Gamma/Gompertz distribution

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

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.

Specification

Probability density function

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

${\displaystyle f(x;b,s,\beta )={\frac {bse^{bx}\beta ^{s)){\left(\beta -1+e^{bx}\right)^{s+1))))$

where ${\displaystyle b>0}$ is the scale parameter and ${\displaystyle \beta ,s>0\,\!}$ are the shape parameters of the Gamma/Gompertz distribution.

Cumulative distribution function

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

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

Moment generating function

The moment generating function is given by:

${\displaystyle {\begin{aligned}{\text{E))(e^{-tx})={\begin{cases}\displaystyle \beta ^{s}{\frac {sb}{t+sb)){\ }{_{2}{\text{F))_{1))(s+1,(t/b)+s;(t/b)+s+1;1-\beta ),&\beta \neq 1;\\\displaystyle {\frac {sb}{t+sb)),&\beta =1.\end{cases))\end{aligned))}$

where ${\displaystyle {_{2}{\text{F))_{1))(a,b;c;z)=\sum _{k=0}^{\infty }[(a)_{k}(b)_{k}/(c)_{k}]z^{k}/k!}$ is a Hypergeometric function.

Properties

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

Related distributions

• 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 ${\displaystyle b\,\!.}$^[1]
• When the shape parameter ${\displaystyle \eta \,\!}$ of a Gompertz distribution varies according to a gamma distribution with shape parameter ${\displaystyle \alpha \,\!}$ and scale parameter ${\displaystyle \beta \,\!}$ (mean = ${\displaystyle \alpha /\beta \,\!}$), the distribution of ${\displaystyle x}$ is Gamma/Gompertz.^[1]