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Splines are useful building blocks when constructing priors on nonparametric models indexed by functions. Recently it has been established in the literature that hierarchical priors based on splines w...
This paper discusses asymptotic theory for penalized spline estimators in generalized additive models. The purpose of this paper is to establish the asymptotic bias and variance as well as the asympto...
Observational time series data often exhibit both cyclic temporal trends and autocorrelation and may also depend on covariates. As such, there is a need for exible regression models that are able to c...
The unceasing demand for continuous situational awareness calls for innovative and large-scale signal processing algorithms, complemented by collaborative and adaptive sensing platforms to accomplish...
Conventional spline procedures have proven to be effective and useful for estimating smooth functions. However, these procedures find piecewise and inhomogeneous smooth functions difficult to handle. ...
The paper considers functional linear regression, where scalar responses Y1, . . . ,Yn are modeled in dependence of random functions X1, . . . ,Xn. We propose a smoothing splines estimator for the f...
This is an expos´e on the use of O’Sullivan penalised splines in contemporary semiparametric regression, including mixed model and Bayesian formulations. O’Sullivan penalised splines are simil...

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