Jeffrey J. Love
2007
<p><span>When studying the mean and variance of paleomagnetic data it is a common practice to employ principal component analysis (Jolliffe, </span><span class="CitationRef">2002</span><span>). The theory of this method is related to the mathematics quantifying the moment of inertia of a set of particles of mass about some reference point of interest. For the purposes of data analysis, principal component analysis was first promoted by Pearson (</span><span class="CitationRef">1901</span><span>) and Hotelling (</span><span class="CitationRef">1933</span><span>), and it also often associated with Karhunen (</span><span class="CitationRef">1947</span><span>) and LoĆ©ve (</span><span class="CitationRef">1977</span><span>). Principal component analysis is widely applied in crystallography (e.g., Schomaker </span><i class="EmphasisTypeItalic ">et al</i><span>., </span><span class="CitationRef">1959</span><span>). In paleomagnetism (e.g., Mardia, </span><span class="CitationRef">1972</span><span>; Kirschvink, </span><span class="CitationRef">1980</span><span>), it finds application in studies of the average paleofield, paleosecular variation, demagnetization, and magnetic susceptibility. Here we discuss and demonstrate principal component analysis in application to full paleomagnetic vectorial data and, separately, to paleomagnetic directional data.</span></p>
application/pdf
10.1007/978-1-4020-4423-6_271
en
Springer
Principal component analysis in paleomagnetism
chapter