Imputation of missing values for compositional data using classical and robust methods

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F10%3A10211954" target="_blank" >RIV/61989592:15310/10:10211954 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1016/j.csda.2009.11.023" target="_blank" >http://dx.doi.org/10.1016/j.csda.2009.11.023</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.csda.2009.11.023" target="_blank" >10.1016/j.csda.2009.11.023</a>

Result language
angličtina
Original language name
Imputation of missing values for compositional data using classical and robust methods
Original language description
New imputation algorithms for estimating missing values in compositional data are introduced. A first proposal uses the k-nearest neighbor procedure based on the Aitchison distance, a distance measure especially designed for compositional data. It is important to adjust the estimated missing values to the overall size of the compositional parts of the neighbors. As a second proposal an iterative model-based imputation technique is introduced which initially starts from the result of the proposed k-nearest neighbor procedure. The method is based on iterative regressions, thereby accounting for the whole multivariate data information. The regressions have to be performed in a transformed space, and depending on the data quality classical or robust regression techniques can be employed. The proposed methods are tested on a real and on simulated data sets. In the presence of outliers, the model-based method with robust regressions is preferable.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
BA - General mathematics
OECD FORD branch
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Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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