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Economic indicators time series are usually complex with high frequency data. The traditional time series methodology requires at least a preliminary transformation of the data to get stationarity. On...
Following a series of high-pro le drug safety disasters in recent years, many countries are redoubling their e orts to ensure the safety of licensed medical products. Large-scale observa-tional databa...
Sparse linear (or generalized linear) models combine a standard likelihood func-tion with a sparse prior on the unknown coefficients. These priors can conve- niently be expressed as a maximization ov...
Linear models with a growing number of parameters have been widely used in modern statistics. One important problem about this kind of model is the variable selection issue. Bayesian approaches, which...
Consistency of M-estimators in a linear model, generated by nonmonotone and discontinuous psi-functions。
M-estimators of regression parameter vector in linear model, studentized by a suitable afine-invariant and scale-equivariant scale statistic, become a n e - and scale-equivariant. We study some asy...
Intheconjugate priorforthenormallinear model, theprior variancefor the coecients is a multiple of the error variance parameter. However, if the prior mean for the coecients is poorly chosen, the pos...
A random linear model for spatially located sensors measured intensity of a source of signals in discrete instants of time is considered. A characterization of admissible quadratic estimators of th...
The problem of prediction in functional linear regression is conventionally addressed by reducing dimension via the standard principal component basis. In this paper we show that weighted least-square...
In several applications data are grouped and there are within-group correlations.With continuous data, there are several available models that are often used; with counting data, the Poisson distribut...
The problem of prediction in functional linear regression is conventionally addressed by reducing dimension via the standard principal component basis. In this paper we show that an alternative basi...
We consider the problem of estimating for a given representer h the value ℓh(β) of a linear functional of the slope parameter β in functional linear regression, where scalar responses Y1, . . ...

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