Add to ORKGThe most part of the paper is about modeling (or approximating) nonstochastic regressors. Examples of regressors which are (not) L2-approximable are given. Applications to central limit theory and OLS estimator asymptotics are provided
A comprehensive description is given of the limiting behaviour of normalised pseudo-MLEs of the coef...
We find the asymptotic distribution of the OLS estimator of the parameters $% \beta$ and $\rho$ in t...
This paper deals with inference in a class of stable but nearly-unstable processes. Autoregressive p...
The most part of the paper is about modeling (or approximating) nonstochastic regressors. Examples o...
We propose a general method of modeling deterministic trends for autoregressions. The method relies ...
AbstractThe properties of L2-approximable sequences established here form a complete toolkit for sta...
The properties of $L_2$-approximable sequences established here form a complete toolkit for statisti...
We consider a mixed vector autoregressive model with deterministic exogenous regressors and an autor...
Standardized slowly varying regressors are shown to be $L_p$-approximable. This fact allows one to r...
Weak consistency and asymptotic normality of the ordinary least-squares estimator in a linear regres...
We investigate the asymptotic behavior of the OLS estimator for regressions with two slowly varying ...
We find the asymptotics of the OLS estimator of the parameters $\beta$ and $\rho$ in the spatial aut...
We build the Conditional Least Squares Estimator of 0 based on the observation of a single trajecto...
AbstractAlmost sure convergence properties of least-squares estimates in stochastic regression model...
The first part of this thesis considers the residual empirical process of a nearly unstable long-mem...
A comprehensive description is given of the limiting behaviour of normalised pseudo-MLEs of the coef...
We find the asymptotic distribution of the OLS estimator of the parameters $% \beta$ and $\rho$ in t...
This paper deals with inference in a class of stable but nearly-unstable processes. Autoregressive p...
The most part of the paper is about modeling (or approximating) nonstochastic regressors. Examples o...
We propose a general method of modeling deterministic trends for autoregressions. The method relies ...
AbstractThe properties of L2-approximable sequences established here form a complete toolkit for sta...
The properties of $L_2$-approximable sequences established here form a complete toolkit for statisti...
We consider a mixed vector autoregressive model with deterministic exogenous regressors and an autor...
Standardized slowly varying regressors are shown to be $L_p$-approximable. This fact allows one to r...
Weak consistency and asymptotic normality of the ordinary least-squares estimator in a linear regres...
We investigate the asymptotic behavior of the OLS estimator for regressions with two slowly varying ...
We find the asymptotics of the OLS estimator of the parameters $\beta$ and $\rho$ in the spatial aut...
We build the Conditional Least Squares Estimator of 0 based on the observation of a single trajecto...
AbstractAlmost sure convergence properties of least-squares estimates in stochastic regression model...
The first part of this thesis considers the residual empirical process of a nearly unstable long-mem...
A comprehensive description is given of the limiting behaviour of normalised pseudo-MLEs of the coef...
We find the asymptotic distribution of the OLS estimator of the parameters $% \beta$ and $\rho$ in t...
This paper deals with inference in a class of stable but nearly-unstable processes. Autoregressive p...