AbstractThe strong consistency of least squares estimates in multiple regression models is established under minimal assumptions on the design and weak dependence and moment restrictions on the errors
Convex regression is concerned with computing the best fit of a convex function to a data set of n o...
The consistency and the asymptotic normality of the least weighted squares is proved and its asympto...
This paper considers the linear regression model with multiple stochastic regressors, intercept, and...
AbstractThe strong consistency of least squares estimates in multiple regression models is establish...
AbstractA recent theorem of T. L. Hai, H. Robbins, and C. Z. Wei (J. Multivariate Anal. 9 (1979), 34...
AbstractMultiple linear regression models with non random regressors in continuous time are consider...
SIGLECNRS RS 17660 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc
Sufficient conditions are given to ensure the existence of a sequence of strongly consistent estimat...
The paper presents an estimator of the errors-in-variables in multiple regressions using only first ...
Sufficient conditions are given to ensure the existence of a sequence of strongly consistent estimat...
SIGLEBibliothek Weltwirtschaft Kiel C117,312 / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Tech...
A vector autoregression with deterministic terms and with no restrictions to its characteristic root...
A vector autoregression with deterministic terms and with no restrictions to its characteristic root...
SIGLETIB: RO 3009 (39) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische Informationsbib...
summary:The least squres invariant quadratic estimator of an unknown covariance function of a stocha...
Convex regression is concerned with computing the best fit of a convex function to a data set of n o...
The consistency and the asymptotic normality of the least weighted squares is proved and its asympto...
This paper considers the linear regression model with multiple stochastic regressors, intercept, and...
AbstractThe strong consistency of least squares estimates in multiple regression models is establish...
AbstractA recent theorem of T. L. Hai, H. Robbins, and C. Z. Wei (J. Multivariate Anal. 9 (1979), 34...
AbstractMultiple linear regression models with non random regressors in continuous time are consider...
SIGLECNRS RS 17660 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc
Sufficient conditions are given to ensure the existence of a sequence of strongly consistent estimat...
The paper presents an estimator of the errors-in-variables in multiple regressions using only first ...
Sufficient conditions are given to ensure the existence of a sequence of strongly consistent estimat...
SIGLEBibliothek Weltwirtschaft Kiel C117,312 / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Tech...
A vector autoregression with deterministic terms and with no restrictions to its characteristic root...
A vector autoregression with deterministic terms and with no restrictions to its characteristic root...
SIGLETIB: RO 3009 (39) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische Informationsbib...
summary:The least squres invariant quadratic estimator of an unknown covariance function of a stocha...
Convex regression is concerned with computing the best fit of a convex function to a data set of n o...
The consistency and the asymptotic normality of the least weighted squares is proved and its asympto...
This paper considers the linear regression model with multiple stochastic regressors, intercept, and...
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