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A Robust Bayesian Dynamic Linear Model to Detect Abrupt Changes in an Economic Time Series: The Case of Puerto Rico
Dynamic Models Consumer Price Index Bayesian Robustness
2013/4/28
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...
Massive parallelization of serial inference algorithms for a complex generalized linear model
Massive parallelization serial inference algorithms generalized linear model
2012/9/17
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...
Consistency of Bayesian Linear Model Selection With a Growing Number of Parameters
Bayesian model selection growing number of parameters Posterior model consistency consistency of Bayes factor consistency of posterior odds ratio Gibbs sampling
2011/3/18
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
Consistency of M-estimators a linear model discontinuous psi-functions
2009/9/23
Consistency of M-estimators in a linear model, generated by nonmonotone and discontinuous psi-functions。
Affine- and scale-equivariant M-estimators in linear model
Affine- and scale-equivariant M-estimators linear model
2009/9/22
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...
Misinformation in the conjugate prior for the linear model with implications for free-knot spline modelling
Bayes factor BIC model selection nonparametric regression unit information prior
2009/9/21
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...
ON ADMISSIBLE QUADRATIC ESTIMATION IN A SPECIAL LINEAR MODEL
Linear estimator quadratic estimator admissibility quadratic subspace locally best estimator
2009/9/18
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...
Weighted least squares methods for prediction in the functional data linear model
Cross-validation eigenfunction eigenvector functional data analysis mean squared error orthogonal series rate of convergence
2009/9/16
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...
A RANDOM-EFFECTS LOG-LINEAR MODEL WITH POISSON DISTRIBUTIONS
log-linear models grouped data random e® ects mixed models overdispersion iterative reweighted generalized least squares
2009/2/26
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...
Weighted least squares methods for prediction in the functional data linear model
Cross-validation eigenfunction eigenvector functional data analysis functional linear regression mean squared error orthogonal series
2010/3/18
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...
On rate optimal local estimation in functional linear model
Linear functional Orthogonal series estimation Thresholding Linear Galerkin projection Minimax-theory Sobolev space
2010/3/18
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, . . ...