| Description |
190 pages : illustrations ; 24 cm |
| Series |
Springer series in statistics |
|
Springer series in statistics.
|
| Contents |
1. Introduction -- 1.1. Why consider functional data at all? -- 1.2. The Web site -- 1.3. The case studies -- 1.4. How is functional data analysis distinctive? -- 1.5. Conclusion and bibliography -- 2. Life Course Data in Criminology -- 2.1. Criminology life course studies -- 2.2. First steps in a functional approach -- 2.3. Functional principal component analyses -- 2.4. What have we seen? -- 2.5. How are functions stored and processed? -- 2.6. Cross-validation for estimating the mean -- 2.7. Notes and bibliography -- 3. The Nondurable Goods Index -- 3.1. Introduction -- 3.2. Transformation and smoothing -- 3.3. Phase-plane plots -- 3.4. The nondurable goods cycles -- 3.5. What have we seen? -- 3.6. Smoothing data for phase-plane plots -- 4. Bone Shapes from a Paleopathology Study -- 4.1. Archaeology and arthritis -- 4.2. Data capture -- 4.3. How are the shapes parameterized? -- 4.4. A functional principal components analysis -- 4.5. Varimax rotation of the principal components -- 4.6. Bone shapes and arthritis: Clinical relationship? -- 4.7. What have we seen? -- 4.8. Notes and bibliography -- |
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5. Modeling Reaction-Time Distributions -- 5.1. Introduction -- 5.2. Nonparametric modeling of density functions -- 5.3. Estimating density and individual differences -- 5.4. Exploring variation across subjects with PCA -- 5.5. What have we seen? -- 5.6. Technical details -- 6. Zooming in on Human Growth -- 6.1. Introduction -- 6.2. Height measurements at three scales -- 6.3. Velocity and acceleration -- 6.4. An equation for growth -- 6.5. Timing or phase variation in growth -- 6.6. Amplitude and phase variation in growth -- 6.7. What we have seen? -- 6.8. Notes and further issues -- 7. Time Warping Handwriting and Weather Records -- 7.1. Introduction -- 7.2. Formulating the registration problem -- 7.3. Registering the printing data -- 7.4. Registering the weather data -- 7.5. What have we seen? -- 7.6. Notes and references -- 8. How Do Bone Shapes Indicate Arthritis? -- 8.1. Introduction -- 8.2. Analyzing shapes without landmarks -- 8.3. Investigating shape variation -- 8.4. The shape of arthritic bones -- 8.5. What have we seen? -- 8.6. Notes and further issues -- |
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9. Functional Models for Test Items -- 9.1. Introduction -- 9.2. The ability space curve -- 9.3. Estimating item response functions -- 9.4. PCA of log odds-ratio functions -- 9.5. Do women and men perform differently on this test? -- 9.6. A nonlatent trait: Arc length -- 9.7. What have we seen? -- 9.8. Notes and bibliography -- 10. Predicting Lip Acceleration from Electromyography -- 10.1. The neural control of speech -- 10.2. The lip and EMG curves -- 10.3. The linear model for the data -- 10.4. The estimated regression function -- 10.5. How far back should the historical model go? -- 10.6. What have we seen? -- 10.7. Notes and bibliography -- 11. The Dynamics of Handwriting Printed Characters -- 11.1. Recording handwriting in real time -- 11.2. An introduction to dynamic models -- 11.3. One subject's printing data -- 11.4. A differential equation for handwriting -- 11.5. Assessing the fit of the equation -- 11.6. Classifying writers by using their dynamic equations -- 11.7. What have we seen? -- 12. A Differential Equation for Juggling -- 12.1. Introduction -- 12.2. The data and preliminary analyses -- 12.3. Features in the average cycle -- 12.4. The linear differential equation -- 12.5. What have we seen? -- 12.6. Notes and references |
| Summary |
"What do juggling, old bones, criminal careers and human growth patterns have in common? They all give rise to functional data, that come in the form of curves or functions rather than the numbers, or vectors of numbers, that are considered in conventional statistics. The authors' highly acclaimed book Functional Data Analysis (1997) presented a thematic approach to the statistical analysis of such data. By contrast, the present book introduces and explores the ideas of functional data analysis by the consideration of a number of case studies, many of them presented for the first time. The two books are complementary but neither is a prerequisite for the other |
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"The case studies are accessible to research workers in a wide range of disciplines. Every reader, whether experienced researcher or graduate student, should gain not only a specific understanding of the methods of functional data analysis, but more importantly a general insight into the underlying patterns of thought. Some of the studies demand the development of novel aspects of the methodology of functional data analysis, but technical details aimed at the specialist statistician are confined to sections which the more general reader can safely omit. There is an associated web site with MATLAB and S-PLUS implementations of the methods discussed, together with all the data sets that are not proprietary." -- Publisher's website |
| Bibliography |
Includes bibliographical references (pages [183]-186) and index |
| Subject |
Multivariate analysis.
|
| Author |
Silverman, B. W., 1952-
|
| LC no. |
2002022924 |
| ISBN |
0387954147 paperback alkaline paper |
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