Regularised kernel density estimation for clustered process data

Author:

Chen Qian,Kruger Uwe,Leung Andrew TY

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering

Reference14 articles.

1. An alternative method of cross-validation for the smoothing of density estimates;Bowman;Biometrika,1984

2. The application of principal component analysis and kernel density estimation to enhance process monitoring;Chen;Journal of Control Engineering Practise,2000

3. Chen, Q., Sandoz, D., Wynne, R. J., & Kruger, U. (2000b). Improved kernel density estimation for clustered data using regularization and deconvolution. ACC2000, Chicago, IL, USA 28–30 June, 2000b.

4. Chen, Q., Kruger, U., Meronk, M., & Leung, Y. T. (2001). Kernel density estimation on T2 and Q-statistics for condition monitoring and fault detection. Proceedings of conference on condition monitoring, Oxford, UK, 25–27 June, 2001.

5. Deconvolution with supersmooth distributions;Fan;The Canadian Journal of Statistics,1992

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