Fred L. Bookstein

Course in Morphometrics for Biologists (eBook, PDF)

Geometry and Statistics for Studies of Organismal Form

• Format: PDF

Produktbeschreibung

This book builds a much-needed bridge between biostatistics and organismal biology by linking the arithmetic of statistical studies of organismal form to the biological inferences that may follow from it. It incorporates a cascade of new explanations of regression, correlation, covariance analysis, and principal components analysis, before applying these techniques to an increasingly common data resource: the description of organismal forms by sets of landmark point configurations. For each data set, multiple analyses are interpreted and compared for insight into the relation between the arithmetic of the measurements and the rhetoric of the subsequent biological explanations. The text includes examples that range broadly over growth, evolution, and disease. For graduate students and researchers alike, this book offers a unique consideration of the scientific context surrounding the analysis of form in today's biosciences.

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Produktdetails

• Verlag: Cambridge University Press
• Erscheinungstermin: 4. Oktober 2018
• Englisch
• ISBN-13: 9781108128940
• Artikelnr.: 56556027

Autorenporträt

Fred L. Bookstein is generally considered the founder of modern morphometrics, an interdisciplinary field bridging computer vision, statistical science, and organismal biology. His most lasting contribution to the field is probably his 1989 invention of the thin-plate spline for depiction and decomposition of changes in landmark configurations, a method that has appeared in countless scientific publications, several courtroom proceedings, and even a dance concert. A Fellow of the Institute of Mathematical Statistics, he was the first winner (2011) of the Rohlf Medal for Excellence in Morphometrics. This is his eighth book.

Inhaltsangabe

1. What this book is about
2. Getting started
3. Multiple regression in general and in special settings
4. Transition to multivariate analysis
5. Geometric morphometrics.