Universidad Complutense de Madrid
E-Prints Complutense

Recursive estimation in linear models with general errors and grouped data: a median-based procedure and related asymptotics

Impacto

Downloads

Downloads per month over past year



Anido, Carmen and Rivero, Carlos and Valdés Sánchez, Teófilo (2003) Recursive estimation in linear models with general errors and grouped data: a median-based procedure and related asymptotics. Journal of Statistical Planning and Inference, 115 (1). pp. 85-102. ISSN 0378-3758

[img] PDF
Restringido a Repository staff only

175kB

Official URL: http://www.sciencedirect.com/science/article/pii/S0378375802001143


URLURL Type
http://www.sciencedirect.com/Publisher


Abstract

We introduce in this paper an iterative estimation procedure based on conditional medians valid to fit linear models when, on the one hand, the distribution of errors, assumed to be known, may be general and, on the other, the dependent data stem from different sources and, consequently, may be either non-grouped or grouped with different classification criteria. The procedure requires us at each step to interpolate the grouped data and is similar to the EM algorithm with normal errors. The expectation step has been replaced by a median-based step which avoids doing awkward integration with general errors and, also, we have substituted for the maximisation step, a natural one which only coincides with it when the errors are normally distributed. With these modifications, we have proved that the iterative estimating algorithm converges to a point which is unique and non-dependent on the starting values. Finally, our final estimate, being a Huber type M-estimator, may enjoy good stochastic asymptotic proper-ties which have also been investigated in detail


Item Type:Article
Uncontrolled Keywords:Censored-data; maximum-likelihood; em algorithm; regression; iterative estimation; median-based imputation; grouped data; linear models; convergence rate; asymptotic distributions; consistency
Subjects:Sciences > Mathematics > Mathematical statistics
ID Code:20225
Deposited On:04 Mar 2013 15:53
Last Modified:09 Aug 2018 08:36

Origin of downloads

Repository Staff Only: item control page