The problem of prediction is considered in a multidimensional setting. Extending an idea presented by Barndorff-Nielsen and Cox, a predictive density for a multivariate random variable of interest is proposed. This density has the form of an estimative density plus a correction term. It gives simultaneous prediction regions with coverage error of smaller asymptotic order than the estimative density. A simulation study is also presented showing the magnitude of the improvement with respect to the estimative method
We present a general modelling method for optimal probability prediction over future observations, i...
This paper proposes a method to construct well-calibrated frequentist prediction regions, with parti...
This paper proposes a method to construct well-calibrated frequentist prediction regions, with parti...
The problem of prediction is considered in a multidimensional setting. Extending an idea presented b...
The specification of multivariate prediction regions, having coverage probability closed to the targ...
This paper concerns the specification of multivariate prediction regions which may be useful in time...
In this work we address the problem of the construction of prediction regions and distribution funct...
In this work we address the problem of prediction in a multidimensional setting. Generalizing a resu...
The goodness of a predictive distribution depends on the aim of the prediction. This presentation i...
AbstractThis paper addresses the problem of estimating the density of a future outcome from a multiv...
This paper presents asymptotically optimal prediction intervals and prediction regions. The predicti...
Suppose we observe X ~ Nm(Aβ, σ2I) and would like to estimate the predictive density p(y|β) of a fut...
In this paper we discuss a robust solution to the problem of prediction. Following Barndorff-Nielsen...
Let X|μ∼Np(μ, vxI) and Y|μ∼Np(μ, vyI) be independent p-dimensional multivariate normal vectors with ...
We present a general modelling method for optimal probability prediction over future observations, i...
This paper proposes a method to construct well-calibrated frequentist prediction regions, with parti...
This paper proposes a method to construct well-calibrated frequentist prediction regions, with parti...
The problem of prediction is considered in a multidimensional setting. Extending an idea presented b...
The specification of multivariate prediction regions, having coverage probability closed to the targ...
This paper concerns the specification of multivariate prediction regions which may be useful in time...
In this work we address the problem of the construction of prediction regions and distribution funct...
In this work we address the problem of prediction in a multidimensional setting. Generalizing a resu...
The goodness of a predictive distribution depends on the aim of the prediction. This presentation i...
AbstractThis paper addresses the problem of estimating the density of a future outcome from a multiv...
This paper presents asymptotically optimal prediction intervals and prediction regions. The predicti...
Suppose we observe X ~ Nm(Aβ, σ2I) and would like to estimate the predictive density p(y|β) of a fut...
In this paper we discuss a robust solution to the problem of prediction. Following Barndorff-Nielsen...
Let X|μ∼Np(μ, vxI) and Y|μ∼Np(μ, vyI) be independent p-dimensional multivariate normal vectors with ...
We present a general modelling method for optimal probability prediction over future observations, i...
This paper proposes a method to construct well-calibrated frequentist prediction regions, with parti...
This paper proposes a method to construct well-calibrated frequentist prediction regions, with parti...