Likelihood-based kernel estimation in semiparametric errors-in-covariables models with validation data

Qihua Wang and Keming Yu

Journal of Multivariate Analysis, 2007, vol. 98, issue 3, 455-480

Abstract: We present methods to handle error-in-variables models. Kernel-based likelihood score estimating equation methods are developed for estimating conditional density parameters. In particular, a semiparametric likelihood method is proposed for sufficiently using the information in the data. The asymptotic distribution theory is derived. Small sample simulations and a real data set are used to illustrate the proposed estimation methods.

Keywords: Conditional; density; estimation; Empirical; likelihood; Kernel; estimation; Measurement; error; Surrogate; variables (search for similar items in EconPapers)
Date: 2007
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Citations: View citations in EconPapers (4)

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