This is the second edition of a highly succesful book which has sold nearly 3000 copies world wide since its publication in 1997.
Many chapters will be rewritten and expanded due to a lot of progress in these areas since the publication of the first edition.
Bernard Silverman is the author of two other books, each of which has lifetime sales of more than 4000 copies. He has a great reputation both as a researcher and an author.
This is likely to be the bestselling book in the Springer Series in Statistics for a couple of years.
Table of ContentsIntroduction * Notation and Techniques * Representing Functional Data as Smooth Functions * The Roughness Penalty Approach * The Registration and Display of Functional Data * Principal Components Analysis for Functional Data * Regularized Principal Components Analysis * Principal Components Analysis of Mixed Data * Functional Linear Models * Functional Linear Models for Scalar Responses * Functional Linear Modesl for Functional Responses * Canonical Correlation and Discriminant Analysis * Differential Operators in Functional Data Analysis * Principal Differential Analysis * More General Roughness Penalties * Some Perspectives on FDA