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Protein structure calculation with data imputation: the use of substitute restraints
(Springer NetherlandsDordrecht, 2009-12)
The amount of experimental restraints e.g., NOEs is often too small for calculating high quality threedimensional structures by restrained molecular dynamics. Considering this as a typical missing value problem we propose ...
Water-quality data imputation with a high percentage of missing values : A machine learning approach
(MDPI, 2021)
The monitoring of surface-water quality followed by water-quality modeling and analysis are essential for generating effective strategies in surface-water-resource management. However, worldwide, particularly in developing ...
SNP-HLA Reference Consortium (SHLARC): HLA and SNP data sharing for promoting MHC-centric analyses in genomics
(2020-10-01)
Genome-wide associations studies have repeatedly identified the major histocompatibility complex genomic region (6p21.3) as key in immune pathologies. Researchers have also aimed to extend the biological interpretation of ...
Computational aspects of nonparametric Bayesian analysis with applications to the modeling of multiple binary sequences
(AMER STATISTICAL ASSOC, 2000)
We consider Markov mixture models for multiple longitudinal binary sequences. Prior uncertainty in the mixing distribution is characterized by a Dirichlet process centered on a matrix beta measure. We use this setting to ...
Techniques for Robust Imputation in Incomplete Two-Way TablesTécnicas de Imputación Robusta en Tablas de Doble Entrada Incompletas
(Applied System Innovation, 08/08/2021)
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, ...
Combining multiple imputation and control function methods to deal with missing data and endogeneity in discrete-choice models
(Elsevier, 2020)
While collecting data for estimating discrete-choice models, researchers often encounter missing information in observations. In addition, endogeneity can occur whenever the error term is not independent of the observed ...
Breast cancer and modifiable lifestyle factors in argentinean women: Addressing missing data in a case-control study
(Asian Pacific Organization Cancer Prevention, 2016-10)
A number of studies have evidenced the effect of modifiable lifestyle factors such as diet, breastfeeding and nutritional status on breast cancer risk. However, none have addressed the missing data problem in nutritional ...
Self-Organizing Maps for Imputation of Missing Data in Incomplete Data Matrices
(Elsevier Science Bv, 2015)
Incremental missing data imputation via modified granular evolving fuzzy modelImputação incremental de dados faltantes via modelo granular fuzzy evolutivo modificado
(Universidade Federal de LavrasPrograma de Pós-Graduação em Engenharia de Sistemas e AutomaçãoUFLAbrasilDepartamento de Engenharia, 2018)