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Statistical tools for analyzing distributions of rock fabric orientations are limited to point estimators and graphical plots. Inapplicability of conventional statistics is a result of directional nature of these observations. This book presents new techniques expanding arsenal of orientational analysis and applicable in statistics for directional data in general. In the introductory chapter, discussion of directional data is given together with its relation to observations in structural geology. Next chapter presents the tools themselves, starting with point estimation on Stiefel and Grassman…mehr

Produktbeschreibung
Statistical tools for analyzing distributions of rock
fabric orientations are limited to point estimators
and graphical plots. Inapplicability of conventional
statistics is a result of directional nature of these
observations. This book presents new techniques
expanding arsenal of orientational analysis and
applicable in statistics for directional data in
general. In the introductory chapter, discussion of
directional data is given together with its relation
to observations in structural geology. Next chapter
presents the tools themselves, starting with point
estimation on Stiefel and Grassman manifolds using
incomplete data. Following it, a nonlinear regression
model of directions on linear (spatial) data is
presented. Finally, modification of kernel smoothing
for directional data is discussed. Last chapter is a
case study of a structurally complex metamorphic
terrane in which, besides applying the above tools,
use of bootstrap for the purpose of inference is
shown. This book should be especially useful for
structural geologists specializing in orientational
analysis, but may also fit interests of others
working with directional data.
Autorenporträt
MS, PhD Candidate: Studied metamorphic
structuctural geology at St.Petersburg State University,
Russia. At the University of Texas, Arlington developed
spherical-spatial regression model in application to fabric
analysis. Currently at the University of
Michigan studying tectonics of the Greater Caucasus.