| lpint-package {lpint} | R Documentation |
Local Polynomail Estimators of the Intensity Function of a Counting Process and Its Derivatives
Description
Estimates the intensity function or its derivative of a give a given order using the local polynomial method with automatic bandwidth selection using a rule of thumb plug-in approach.
Details
| Package: | lpint |
| Type: | Package |
| Version: | 1.0 |
| Date: | 2012-09-21 |
| License: | GPL (>=2.0) |
| LazyLoad: | yes |
Author(s)
Feng Chen <feng.chen@unsw.edu.au> Maintainer: Feng Chen <feng.chen@unsw.edu.au>
References
Chen, F. (2011) Maximum local partial likelihood estimators for the counting process intensity function and its derivatives. Statistica Sinica 21(1): 107 -128. http://www3.stat.sinica.edu.tw/statistica/j21n1/J21N14/J21N14.html
Chen, F., Yip, P.S.F., & Lam, K.F. (2011) On the Local Polynomial Estimators of the Counting Process Intensity Function and its Derivatives. Scandinavian Journal of Statistics 38(4): 631 - 649. http://dx.doi.org/10.1111/j.1467-9469.2011.00733.x
Chen, F., Higgins, R.M., Yip, P.S.F. & Lam, K.F. (2008) Nonparametric estimation of multiplicative counting process intensity functions with an application to the Beijing SARS epidemic, Communications in Statistics - Theory and Methods 37: 294 - 306. http://www.tandfonline.com/doi/abs/10.1080/03610920701649035
Chen, F., Higgins, R.M., Yip, P.S.F. & Lam, K.F. (2008) Local polynomial estimation of Poisson intensities in the presence of reporting delays, Journal of the Royal Statistical Society Series C (Applied Statistics) 57(4): 447 - 459. http://onlinelibrary.wiley.com/doi/10.1111/j.1467-9876.2008.00624.x/full