Model-based replacement of rounded zeros in compositional data: Classical and robust approaches

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F12%3A33141584" target="_blank" >RIV/61989592:15310/12:33141584 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.csda.2012.02.012" target="_blank" >http://dx.doi.org/10.1016/j.csda.2012.02.012</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.csda.2012.02.012" target="_blank" >10.1016/j.csda.2012.02.012</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Model-based replacement of rounded zeros in compositional data: Classical and robust approaches

Popis výsledku v původním jazyce

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 combining a particular family of isometric log-ratio transformations with censored regression. In the context of classical regression methods, the equivalence of the method based on additive and isometric log-ratio transformations is proved. This equivalence does not hold for robust regression. Based on Monte Carlo methods, simulations are performed to assess the performance of classical and robustmethods. To illustrate the method, a case study involving geochemical data is conducted.

Název v anglickém jazyce

Model-based replacement of rounded zeros in compositional data: Classical and robust approaches

Popis výsledku anglicky

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 combining a particular family of isometric log-ratio transformations with censored regression. In the context of classical regression methods, the equivalence of the method based on additive and isometric log-ratio transformations is proved. This equivalence does not hold for robust regression. Based on Monte Carlo methods, simulations are performed to assess the performance of classical and robustmethods. To illustrate the method, a case study involving geochemical data is conducted.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2012

Kód důvěrnosti údajů

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

Název periodika

Computational Statistics and Data Analysis

ISSN

0167-9473

e-ISSN

—

Svazek periodika

56

Číslo periodika v rámci svazku

9

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

17

Strana od-do

2688-2704

Kód UT WoS článku

000304073600007

EID výsledku v databázi Scopus

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