7. Other topics; Part V. Analysis of Two or More Samples, and of Other Experimental Layouts: 5.1. Introduction; 5.2. Exploratory analysis; 5.3. Nonparametric methods for analysing two or more samples of unimodal data; 5.4. Analysis of two or more samples from von Mises distributions; 5.5. Analysis of data from more complicated experimental designs; Part VI. Correlation and Regression: 6.1. Introduction; 6.2. Linear-circular association and circular-linear association; 6.3. Circular-circular association; 6.4. Regression models for a circular response variable; Part VII. Analysis of Data with Temporal or Spatial Structure: 7.1. Introduction; 7.2. Analysis of temporal data; 7.3. Spatial analysis; Part VIII. Some Modern Statistical Techniques for Testing and Estimation: 8.1. Introduction; 8.2. Bootstrap methods for confidence intervals and hypothesis tests: general description; 8.3. Bootstrap methods for circular data: confidence regions for the mean direction; 8.4. Bootstrap methods for circular data: hypothesis tests for mean directions; 8.5. Randomisation, or permutation, tests; Appendix A. Tables; Appendix B. Data sets; References; Index.
Handbook / Manual
277 pages, B/w figs, tabs
...I suggest you pick up this book...this is a delightful, modern, and unified text. The writing style is exceptionally clear and lucid...examples are motivating and nontechnical and are easy to follow. For these reasons, the book can also be used as a textbook for university students who often deal with or collect circular data...the book looks wonderful...contains much valuable information and many interesting examples and gives an excellent--and for the most part nontechnical--introduction to build a solid foundation in circular data analysis...covers the most recent developments in the area. I strongly recommend it for students and researchers. Chance "I would recommend this book to any statistician who needs to analyze circular data. The author's style is quite readable. The page layout is pleasing, and the graphics are very well done...I was very impressed with this book." Thomas E. Wehrly, Technometrics "...as circular data become more common and their underlying questions become more complex, Statistical Analysis of Circular Data will continue to help move this 'curious byway' into a mainstream of applied statistical science. This is a book that is written to be used." Nicholas Lange, Journal of the American Statistical Association "...this well-crafted text contains a wealth of other historical and technical aspects of analyzing circular data that you will find both interesting and informative." Timothy G. Gregoire, Forest Science