Wyniki wyszukiwania

1

Artykuł dostępny w postaci pełnego tekstu - kliknij by otworzyć plik

Least squares estimator consistency: a geometric approach

100%

Mexia J., da Silva J.

Discussiones Mathematicae Probability and Statistics

|

2006

|

tom 26

|

nr 1

19-45

EN

Consistency of LSE estimator in linear models is studied assuming that the error vector has radial symmetry. Generalized polar coordinates and algebraic assumptions on the design matrix are considered in the results that are established.

2

On the matrix form of Kronecker lemma

100%

da Silva J., Oliveira A.

Discussiones Mathematicae Probability and Statistics

|

2009

|

tom 29

|

nr 2

233-243

EN

A matrix generalization of Kronecker's lemma is presented with assumptions that make it possible not only the unboundedness of the condition number considered by Anderson and Moore (1976) but also other sequences of real matrices, not necessarily monotone increasing, symmetric and nonnegative definite. A useful matrix decomposition and a well-known equivalent result about convergent series are used in this generalization.

3

Sufficient conditions for the strong consistency of least squares estimator with α-stable errors

100%

Mexia J., da Silva J.

Discussiones Mathematicae Probability and Statistics

|

2007

|

tom 27

|

nr 1-2

27-45

EN

Let $Y_{i} = x_{i}^{T}β + e_{i}$, 1 ≤ i ≤ n, n ≥ 1 be a linear regression model and suppose that the random errors e₁, e₂, ... are independent and α-stable. In this paper, we obtain sufficient conditions for the strong consistency of the least squares estimator β̃ of β under additional assumptions on the non-random sequence x₁, x₂,... of real vectors.

Ograniczanie wyników

3 Discussiones Mathematicae Probability and Statistics

3 da Silva J.

2 Mexia J.

1 Oliveira A.

1 2009

1 2007

1 2006

Least squares estimator consistency: a geometric approach

On the matrix form of Kronecker lemma

Sufficient conditions for the strong consistency of least squares estimator with α-stable errors