Applying Advanced Statistics to Problems in Tephrochronology
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Applying Advanced Statistics to Problems in Tephrochronology

Applying Advanced Statistics to Problems in Tephrochronology


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About the Book

This dissertation, "Applying Advanced Statistics to Problems in Tephrochronology" by Bik-wa, Lee, 李碧華, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Abstract of thesis entitled APPLYING ADVANCED STATISTICS TO PROBLEMS IN TEPHROCHRONOLOGY Submitted by LEE BIK WA for the degree of Master of Philosophy at the University of Hong Kong in August 2006 Tephrochronology is the dating of tephra by studying the characteristics of different tephra layers, so it is both as a geological and statistical problem. The characteristic studied in this thesis is the composition of the ten most common major oxides. Due to the great number of variables, discriminant function analysis (DFA) has often been applied to correlate unknown tephras to a reference set. However, DFA may give an ambiguous assignation and the assumption of exhaustibility of the reference set in describing all the possible and existing tephras is unrealistic. The aim of this thesis is to derive new methods that do not just consider the age of the tephras in the reference set, but also include the possibility that the tephra is a new-found one and does not belong to the reference set. DFA is applied to compositional datasets of two different types of tephras from Mountain Ruapehu in New Zealand and Mountain Rainier in the USA. The first few canonical variables are used to summarize the variation and a periodic up-and-down pattern is found consistently across age in different canonical variables of all the datasets. The first canonical variable is investigated with an advanced statistical methodology of change-point problems in order to study the time of change and the change in pattern. A special case of segmented regression is proposed to model this pattern, which gives a composition-age relationship that can be used to compare the unknown tephra with the reference set in order to estimate the age for the unknown tephras. Two methods based on the proposed segmented regression are suggested to date the unknown tephras; the first estimates the age by calibration and the second matches the unknown tephras with samples from the reference set or missing samples. These methodologies are illustrated using a simulated dataset and a real dataset. DOI: 10.5353/th_b3847845 Subjects: Tephrochronology - Statistical methods


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Product Details
  • ISBN-13: 9781374670808
  • Publisher: Open Dissertation Press
  • Publisher Imprint: Open Dissertation Press
  • Height: 279 mm
  • No of Pages: 124
  • Weight: 304 gr
  • ISBN-10: 1374670804
  • Publisher Date: 27 Jan 2017
  • Binding: Paperback
  • Language: English
  • Spine Width: 7 mm
  • Width: 216 mm


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