On the rates of convergence for moments convergence in regression models

João Lita da Silva

doi:10.1007/s11749-017-0561-3

On the rates of convergence for moments convergence in regression models

Research output: Contribution to journal › Article › peer-review

Abstract

In one-dimensional regression models, we establish a rate for the rth moment convergence (Formula presented.) of the ordinary least-squares estimator involving explicitly the regressors, answering to an open question raised lately by Afendras and Markatou (Test 25:775–784, 2016). An extension of the classic Theorem 2.6.1 of Anderson (The statistical analysis of time series, Wiley, New York, 1971) is also presented.

Original language	English
Pages (from-to)	477-495
Number of pages	19
Journal	Test
Volume	27
Issue number	2
DOIs	https://doi.org/10.1007/s11749-017-0561-3
Publication status	Published - 1 Jun 2018

Keywords

Linear regression model
Moment convergence
Rate of convergence

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On the rates of convergence for moments convergence in regression models

Abstract

Keywords

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