If you are experiencing problems downloading PDF or HTML fulltext, our helpdesk recommend clearing your browser cache and trying again. If you need help in clearing your cache, please click here . Still need help? Email help@ingentaconnect.com

Semiparametric estimators of functional measurement error models with unknown error

$48.00 plus tax (Refund Policy)

Download / Buy Article:

Abstract:

Summary. 

We consider functional measurement error models where the measurement error distribution is estimated non-parametrically. We derive a locally efficient semiparametric estimator but propose not to implement it owing to its numerical complexity. Instead, a plug-in estimator is proposed, where the measurement error distribution is estimated through non-parametric kernel methods based on multiple measurements. The root n consistency and asymptotic normality of the plug-in estimator are derived. Despite the theoretical inefficiency of the plug-in estimator, simulations demonstrate its near optimal performance. Computational advantages relative to the theoretically efficient estimator make the plug-in estimator practically appealing. Application of the estimator is illustrated by using the Framingham data example.

Keywords: Errors in variables; Latent variables; Measurement error; Semiparametric efficiency; Semiparametric methods

Document Type: Research Article

DOI: http://dx.doi.org/10.1111/j.1467-9868.2007.00596.x

Affiliations: 1: Australian National University, Canberra, Australia 2: Texas A&M University, College Station, USA

Publication date: June 1, 2007

Related content

Tools

Favourites

Share Content

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
X
Cookie Policy
ingentaconnect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more