<abstract xmlns="http://www.w3.org/1999/xhtml"><p> The structural linear model is considered that is an errors-in- -variables model where the unobserved variables are i.i.d. In this model we can find linear transformations depending on the parameter, such that the transformed observations using the true parameter are uncorrelated. Then a parameter estimator is defined as a zero point of a consistent correlation estimator. A rank estimation is proposed as a zero point of Kendall’s correlation measure and its consistency is shown. While the Pearson estimate of the covariance delivers the total least squares estimate.</p></abstract>

The structural linear model is considered that is an errors-in- -variables model where the unobserved variables are i.i.d. In this model we can find linear transformations depending on the parameter, such that the transformed observations using the true parameter are uncorrelated. Then a parameter estimator is defined as a zero point of a consistent correlation estimator. A rank estimation is proposed as a zero point of Kendall’s correlation measure and its consistency is shown. While the Pearson estimate of the covariance delivers the total least squares estimate.

On a consistent rank estimate in a linear structural model

Department of Mathematics Uppsala University P.O. Box 480 SE–75106 Uppsala SWEDEN

Tatra Mountains Mathematical Publications

{"article-title":"On a consistent rank estimate in a linear structural model"}

The structural linear model is considered that is an errors-in- -variables model where the unobserved variables are i.i.d. In this model we can find linear...

On a consistent rank estimate in a linear structural model

Online veröffentlicht: 13. Nov. 2012

Seitenbereich: 191 - 202

DOI: https://doi.org/10.2478/v10127-012-0019-7

Schlüsselwörter
rank estimate, structural linear model, Kendall’s tau, total least squares, Theil-Sen estimate.

This content is open access.

On a consistent rank estimate in a linear structural model

Online veröffentlicht: 13. Nov. 2012

Seitenbereich: 191 - 202

DOI: https://doi.org/10.2478/v10127-012-0019-7

Schlüsselwörterrank estimate, structural linear model, Kendall’s tau, total least squares, Theil-Sen estimate.

This content is open access.

Schlüsselwörter
rank estimate, structural linear model, Kendall’s tau, total least squares, Theil-Sen estimate.