Open AccessLinear and planar structure in ordered multivariate data as applied to progressive demagnetization of palaeomagnetic remanence
Author(s) -
Kent J. T.,
Briden J. C.,
Mardia K. V.
Publication year - 1983
Publication title -
geophysical journal of the royal astronomical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.302
H-Index - 168
eISSN - 1365-246X
pISSN - 0016-8009
DOI - 10.1111/j.1365-246x.1983.tb05001.x
Subject(s) - completeness (order theory) , geology , a priori and a posteriori , stability (learning theory) , mathematics , remanence , algorithm , statistics , physics , mathematical analysis , computer science , magnetization , quantum mechanics , magnetic field , philosophy , epistemology , machine learning
Summary. Consider a sequence of, say, 10 to 20 vector observations in three‐dimensional space. It is suspected that a few subsets of consecutive observations are made up of collinear points. The purpose of this paper is to construct a statistically based algorithm to find such linear segments and to assess their accuracy. A similar assessment is made for coplanar sets of points. This algorithm is applied here to palaeomagnetic data and is claimed to be superior to previous methods of palaeomagnetic analysis in terms of completeness and balance of analysis, treatment of measurement errors and other sources of scatter, criteria for identification of linear and planar sets of points, and statistical rigour. Stability spectra, with statistically based confidence limits, are obtained as a by‐product.