Tweedie Distributions
Functions for computing and fitting the Tweedie family of distributions
| Package: | tweedie |
| Type: | Package |
| Version: | 2.3.1 |
| Date: | 2017-11-15 |
| License: | GPL (>=2) |
Peter K Dunn
Maintainer: Peter K Dunn <pdunn2@usc.edu.au>
Dunn, P. K. and Smyth, G. K. (2008). Evaluation of Tweedie exponential dispersion model densities by Fourier inversion. Statistics and Computing, 18, 73–86. doi: 10.1007/s11222-007-9039-6
Dunn, Peter K and Smyth, Gordon K (2005). Series evaluation of Tweedie exponential dispersion model densities Statistics and Computing, 15(4). 267–280. doi: 10.1007/s11222-005-4070-y
Dunn, Peter K and Smyth, Gordon K (2001). Tweedie family densities: methods of evaluation. Proceedings of the 16th International Workshop on Statistical Modelling, Odense, Denmark, 2–6 July
Jorgensen, B. (1987). Exponential dispersion models. Journal of the Royal Statistical Society, B, 49, 127–162.
Jorgensen, B. (1997). Theory of Dispersion Models. Chapman and Hall, London.
Tweedie, M. C. K. (1984). An index which distinguishes between some important exponential families. Statistics: Applications and New Directions. Proceedings of the Indian Statistical Institute Golden Jubilee International Conference (Eds. J. K. Ghosh and J. Roy), pp. 579–604. Calcutta: Indian Statistical Institute.
# Generate random numbers set.seed(987654) y <- rtweedie( 20, xi = 1.5, mu = 1, phi = 1) # With Tweedie index xi between 1 and 2, this produces continuous # data with exact zeros x <- rnorm( length(y), 0, 1) # Unrelated predictor # With exact zeros, Tweedie index xi must be between 1 and 2 # Fit the tweedie distribution; expect xi about 1.5 library(statmod) xi.vec <- seq(1.1, 1.9, by = 0.5) out <- tweedie.profile( y ~ 1, xi.vec = xi.vec, do.plot = TRUE, verbose = TRUE) # Fit the glm require(statmod) # Provides tweedie family functions summary(glm( y ~ x, family = tweedie(var.power = out$xi.max, link.power = 0) ))
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