Add to ORKGSufficient conditions are given to ensure the existence of a sequence of strongly consistent estimators of an unknown parameter for a nonlinear regression model. The parameter space includes all separable metric spaces but is not assumed to be compact.
AbstractFor a well-known class of nonparametric regression function estimators of nearest neighbor t...
For a well-known class of nonparametric regression function estimators of nearest neighbor type the ...
The strong universal pointwise consistency of some modified versions of the standard regression func...
Sufficient conditions are given to ensure the existence of a sequence of strongly consistent estimat...
Sufficient conditions are given in order to ensure the existence of a sequence of strongly consisten...
Sufficient conditions are given to ensure the existence of a sequence of strongly consistent estimat...
Sufficient conditions are given to ensure the existence of a sequence of strongly consistent estimat...
In this paper, we study conditions sufficient for strong consistency of a class of estimators of par...
A strongly consistent sequence of estimators of the variance of the disturbance term in a nonlinear ...
A strongly consistent sequence of estimators of the variance of the disturbance term in a nonlinear ...
A strongly consistent sequence of estimators of the variance of the disturbance term in a nonlinear ...
Conditions are given which ensure the nonexistence of a sequence of strongly consistent M-estimators...
Conditions are given which ensure the nonexistence of a sequence of strongly consistent M-estimators...
Under the condition that the design space is finite, new sufficient conditions for the strong consis...
Standard consistency proofs of the maximum likelihood estimator rely on the assumption that the obse...
AbstractFor a well-known class of nonparametric regression function estimators of nearest neighbor t...
For a well-known class of nonparametric regression function estimators of nearest neighbor type the ...
The strong universal pointwise consistency of some modified versions of the standard regression func...
Sufficient conditions are given to ensure the existence of a sequence of strongly consistent estimat...
Sufficient conditions are given in order to ensure the existence of a sequence of strongly consisten...
Sufficient conditions are given to ensure the existence of a sequence of strongly consistent estimat...
Sufficient conditions are given to ensure the existence of a sequence of strongly consistent estimat...
In this paper, we study conditions sufficient for strong consistency of a class of estimators of par...
A strongly consistent sequence of estimators of the variance of the disturbance term in a nonlinear ...
A strongly consistent sequence of estimators of the variance of the disturbance term in a nonlinear ...
A strongly consistent sequence of estimators of the variance of the disturbance term in a nonlinear ...
Conditions are given which ensure the nonexistence of a sequence of strongly consistent M-estimators...
Conditions are given which ensure the nonexistence of a sequence of strongly consistent M-estimators...
Under the condition that the design space is finite, new sufficient conditions for the strong consis...
Standard consistency proofs of the maximum likelihood estimator rely on the assumption that the obse...
AbstractFor a well-known class of nonparametric regression function estimators of nearest neighbor t...
For a well-known class of nonparametric regression function estimators of nearest neighbor type the ...
The strong universal pointwise consistency of some modified versions of the standard regression func...