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

João Tiago Mexia; João Lita da Silva

Discussiones Mathematicae Probability and Statistics (2007)

- Volume: 27, Issue: 1-2, page 27-45
- ISSN: 1509-9423

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topJoão Tiago Mexia, and João Lita da Silva. "Sufficient conditions for the strong consistency of least squares estimator with α-stable errors." Discussiones Mathematicae Probability and Statistics 27.1-2 (2007): 27-45. <http://eudml.org/doc/277074>.

@article{JoãoTiagoMexia2007,

abstract = {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.},

author = {João Tiago Mexia, João Lita da Silva},

journal = {Discussiones Mathematicae Probability and Statistics},

keywords = {linear models; least squares estimator; strong consistency; stability; least squares estimates; regression models; Marcinkiewicz-Zygmund law; undefined errors mean values},

language = {eng},

number = {1-2},

pages = {27-45},

title = {Sufficient conditions for the strong consistency of least squares estimator with α-stable errors},

url = {http://eudml.org/doc/277074},

volume = {27},

year = {2007},

}

TY - JOUR

AU - João Tiago Mexia

AU - João Lita da Silva

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

JO - Discussiones Mathematicae Probability and Statistics

PY - 2007

VL - 27

IS - 1-2

SP - 27

EP - 45

AB - 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.

LA - eng

KW - linear models; least squares estimator; strong consistency; stability; least squares estimates; regression models; Marcinkiewicz-Zygmund law; undefined errors mean values

UR - http://eudml.org/doc/277074

ER -

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