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Hierarchical Penalized Mixed Model

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Document pages: 7 pages

Abstract: Penalized spline has been a popular method for estimating an unknown functionin the non-parametric regression due to their use of low-rank spline bases, which makecomputations tractable. However its performance is poor when estimatingfunctions that are rapidly varying in some regions and are smooth in otherregions. This is contributed by the use of a global smoothing parameter thatprovides a constant amount of smoothing across the function. In order to makethis spline spatially adaptive we have introduced hierarchical penalizedsplines which are obtained by modelling the global smoothing parameter asanother spline.

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