# The two-dimensional linear relation in the errors-in-variables model with replication of one variable

Anna Czapkiewicz; Antoni Dawidowicz

Applicationes Mathematicae (2000)

- Volume: 27, Issue: 3, page 335-342
- ISSN: 1233-7234

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topCzapkiewicz, Anna, and Dawidowicz, Antoni. "The two-dimensional linear relation in the errors-in-variables model with replication of one variable." Applicationes Mathematicae 27.3 (2000): 335-342. <http://eudml.org/doc/219277>.

@article{Czapkiewicz2000,

abstract = {We present a two-dimensional linear regression model where both variables are subject to error. We discuss a model where one variable of each pair of observables is repeated. We suggest two methods to construct consistent estimators: the maximum likelihood method and the method which applies variance components theory. We study asymptotic properties of these estimators. We prove that the asymptotic variances of the estimators of regression slopes for both methods are comparable.},

author = {Czapkiewicz, Anna, Dawidowicz, Antoni},

journal = {Applicationes Mathematicae},

keywords = {consistent estimator; linear regression},

language = {eng},

number = {3},

pages = {335-342},

title = {The two-dimensional linear relation in the errors-in-variables model with replication of one variable},

url = {http://eudml.org/doc/219277},

volume = {27},

year = {2000},

}

TY - JOUR

AU - Czapkiewicz, Anna

AU - Dawidowicz, Antoni

TI - The two-dimensional linear relation in the errors-in-variables model with replication of one variable

JO - Applicationes Mathematicae

PY - 2000

VL - 27

IS - 3

SP - 335

EP - 342

AB - We present a two-dimensional linear regression model where both variables are subject to error. We discuss a model where one variable of each pair of observables is repeated. We suggest two methods to construct consistent estimators: the maximum likelihood method and the method which applies variance components theory. We study asymptotic properties of these estimators. We prove that the asymptotic variances of the estimators of regression slopes for both methods are comparable.

LA - eng

KW - consistent estimator; linear regression

UR - http://eudml.org/doc/219277

ER -

## References

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