Fitting limit lines (envelope curves) to spreads of geoenvironmental data

Carling, P.A. and Jonathan, P. and Su, T. (2022) Fitting limit lines (envelope curves) to spreads of geoenvironmental data. Progress in Physical Geography, 46 (2). pp. 272-290. ISSN 0309-1333

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Abstract

Geoscientists frequently are interested in defining the overall trend in x-y data clouds using techniques such as least-squares regression. Yet often the sample data exhibits considerable spread of y-values for given x-values, which is itself of interest. In some cases, the data may exhibit a distinct visual upper (or lower) ‘limit’ to a broad spread of y-values for a given x-value, defined by a marked reduction in concentration of y-values. As a function of x-value, the locus of this ‘limit’ defines a ‘limit line’, with no (or few) points lying above (or below) it. Despite numerous examples of such situations in geoscience, there has been little consideration within the general geoenvironmental literature of methods used to define limit lines (sometimes termed ‘envelope curves’ when they enclose all data of interest). In this work, methods to fit limit lines are reviewed. Many commonly applied methods are ad-hoc and statistically not well founded, often because the data sample available is small and noisy. Other methods are considered which correspond to specific statistical models offering more objective and reproducible estimation. The strengths and weaknesses of methods are considered by application to real geoscience data sets. Wider adoption of statistical models would enhance confidence in the utility of fitted limits and promote statistical developments in limit fitting methodologies which are likely to be transformative in the interpretation of limits. Supplements, a spreadsheet and references to software are provided for ready application by geoscientists.

Item Type:
Journal Article
Journal or Publication Title:
Progress in Physical Geography
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1900/1901
Subjects:
?? envelope curveslimit linesnon-parametric maximum likelihood methodsquantile regressiontrimming methodearth and planetary sciences (miscellaneous)general earth and planetary sciencesgeography, planning and developmentearth and planetary sciences(all) ??
ID Code:
187295
Deposited By:
Deposited On:
22 Feb 2023 14:40
Refereed?:
Yes
Published?:
Published
Last Modified:
16 Jul 2024 11:46