Abstract
The theory of Lg-splines developed by Jerome and Schumaker is extended to the vector-valued (multivariate) case. The extension is described in the frame-work of a reproducing-kernel Hilbert space which among other things allows the establishment of a congruent least-squares estimation problem for a vectorvalued lumped random process. The results include a dynamic recursive algorithm for vector-valued Lg-splines with EHB data and a useful structural characterization theorem for such splines. Some results on computable approximation error bounds are also included.
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