In this paper we give some results of statistical inference for bilinear stochastic processes, obtained by methods of recursive parametric and functional non parametric estimation
A response approximation method for stochastically excited, nonlinear, dynamic systems is presented....
Data sets in numerous areas of application can be modelled by symmetric bivariate nonnormal distribu...
Abstract. It is well known that estimating bilinear models is quite challenging. Many different idea...
Graduation date: 1988In engineering, biology, ecology, medicine, economics and social\ud science, so...
Statistical Inference for Fractional Diffusion Processes looks at statistical inference for stochast...
Wichelhaus C, Langrock R. Nonparametric inference for stochastic feedforward networks based on cross...
The paper introduces a t-ratio type test for detecting bilinearity in a stochastic unit root process...
AbstractThe paper concerns the bilinear stochastic models generated by Gaussian white noise processe...
This is a survey of some aspects of large-sample inference for stochastic processes. A unified frame...
The aim of the paper is to find the univariate stationary distribution of a particular bilinear pro...
The aim of this volume is to provide an extensive account of the most recent advances in statistics ...
This research focuses on the estimation of a class of econometric models for involved unknown nonlin...
The goal of the current research project is the formulation of a method for the estimation and model...
A new methodology, based on the asymptotic separation of probability laws, was introduced by Gonçalv...
In this paper, we extend the integer-valued model class to give a nonnegative integer-valued bilinea...
A response approximation method for stochastically excited, nonlinear, dynamic systems is presented....
Data sets in numerous areas of application can be modelled by symmetric bivariate nonnormal distribu...
Abstract. It is well known that estimating bilinear models is quite challenging. Many different idea...
Graduation date: 1988In engineering, biology, ecology, medicine, economics and social\ud science, so...
Statistical Inference for Fractional Diffusion Processes looks at statistical inference for stochast...
Wichelhaus C, Langrock R. Nonparametric inference for stochastic feedforward networks based on cross...
The paper introduces a t-ratio type test for detecting bilinearity in a stochastic unit root process...
AbstractThe paper concerns the bilinear stochastic models generated by Gaussian white noise processe...
This is a survey of some aspects of large-sample inference for stochastic processes. A unified frame...
The aim of the paper is to find the univariate stationary distribution of a particular bilinear pro...
The aim of this volume is to provide an extensive account of the most recent advances in statistics ...
This research focuses on the estimation of a class of econometric models for involved unknown nonlin...
The goal of the current research project is the formulation of a method for the estimation and model...
A new methodology, based on the asymptotic separation of probability laws, was introduced by Gonçalv...
In this paper, we extend the integer-valued model class to give a nonnegative integer-valued bilinea...
A response approximation method for stochastically excited, nonlinear, dynamic systems is presented....
Data sets in numerous areas of application can be modelled by symmetric bivariate nonnormal distribu...
Abstract. It is well known that estimating bilinear models is quite challenging. Many different idea...
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