References
- Albert-Green, A., Braun, W. J., Martell, D.L., Woolford, D. G. (2013). Visualization tools for assessing the Markov property: sojourn times in the Ontario Fire Weather Index. Environmetrics DOI: 10.1002/env.2237.
- Davison, A.C., Hinkley, D.V. (1997). Bootstrap Methods and Their Application. Cambridge:Cambridge University Press.
- Forestry Canada Fire Danger Group. (1992). Development and Structure of the Canadian Forest Fire Behaviour Prediction System. Information Report ST-X-3. OttawaOntario:Forestry Canada.
- Fujioka, F.M., Tsou, T. (1985). Probability modelling of a fire weather index. In: Donoghue, L.R., Martin, R.E., eds. Proceedings of the 8th Conference on Fire and Forest Meteorology. Society of American Foresters, pp. 239–243.
- Hall, P. (1992). The Bootstrap and Edgeworth Expansion. New York: Springer.
- Lee, S. M.S., Lai, P.Y. (2009). Double block bootstrap confidence intervals for dependent data. Biometrika 96:427–443.
- Loh, W.-Y. (1991). Bootstrap calibration for confidence interval construction and selection. Statistica Sinica 1:477–491.
- Martell, D. L. (1999). A Markov chain model of day to day changes in the Canadian Forest Fire Weather Index. International Journal of Wildland Fire 9:265–273.
- Nordman, D.J., Lahiri, S. N., Fridley, B.L. (2007). Optimal block size for variance estimation by a spatial block bootstrap method. Sankhya: The Indian Journal of Statistics Special Issue on Statistics in Biology and Health Sciences 69:468–493.
- R Development Core Team. (2009). R: A Language and Environment for Statistical Computing. Vienna, Austria:R Foundation for Statistical Computing. Available at: http://www.R-project.org.