# Gamma/Gompertz distribution

In probability and statistics, the Gamma/Gompertz distribution is a continuous probability distribution. It has been used as an aggregate-level model of customer lifetime and a model of mortality risks.

Parameters Probability density functionNote: b=0.4, β=3 Cumulative distribution function $b,s,\beta >0\,\!$ $x\in [0,\infty )\!$ $bse^{bx}\beta ^{s}/\left(\beta -1+e^{bx}\right)^{s+1}{\text{where }}b,s,\beta >0$ $1-\beta ^{s}/\left(\beta -1+e^{bx}\right)^{s},x>0,b,s,\beta >0$ $1-e^{-bsx},\beta =1$ $=\left(1/b\right)\left(1/s\right){_{2}{\text{F}}_{1}}\left(s,1;s+1;\left(\beta -1\right)/\beta \right),$ $b,s>0,\beta \neq 1$ $=\left(1/b\right)\left[\beta /\left(\beta -1\right)\right]\ln \left(\beta \right),$ $b>0,s=1,\beta \neq 1$ $=1/\left(bs\right),\quad b,s>0,\beta =1$ $\left(1/b\right)\ln\{\beta \left[\left(1/2\right)^{-1/s}-1\right]+1\}$ {\begin{aligned}x^{*}&=(1/b)\ln \left[(1/s)(\beta -1)\right],\\&{\text{with }}0<{\text{F}}(x^{*})<1-(\beta s)^{s}/\left[(\beta -1)(s+1)\right]^{s}<0.632121,\\&\beta >s+1\\&=0,\quad \beta \leq s+1\\\end{aligned}} $=2(1/b^{2})(1/s^{2})\beta ^{s}{_{3}{\text{F}}_{2}}(s,s,s;s+1,s+1;1-\beta )$ $-{\text{E}}^{2}(\tau |b,s,\beta ),\quad \beta \neq 1$ $=(1/b^{2})(1/s^{2}),\quad \beta =1$ ${\text{with}}$ ${_{3}{\text{F}}_{2}}(a,b,c;d,e;z)=\sum _{k=0}^{\infty }\{(a)_{k}(b)_{k}(c)_{k}/[(d)_{k}(e)_{k}]\}z^{k}/k!$ ${\text{and}}$ $(a)_{k}=\Gamma (a+k)/\Gamma (a)$ ${\text{E}}(e^{-tx})$ $=\beta ^{s}[sb/(t+sb)]{_{2}{\text{F}}_{1}}(s+1,(t/b)+s;(t/b)+s+1;1-\beta ),$ $\quad \beta \neq 1$ $=sb/(t+sb),\quad \beta =1$ ${\text{with }}{_{2}{\text{F}}_{1}}(a,b;c;z)=\sum _{k=0}^{\infty }[(a)_{k}(b)_{k}/(c)_{k}]z^{k}/k!$ ## Specification

### Probability density function

The probability density function of the Gamma/Gompertz distribution is:

$f(x;b,s,\beta )={\frac {bse^{bx}\beta ^{s}}{\left(\beta -1+e^{bx}\right)^{s+1}}}$ where $b>0$ is the scale parameter and $\beta ,s>0\,\!$ are the shape parameters of the Gamma/Gompertz distribution.

### Cumulative distribution function

The cumulative distribution function of the Gamma/Gompertz distribution is:

{\begin{aligned}F(x;b,s,\beta )&=1-{\frac {\beta ^{s}}{\left(\beta -1+e^{bx}\right)^{s}}},{\ }x>0,{\ }b,s,\beta >0\\[6pt]&=1-e^{-bsx},{\ }\beta =1\\\end{aligned}} ### Moment generating function

The moment generating function is given by:

{\begin{aligned}{\text{E}}(e^{-tx})={\begin{cases}\displaystyle \beta ^{s}{\frac {sb}{t+sb}}{\ }{_{2}{\text{F}}_{1}}(s+1,(t/b)+s;(t/b)+s+1;1-\beta ),&\beta \neq 1;\\\displaystyle {\frac {sb}{t+sb}},&\beta =1.\end{cases}}\end{aligned}} where ${_{2}{\text{F}}_{1}}(a,b;c;z)=\sum _{k=0}^{\infty }[(a)_{k}(b)_{k}/(c)_{k}]z^{k}/k!$ is a Hypergeometric function.

## Properties

The Gamma/Gompertz distribution is a flexible distribution that can be skewed to the right or to the left.

• When β = 1, this reduces to an Exponential distribution with parameter sb.
• The gamma distribution is a natural conjugate prior to a Gompertz likelihood with known, scale parameter $b\,\!.$ • When the shape parameter $\eta \,\!$ of a Gompertz distribution varies according to a gamma distribution with shape parameter $\alpha \,\!$ and scale parameter $\beta \,\!$ (mean = $\alpha /\beta \,\!$ ), the distribution of $x$ is Gamma/Gompertz.