J. A. Martín-Fernández

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The log-ratio methodology represents a powerful set of methods and techniques for statistical analysis of compositional data. These techniques may be used for the estimation of rounded zeros or values below the detection limit in cases when the underlying data are compositional in nature. An algorithm based on iterative log-ratio regressions is developed by(More)
The application of hierarchic methods of classification needs to establish in advance some or all of the following measures: difference, central tendency and dispersion, in accordance with the nature of the data. In this work, we present the requirements for these measures when the data set to classify is a compositional data set. Specific measures of(More)
Provenance studies are an increasingly important analog for understanding how trees adapted to particular climatic conditions might respond to climate change. Dendrochronological analysis can illuminate differences among trees from different seed sources in terms of absolute annual growth and sensitivity to external growth factors. We analyzed annual radial(More)
Compositional data is frequently collected in many applied fields such as chemistry, nutrition and behaviour sciences. Formally, a compositional vector or simply a composition is defined as a D-dimensional vector x=[x 1 , x 2 ,…, x D ] such that x j >0, j= 1,…,D, subject to a constant-sum constraint x 1 +x 2 +. .. +x D =1. The log-ratio methodology (e.g.,(More)
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