AbstractIn this paper we consider a general linear model in a continuous time. We propose a decomposition of the process which helps us to understand the structure of the model. Moreover, the sufficiency of the BLUE estimator of the expectation of the process can be characterized in terms of the Gaussian character of a component of the decomposition
AbstractIn the general Gauss-Markoff model (Y, Xβ, σ2V), when V is singular, there exist linear func...
Abstract This paper derives a methodology for the estimation of continuous-time stochastic models ba...
In this paper, we present an algorithm for decomposing time series based on Gaussian processes. Gaus...
AbstractIn this paper we consider a general linear model in a continuous time. We propose a decompos...
AbstractIn this paper we consider the estimation problem in a continuous time linear model. We estab...
AbstractThe problem of building a linear stationary model for a process given by evenly spaced discr...
In this paper, the problem of best linear unbiased estimation is investigated for continuous-time re...
AbstractThis paper considers the problem of estimation in a linear model when a stochastic process i...
The general linear model with correlated error variables can be transformed by means of the generali...
AbstractNecessary and sufficient conditions are derived for the BLUE in a general multiple-partition...
Here we present a nearly complete treatment of the Grand Universe of linear and weakly nonlinear reg...
We describe a simple procedure for decomposing a vector of time series into trend, cycle, seasonal a...
Two new approaches for reducing the order of large scale continuous systems are presented. The first...
AbstractA new derivation is given for the generalized singular value decomposition of two matrices X...
This thesis is concerned with the estimation of parameters in continuous-time systems, when the ava...
AbstractIn the general Gauss-Markoff model (Y, Xβ, σ2V), when V is singular, there exist linear func...
Abstract This paper derives a methodology for the estimation of continuous-time stochastic models ba...
In this paper, we present an algorithm for decomposing time series based on Gaussian processes. Gaus...
AbstractIn this paper we consider a general linear model in a continuous time. We propose a decompos...
AbstractIn this paper we consider the estimation problem in a continuous time linear model. We estab...
AbstractThe problem of building a linear stationary model for a process given by evenly spaced discr...
In this paper, the problem of best linear unbiased estimation is investigated for continuous-time re...
AbstractThis paper considers the problem of estimation in a linear model when a stochastic process i...
The general linear model with correlated error variables can be transformed by means of the generali...
AbstractNecessary and sufficient conditions are derived for the BLUE in a general multiple-partition...
Here we present a nearly complete treatment of the Grand Universe of linear and weakly nonlinear reg...
We describe a simple procedure for decomposing a vector of time series into trend, cycle, seasonal a...
Two new approaches for reducing the order of large scale continuous systems are presented. The first...
AbstractA new derivation is given for the generalized singular value decomposition of two matrices X...
This thesis is concerned with the estimation of parameters in continuous-time systems, when the ava...
AbstractIn the general Gauss-Markoff model (Y, Xβ, σ2V), when V is singular, there exist linear func...
Abstract This paper derives a methodology for the estimation of continuous-time stochastic models ba...
In this paper, we present an algorithm for decomposing time series based on Gaussian processes. Gaus...
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