ShiftGomp | R Documentation |
Density, distribution function, and random generation for the shifted Gompertz distribution.
dsgomp(x, b, eta, log = FALSE)
psgomp(q, b, eta, lower.tail = TRUE, log.p = FALSE)
rsgomp(n, b, eta)
x , q |
vector of quantiles. |
b , eta |
positive valued scale and shape parameters; both need to be positive. |
log , log.p |
logical; if TRUE, probabilities p are given as log(p). |
lower.tail |
logical; if TRUE (default), probabilities are |
n |
number of observations. If |
If X
follows exponential distribution parametrized by scale b
and
Y
follows reparametrized Gumbel distribution with cumulative distribution function
F(x) = \exp(-\eta e^{-bx})
parametrized by
scale b
and shape \eta
, then \max(X,Y)
follows shifted
Gompertz distribution parametrized by scale b>0
and shape \eta>0
.
The above relation is used by rsgomp
function for random generation from
shifted Gompertz distribution.
Probability density function
f(x) = b e^{-bx} \exp(-\eta e^{-bx}) \left[1 + \eta(1 - e^{-bx})\right]
Cumulative distribution function
F(x) = (1-e^{-bx}) \exp(-\eta e^{-bx})
Bemmaor, A.C. (1994). Modeling the Diffusion of New Durable Goods: Word-of-Mouth Effect Versus Consumer Heterogeneity. [In:] G. Laurent, G.L. Lilien & B. Pras. Research Traditions in Marketing. Boston: Kluwer Academic Publishers. pp. 201-223.
Jimenez, T.F. and Jodra, P. (2009). A Note on the Moments and Computer Generation of the Shifted Gompertz Distribution. Communications in Statistics - Theory and Methods, 38(1), 78-89.
Jimenez T.F. (2014). Estimation of the Parameters of the Shifted Gompertz Distribution, Using Least Squares, Maximum Likelihood and Moments Methods. Journal of Computational and Applied Mathematics, 255(1), 867-877.
x <- rsgomp(1e5, 0.4, 1)
hist(x, 50, freq = FALSE)
curve(dsgomp(x, 0.4, 1), 0, 30, col = "red", add = TRUE)
hist(psgomp(x, 0.4, 1))
plot(ecdf(x))
curve(psgomp(x, 0.4, 1), 0, 30, col = "red", lwd = 2, add = TRUE)
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