ShiftGomp function

Shifted Gompertz distribution

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)

Arguments

• 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 $P[X \le x]$

  otherwise, $P[X > x]$.

• n: number of observations. If length(n) > 1, the length is taken to be the number required.

Details

If $X$ follows exponential distribution parametrized by scale $b$ and $Y$ follows reparametrized Gumbel distribution with cumulative distribution function $F(x) = exp(-\eta*exp(-b*x))$ 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

Cumulative distribution function

Examples

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)

References

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.