It is sometimes desired to update solutions to systems of equations or other problems as new information is to be appended. Also, a system that is too large to solve directly can often be managed by first solving a part of the system, and then updating the solution with the rest of the system. This updating procedure is often required to be both efficient and stable, and recomputing the solution from scratch may be too costly. Beside efficiency and stability, factors such as storage requirement, simplicity, and applicability are often important. Updating the least squares solution to an over determined system of linear equations can be done in many ways. The method of Recursive Least Squares is simple and efficient, and...
We empirically show that Bayesian inference can be inconsistent under misspecification in simple lin...
International audienceModern science makes use of computer models to reproduce and predict complex p...
Three simplifying conditions are given for obtaining least squares (LS) estimates for a nonlinear su...
It is sometimes desired to update solutions to systems of equations or other problems as new infor...
This paper investigates the Bayesian process of identifying unknown model parameters given prior inf...
In recent years, with widely accesses to powerful computers and development of new computing methods...
The behaviour of many processes in science and engineering can be accurately described by dynamical ...
The book is based on several years of experience of both authors in teaching linear models at variou...
In this thesis, I shall present a matrix form of Backus' theory of linear inference with multiple pr...
The problem of updating a structural model and its associated uncertainties by utilizing dynamic res...
SUMMARY. In this paper we provide exact algebraic expressions for the recalculation of the BLUE, the...
The problem of updating a structural model and its associated uncertainties by utilizing dynamic res...
Identification of linear systems, a priori known to be stable, from input output measurements corrup...
Here we present a nearly complete treatment of the Grand Universe of linear and weakly nonlinear reg...
In computational science it is common to describe dynamic systems by mathematical models in forms of...
We empirically show that Bayesian inference can be inconsistent under misspecification in simple lin...
International audienceModern science makes use of computer models to reproduce and predict complex p...
Three simplifying conditions are given for obtaining least squares (LS) estimates for a nonlinear su...
It is sometimes desired to update solutions to systems of equations or other problems as new infor...
This paper investigates the Bayesian process of identifying unknown model parameters given prior inf...
In recent years, with widely accesses to powerful computers and development of new computing methods...
The behaviour of many processes in science and engineering can be accurately described by dynamical ...
The book is based on several years of experience of both authors in teaching linear models at variou...
In this thesis, I shall present a matrix form of Backus' theory of linear inference with multiple pr...
The problem of updating a structural model and its associated uncertainties by utilizing dynamic res...
SUMMARY. In this paper we provide exact algebraic expressions for the recalculation of the BLUE, the...
The problem of updating a structural model and its associated uncertainties by utilizing dynamic res...
Identification of linear systems, a priori known to be stable, from input output measurements corrup...
Here we present a nearly complete treatment of the Grand Universe of linear and weakly nonlinear reg...
In computational science it is common to describe dynamic systems by mathematical models in forms of...
We empirically show that Bayesian inference can be inconsistent under misspecification in simple lin...
International audienceModern science makes use of computer models to reproduce and predict complex p...
Three simplifying conditions are given for obtaining least squares (LS) estimates for a nonlinear su...