Introduction to “Fast matrix computations for functional additive models” by S. Barthelmé

Statistics and Computing, Nov 2014

Håvard Rue

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Introduction to “Fast matrix computations for functional additive models” by S. Barthelmé

Hvard Rue 0 0 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. - 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 (...truncated)


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Håvard Rue. Introduction to “Fast matrix computations for functional additive models” by S. Barthelmé, Statistics and Computing, 2015, pp. 45-45, Volume 25, Issue 1, DOI: 10.1007/s11222-014-9527-4