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.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Carroll, R., Ruppert, D., Stefanski, L. A., & Crainiceanu, L. M. (2006). Measurement error in nonlinear models (2nd edition). Boca Raton: Chapman and Hall/CRC.
Chowdhury, S., & Sharma, A. (2007). Mitigating parmeter bias in hydrological modelling due to uncertainty in covariates. Journal of Hydrology, 340, 197–204.
Cook, J. R., & Stefanski, L. A. (1994). Simulation-extrapolation estimation in parametric measurement error models. Journal of the American Statistical Association, 89(428), 1314–1328.
Fuller, W. A. (1986). Measurement error models. New York: Wiley.
Kalman, R. E. (1960). A new approach to linear filtering and prediction problems. Journal of Basic Engineering, 82, 35–45.
Mantovan, P., & Pastore, A. (2004). Flexible dynamic regression models for real-time forecasting of air pollutant concentration. In: H. H. Bock, M. Chiodi, & A. Mineo (Eds.), Advances in multivariate data analysis (pp. 265–276). Berlin: Springer.
Mantovan, P., Pastore, A., & Tonellato, S. (1999). A comparison between parallel algorithms for system parameter estimation in dynamic linear models. Applied Stochastic Models in Business and Industry, 15, 369–378.
Marshall, A. W., & Olkin, I. (1979). Inequalities – Theory of majorization and its applications. New York: Academic.
West, M., & Harrison, J. (1997). Bayesian forecasting and dynamic models (2nd edition). New York: Springer.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-642-03739-9_32
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03738-2
Online ISBN: 978-3-642-03739-9
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)