References

1. Richardson HR, Stone LD, Monach WR, Discenza JH. Early maritime applications of particle filtering. Signal and Data Processing of Small Targets, Proceedings of SPIE, Vol. 5204, 2003, pp. 165–174.

2. Agnew DC, Constable C. Geophysical Data Analysis. [Online] http://mahi.ucsd.edu/cathy/ Classes/SIO223/Part1/. Chapter 9. 2005.

3. Scott DW. Multivariate density estimation and visualization. In Handbook of Statistics, Vol. 23: Data Mining and Computational Statistics. Springer; 2004.

4. Patlolla R. 2-Dimensional histogram. [Online] http://www.mathworks.com/matlabcentral/fileexchange/8422. 2005.

5. Fukunaga K. Introduction to Statistical Pattern Recognition, 2nd ed. Academic Press, 1990.

6. Silverman BW. Density Estimation for Statistics and Data Analysis. New York: Chapman and Hall; 1986.

7. Turlach BA. Bandwidth selection in Kernel density estimation: a review. In CORE Institut Stat 1993;23–49.

8. Musso C, Oudjane N, Le Gland F. Improving regularized particle filters. In Doucet A, de Freita N, Gordon G, editors. Sequential Monte Carlo Methods in Practice. Springer; 2001.

9. Wand MP, Jones MC. Comparison of smoothing parameterization in bivariate Kernel density estimation. J. Am. Stat. Soc. 1993;88(422):520–528.

10. Zhang X, King ML, Hyndman RJ. Bandwidth selection for multivariate Kernel density estimation using MCMC. Comp. Stat. Data Anal. 2006;50:3009–3031.

11. Wikipedia. [Online] http://en.wikipedia.org/wiki/Kernel_(statistics).

12. Botev Z. Two-Dimensional Kernel ...

Get Bayesian Estimation and Tracking: A Practical Guide now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.