Exponential Geometric Distribution Family Function
Estimates the two parameters of the exponential geometric distribution by maximum likelihood estimation.
expgeometric(lscale = "loglink", lshape = "logitlink",
iscale = NULL, ishape = NULL,
tol12 = 1e-05, zero = 1, nsimEIM = 400)lscale, lshape |
Link function for the two parameters.
See |
iscale, ishape |
Numeric. Optional initial values for the scale and shape parameters. |
tol12 |
Numeric. Tolerance for testing whether a parameter has value 1 or 2. |
zero, nsimEIM |
The exponential geometric distribution has density function
(1/c) * (1 - s) * e^(-y/c) * (1 - s * e^(-y/c))^(-2)
where y > 0, c > 0 and 0 < s < 1. The mean, (c * (s - 1)/ s) * log(1 - s) is returned as the fitted values. Note the median is c * log(2 - s). Simulated Fisher scoring is implemented.
An object of class "vglmff" (see vglmff-class).
The object is used by modelling functions such as vglm
and vgam.
We define scale as the reciprocal of the scale parameter
used by Adamidis and Loukas (1998).
J. G. Lauder and T. W. Yee
Adamidis, K., Loukas, S. (1998). A lifetime distribution with decreasing failure rate. Statistics and Probability Letters, 39, 35–42.
## Not run: Scale <- exp(2); shape = logitlink(-1, inverse = TRUE); edata <- data.frame(y = rexpgeom(n = 2000, scale = Scale, shape = shape)) fit <- vglm(y ~ 1, expgeometric, edata, trace = TRUE) c(with(edata, mean(y)), head(fitted(fit), 1)) coef(fit, matrix = TRUE) Coef(fit) summary(fit) ## End(Not run)
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