Asymptotics for weakly dependent errors-in-variables

Pešta, Michal. "Asymptotics for weakly dependent errors-in-variables." Kybernetika 49.5 (2013): 692-704. <http://eudml.org/doc/260730>.

@article{Pešta2013,
abstract = {Linear relations, containing measurement errors in input and output data, are taken into account in this paper. Parameters of these so-called errors-in-variables (EIV) models can be estimated by minimizing the total least squares (TLS) of the input-output disturbances. Such an estimate is highly non-linear. Moreover in some realistic situations, the errors cannot be considered as independent by nature. Weakly dependent ($\alpha $- and $\varphi $-mixing) disturbances, which are not necessarily stationary nor identically distributed, are considered in the EIV model. Asymptotic normality of the TLS estimate is proved under some reasonable stochastic assumptions on the errors. Derived asymptotic properties provide necessary basis for the validity of block-bootstrap procedures.},
author = {Pešta, Michal},
journal = {Kybernetika},
keywords = {errors-in-variables (EIV); dependent errors; total least squares (TLS); asymptotic normality; errors-in-variables (EIV); dependent errors; total least squares (TLS); asymptotic normality},
language = {eng},
number = {5},
pages = {692-704},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Asymptotics for weakly dependent errors-in-variables},
url = {http://eudml.org/doc/260730},
volume = {49},
year = {2013},
}

TY - JOUR
AU - Pešta, Michal
TI - Asymptotics for weakly dependent errors-in-variables
JO - Kybernetika
PY - 2013
PB - Institute of Information Theory and Automation AS CR
VL - 49
IS - 5
SP - 692
EP - 704
AB - Linear relations, containing measurement errors in input and output data, are taken into account in this paper. Parameters of these so-called errors-in-variables (EIV) models can be estimated by minimizing the total least squares (TLS) of the input-output disturbances. Such an estimate is highly non-linear. Moreover in some realistic situations, the errors cannot be considered as independent by nature. Weakly dependent ($\alpha $- and $\varphi $-mixing) disturbances, which are not necessarily stationary nor identically distributed, are considered in the EIV model. Asymptotic normality of the TLS estimate is proved under some reasonable stochastic assumptions on the errors. Derived asymptotic properties provide necessary basis for the validity of block-bootstrap procedures.
LA - eng
KW - errors-in-variables (EIV); dependent errors; total least squares (TLS); asymptotic normality; errors-in-variables (EIV); dependent errors; total least squares (TLS); asymptotic normality
UR - http://eudml.org/doc/260730
ER -