Regression imputation with Q-mode clustering for rounded zero replacement in high-dimensional compositional data

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F18%3A73589105" target="_blank" >RIV/61989592:15310/18:73589105 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1080/02664763.2017.1410524" target="_blank" >http://dx.doi.org/10.1080/02664763.2017.1410524</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1080/02664763.2017.1410524" target="_blank" >10.1080/02664763.2017.1410524</a>

Result language

angličtina

Original language name

Regression imputation with Q-mode clustering for rounded zero replacement in high-dimensional compositional data

Original language description

The logratio methodology is not applicable when rounded zeros occur in compositional data. There are many methods to deal with rounded zeros. However, some methods are not suitable for analyzing data sets with high dimensionality. Recently, related methods have been developed, but they cannot balance the calculation time and accuracy. For further improvement, we propose a method based on regression imputation with Q-mode clustering. This method forms the groups of parts and builds partial least squares regression with these groups using centered logratio coordinates.We also prove that using centered logratio coordinates or isometric logratio coordinates in the response of partial least squares regression have the equivalent results for the replacement of rounded zeros. Simulation study and real example are conducted to analyze the performance of the proposed method. The results show that the proposed method can reduce the calculation time in higher dimensions and improve the quality of results.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10103 - Statistics and probability

Project

—

Continuities

N - Vyzkumna aktivita podporovana z neverejnych zdroju

Publication year

2018

Confidentiality

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

Name of the periodical

JOURNAL OF APPLIED STATISTICS

ISSN

0266-4763

e-ISSN

—

Volume of the periodical

45

Issue of the periodical within the volume

11

Country of publishing house

GB - UNITED KINGDOM

Number of pages

14

Pages from-to

2067-2080

UT code for WoS article

000436973300009

EID of the result in the Scopus database

2-s2.0-85049522544