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.
(Publisher abstract provided.)
Downloads
Similar Publications
- Spectroscopic Differentiation and Regioisomeric Indole Aldehydes: Synthetic Cannabinoids Precursors
- Examination of DNA Yield Rates for Different Skeletal Elements at Increasing Post Mortem Intervals
- Eutylone (bk-EBDB) and Benzylone (BMDP): Increasing Prevalence of New Synthetic Stimulants in the United States