By J.O. Ramsay
A pleasant, if overpriced, booklet, yet no longer one who you must hold, in contrast to Ramsay and Silverman's "Functional info research" (FDA). AFDA elaborates numerous examples brought in FDA. The examples hide approximately 60% of FDA's fabric: smoothing is given less area than in FDA, and regression (cf. FDA's Chapters 12-15) is skipped over. when you are determining among the 2 books, opt for FDA.
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Additional info for Applied Functional Data Analysis
2 onwards. 5 How are functions stored and processed? 1 Basis expansions In the example we have considered, we could simply store all the original values at the 25 evaluation points, since these points are the same for each individual in the sample. However, there are several reasons for considering other approaches. First, it is in the spirit of functional data analysis that we wish to specify the whole function, not just its value at a ﬁnite number of points. Second, it is important to have a method that can generalize to the case where the evaluation points are not the same for every individual in the sample.
2. 2. 1 plotted on a logarithmic scale. 6% increase in the index per year. 2 Transformation and smoothing Like most economic indicators, the nondurable goods index tends to exhibit exponential increase, corresponding to percentage increases over ﬁxed time periods. Moreover, the index tends to increase in size and volatility at the same time, so that the large relative eﬀects surrounding the Second World War seem to be small relative to the large changes in the 1970s and 1980s, and seasonal variation in recent years dwarfs that in early years.
2. The record of a particular individual, showing the numbers of arrests at various ages. This individual was arrested for three oﬀenses at age 11, one at age 14, and so on, but was not arrested at all in years 12, 13, 15, etc. every individual is likely to show a sporadic pattern of some sort. Despite the very noisy nature of the data, one of our aims is to ﬁnd ways of quantifying meaningful patterns in individuals that reﬂect variation in the wider population. Our analysis raises a number of questions of broader importance in functional data analysis.