Abstract
We consider a dynamic linear regression model with errors-in-covariate. Neglecting such errors has some undesirable effects on the estimates obtained with the Kalman Filter. We propose a modification of the Kalman Filter where the perturbed covariate is replaced with a suitable function of a local cluster of covariates. Some results of both a simulation experiment and an application are reported.
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Mantovan, P., Pastore, A. (2010). Covariate Error Bias Effects in Dynamic Regression Model Estimation and Improvement in the Prediction by Covariate Local Clusters. In: Palumbo, F., Lauro, C., Greenacre, M. (eds) Data Analysis and Classification. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03739-9_32
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DOI: https://doi.org/10.1007/978-3-642-03739-9_32
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