Statistical Papers

, Volume 57, Issue 4, pp 929–938 | Cite as

Inverse prediction for multivariate mixed models with standard software

Regular Article

Abstract

Inverse prediction (IP) is reputed to be computationally inconvenient for multivariate responses. This paper describes how IP can be formulated in terms of a general linear mixed model, along with a flexible modeling approach for both mean vectors and variance–covariance matrices. It illustrates that results can be had as standard output from widely-available statistical computing packages.

Keywords

Heteroscedastic multivariate models Multivariate calibration Forensic entomology 

Mathematics Subject Classification

62H15 62J05 62H30 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.LSU Health Sciences CenterNew OrleansUSA
  2. 2.Florida International UniversityMiamiUSA

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