Classification of Continuous Distributional Data Using the Logratio Approach

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F22%3A73617310" target="_blank" >RIV/61989592:15310/22:73617310 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1201/9781315370545-9" target="_blank" >http://dx.doi.org/10.1201/9781315370545-9</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1201/9781315370545-9" target="_blank" >10.1201/9781315370545-9</a>

Result language

angličtina

Original language name

Classification of Continuous Distributional Data Using the Logratio Approach

Original language description

One of the fundamental tasks in statistics is to classify observations into one of predefined classes, whether the observations are of multivariate or functional character. When considering distributional data, suitable classification methods honouring the data specificities are yet to be developed. In this work, a classification method for distributional data represented as probability density functions (PDFs) is proposed. The method uses the centred log-ratio (clr) transformation to adapt functional linear discriminant analysis to the distributional setting. Within the proposed setting, each functional observation is projected into a reduced discriminant space, and the classification itself is then based on minimizing the distance between the linear projections of the class representatives and those of the functional observations. The introduced method is demonstrated on geological data consisting of particle size distribution of 250 soil samples from four measuring sites in Moravia region, Czech Republic.

Czech name

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Czech description

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Type

C - Chapter in a specialist book

CEP classification

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OECD FORD branch

10103 - Statistics and probability

Project

<a href="/en/project/GA19-01768S" target="_blank" >GA19-01768S: Separation of geochemical signals in sediments: application of advanced statistical methods on large geochemical datasets</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Book/collection name

Analysis of Distributional Data

ISBN

978-1-4987-2545-3

Number of pages of the result

20

Pages from-to

183-202

Number of pages of the book

376

Publisher name

Chapman &amp; Hall

Place of publication

London

UT code for WoS chapter

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