Shifted Gompertz distribution
| Probability density function |
|
| Cumulative distribution function |
|
| Parameters | scale (real) shape (real) |
|---|---|
| Support | ![]() |
![]() |
|
| CDF | ![]() |
| Mean |
where |
| Mode | ![]() ![]() ![]() |
| Variance |
where |
The shifted Gompertz distribution is the distribution of the largest of two independent random variables one of which has an exponential distribution with parameter b and the other has a Gumbel distribution with parameters
and b. In its original formulation the distribution was expressed referring to the Gompertz distribution instead of the Gumbel distribution but, since the Gompertz distribution is a reverted Gumbel distribution (truncated at zero), the labelling can be considered as accurate. It has been used as a model of adoption of innovations. It was proposed by Bemmaor (1994).
Contents |
Specification
Probability density function
The probability density function of the shifted Gompertz distribution is:
where
is the scale parameter and
is the shape parameter of the shifted Gompertz distribution.
Cumulative distribution function
The cumulative distribution function of the shifted Gompertz distribution is:
Properties
The shifted Gompertz distribution is right-skewed for all values of
. It is more flexible than the Gumbel distribution.
Shapes
The shifted Gompertz density function can take on different shapes depending on the values of the shape parameter
:
the probability density function has its mode at 0.
the probability density function has its mode at
-
- where
is the smallest root of
- which is
Related distributions
If
varies according to a gamma distribution with shape parameter
and scale parameter
(mean =
), the distribution of
is Gamma/Shifted Gompertz (G/SG). When
is equal to one, the G/SG reduces to the Bass model.
See also
- Gumbel distribution
- Generalized extreme value distribution
- Mixture model
- Bass model
- Gompertz distribution
References
|
|
This article includes a list of references, related reading or external links, but its sources remain unclear because it lacks inline citations. (April 2012) |
- Bemmaor, Albert 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. ISBN 0-7923-9388-0.
- Chandrasekaran, Deepa; Tellis, Gerard J. (2007). "A Critical Review of Marketing Research on Diffusion of New Products". In Naresh K. Malhotra. Review of Marketing Research 3. Armonk: M.E. Sharpe. pp. 39–80. ISBN 978-0-7656-1306-6.
- Dover, Yaniv; Goldenberg, Jacob; Shapira, Daniel (2012). "Network Traces on Penetration: Uncovering Degree Distribution From Adoption Data". Marketing Science. doi:10.1287/mksc.1120.0711.
- Jimenez, Fernando; Jodra, Pedro (2009). "A Note on the Moments and Computer Generation of the Shifted Gompertz Distribution". Communications in Statistics - Theory and Methods 38 (1): 78–89. doi:10.1080/03610920802155502.
- Van den Bulte, Christophe; Stremersch, Stefan (2004). "Social Contagion and Income Heterogeneity in New Product Diffusion: A Meta-Analytic Test". Marketing Science 23 (4): 530–544. doi:10.1287/mksc.1040.0054.
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![b e^{-bx} e^{-\eta e^{-bx}}\left[1 + \eta\left(1 - e^{-bx}\right)\right]](http://upload.wikimedia.org/math/4/e/f/4efe11d1016f67a67761bf1697fb5a9b.png)

and ![\begin{align}\mathrm{E}[\ln(X)] =& [1 {+} 1 / \eta]\!\!\int_0^\eta \!\!\!\! e^{-X}[\ln(X)]dX\\ &- 1/\eta\!\! \int_0^\eta \!\!\!\! X e^{-X}[\ln(X)] dX \end{align}](http://upload.wikimedia.org/math/a/9/1/a9194919db20d1b6fc6385e35ca9b907.png)


![\text{ where }z^\star = [3 + \eta - (\eta^2 + 2\eta + 5)^{1/2}]/(2\eta)](http://upload.wikimedia.org/math/2/d/8/2d803da44615fab652d99b8a757acb7c.png)
![\begin{align}\mathrm{E}\{[\ln(X)]^2\} =& [1 {+} 1 / \eta]\!\!\int_0^\eta \!\!\!\! e^{-X}[\ln(X)]^2 dX\\ &- 1/\eta \!\!\int_0^\eta \!\!\!\! X e^{-X}[\ln(X)]^2 dX \end{align}](http://upload.wikimedia.org/math/a/e/0/ae0c3a36593ebf4a23836ecbf71d194d.png)
![f(x;b,\eta) = b e^{-bx} e^{-\eta e^{-bx}}\left[1 + \eta\left(1 - e^{-bx}\right)\right] \text{ for }x \geq 0. \,](http://upload.wikimedia.org/math/3/4/6/346d645e1451a1f8b8037064d6a24ba5.png)

the probability density function has its mode at 0.
the probability density function has its mode at
is the smallest root of

![z^\star = [3 + \eta - (\eta^2 + 2\eta + 5)^{1/2}]/(2\eta).](http://upload.wikimedia.org/math/6/c/7/6c7cbd9304392dbc1aa42d55b99dd33b.png)