Techniques for Robust Imputation in Incomplete Two-Way Tables

Applied System Innovation

Wojtek J. Krzanowski¹  Marisol García-Peña²  Sergio Arciniegas-Alarcón³  Camilo Rengifo³ 

[1] College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter EX4 4QF, UK;Departamento de Matemáticas, Pontificia Universidad Javeriana, Carrera 7 40-62, Bogotá 110231, Colombia;Facultad de Ingeniería, Universidad de La Sabana, Campus Puente del Común, Km. 7 Autopista Norte, Chía 140013, Colombia;

关键词: imputation;    missing values;    singular value decomposition;    genotype-by-environment interaction;   

DOI  :  10.3390/asi4030062

来源: DOAJ

【 摘 要 】

We describe imputation strategies resistant to outliers, through modifications of the simple imputation method proposed by Krzanowski and assess their performance. The strategies use a robust singular value decomposition, do not depend on distributional or structural assumptions and have no restrictions as to the pattern or missing data mechanisms. They are tested through the simulation of contamination and unbalance, both in artificially generated matrices and in a matrix of real data from an experiment with genotype-by-environment interaction. Their performance is assessed by means of prediction errors, the squared cosine between matrices, and a quality coefficient of fit between imputations and true values. For small matrices, the best results are obtained by applying robust decomposition directly, while for larger matrices the highest quality is obtained by eliminating the singular values of the imputation equation.

【 授权许可】

Unknown