 A two-step estimation method for grouped data with connections to the extended growth curve model and partial least squares regressionYing Li, Peter Udén and Dietrich von Rosen Journal of Multivariate Analysis, 2015, vol. 139, issue C, 347-359 Abstract: In this article, the two-step method for prediction, which was proposed by Li et al. (2012), is extended for modelling grouped data, which besides having near-collinear explanatory variables, also having different mean structure, i.e. the mean structure of some part of the data is more complex than other parts. In the first step, inspired by partial least squares regression (PLS), the information for explanatory variables is summarized by a multilinear model with Krylov structured design matrices, which for different groups have different size. The multilinear model is similar to the classical growth curve model except that the design matrices are unknown and are functions of the dispersion matrix. Under such a multilinear model, natural estimators for mean and dispersion matrices are proposed. In the second step, the response is predicted through a conditional predictor where the estimators obtained in the first step are utilized. Keywords: Extended growth curve model; Grouped data; Krylov space; PLS; Two-step method (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:139:y:2015:i:c:p:347-359 Ordering information: This journal article can be ordered from DOI: 10.1016/j.jmva.2015.03.011 Access Statistics for this article Journal of Multivariate Analysis is currently edited by de Leeuw, J. More articles in Journal of Multivariate Analysis from Elsevier |
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