 Consistent test of error-in-variables partially linear model with auxiliary variablesZhihua Sun, Xue Ye and Liuquan Sun Journal of Multivariate Analysis, 2015, vol. 141, issue C, 118-131 Abstract: In this paper, we investigate the model checking problem of a partially linear model when some covariates are measured with error and some auxiliary variables are supplied. The often-used assumptions on the measurement error, such as a known error variance or a known distribution of the error variable, are not required. Also repeated measurements are not needed. Instead, a nonparametric calibration method is applied to deal with the measurement error. An estimating method for the null hypothetical model is proposed and the asymptotic properties of the proposed estimators are established. A testing method based on a residual-marked empirical process is then developed to check the null hypothetical partially linear model. The tests are shown to be consistent and can detect the alternative hypothesis close to the null hypothesis at the rate n−r with 0≤r≤1/2. Simulation studies and real data analysis are conducted to examine the finite sample behavior of the proposed methods. Keywords: Auxiliary variable; Consistent test; Measurement error; Model check; Partial linear model (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:141:y:2015:i:c:p:118-131 Ordering information: This journal article can be ordered from DOI: 10.1016/j.jmva.2015.07.007 Access Statistics for this article Journal of Multivariate Analysis is currently edited by de Leeuw, J. More articles in Journal of Multivariate Analysis from Elsevier |
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