Multivariate linear regression with missing values
Multivariate linear regression with missing values is a scholarly work, published in 2013 in ''Analytica Chimica Acta''. The main subjects of the publication include imputation, general linear model, data set, statistics, missing data, regression, univariate, multivariate statistics, Proper linear model, chemistry, Bayesian multivariate linear regression, multicollinearity, Data Matrix, linear regression, chemometrics, Linear predictor function, design matrix, regression analysis, mathematics, and Principal component regression. This contribution presents and discusses an efficient algorithm for multivariate linear regression analysis of data sets with missing values.