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Introduction to “Fast matrix computations for functional additive models” by S. Barthelmé
Hvard Rue
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Heersink, D.K., Furrer, R.: On Moore-Penrose inverses of quasi- Kronecker structured matrices. Linear Algebra Appl. 436, 561- 570 (2011)
vincingly, how to leverage this new rQK-class to obtain great computational savings doing inference in some Latent Gaussian models for functional data analysis.
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I am very enthusiastic about the very innovative paper Fast
matrix computations for functional additive models by
S. Barthelm, which I find both to be both
methodologically and practically very useful. The characterization of
the new rQK-class of symmetric positive definite matrices
(with inspiration from previous work of Heersink and Furrer
(2011)), defines a new class of matrices which can be
computed with much less computational costs compared to the
general case. Further, the rQK-class is closed under
multiplication and inversion. This adds new tools to the
computational statisticians toolbox, in addition to the well known
computational friendly block-diagoal, Toeplitz, Toeplitz
circulant and sparse matrices. Barthelm demonstrates,
con
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