Laplace transform of generalized hypergeometric distribution












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$begingroup$


What is please the Laplace transform (moment generating function $M(t)$) of a generalised hypergeometric distribution shown below
$$p_X(x)=Kcdotfrac{(a_1)_xdots(a_p)_x}{(b_1)_xdots(b_q)_x}cdotfrac{theta^x}{x!}$$
for $theta>0$ and some constant $K$?



Meaning $$mathcal{L}left{ p_X(x)right} left(sright)=Kcdotsum_{xgeq0}frac{(a_1)_xdots(a_p)_x}{(b_1)_xdots(b_q)_x}cdotfrac{theta^x}{x!}e^{-xs}
$$
In the case you would know also the cumulant generating function $K(t)=log M(t)$, I would be most obliged.










share|cite|improve this question









$endgroup$












  • $begingroup$
    You need an integral sign just after the equal sign in the second formula...
    $endgroup$
    – Jean Marie
    Nov 27 '18 at 18:36










  • $begingroup$
    in the discrete case it is a sum e.g. here
    $endgroup$
    – Rafael
    Nov 27 '18 at 18:40












  • $begingroup$
    Your formulas are incomplete : you need a summation symbol Σ in your first equation and an integral sign $int_0^{infty}$... before summation symbol Σ in the second equation.
    $endgroup$
    – Jean Marie
    Nov 27 '18 at 22:32










  • $begingroup$
    my first equation is meant not to be a generalised hypergeometric function, but it terms. The constant is 1/$sum$. It is a function of x, not $theta$
    $endgroup$
    – Rafael
    Nov 28 '18 at 9:34










  • $begingroup$
    The terms are the probabilities.
    $endgroup$
    – Rafael
    Nov 28 '18 at 9:35
















0












$begingroup$


What is please the Laplace transform (moment generating function $M(t)$) of a generalised hypergeometric distribution shown below
$$p_X(x)=Kcdotfrac{(a_1)_xdots(a_p)_x}{(b_1)_xdots(b_q)_x}cdotfrac{theta^x}{x!}$$
for $theta>0$ and some constant $K$?



Meaning $$mathcal{L}left{ p_X(x)right} left(sright)=Kcdotsum_{xgeq0}frac{(a_1)_xdots(a_p)_x}{(b_1)_xdots(b_q)_x}cdotfrac{theta^x}{x!}e^{-xs}
$$
In the case you would know also the cumulant generating function $K(t)=log M(t)$, I would be most obliged.










share|cite|improve this question









$endgroup$












  • $begingroup$
    You need an integral sign just after the equal sign in the second formula...
    $endgroup$
    – Jean Marie
    Nov 27 '18 at 18:36










  • $begingroup$
    in the discrete case it is a sum e.g. here
    $endgroup$
    – Rafael
    Nov 27 '18 at 18:40












  • $begingroup$
    Your formulas are incomplete : you need a summation symbol Σ in your first equation and an integral sign $int_0^{infty}$... before summation symbol Σ in the second equation.
    $endgroup$
    – Jean Marie
    Nov 27 '18 at 22:32










  • $begingroup$
    my first equation is meant not to be a generalised hypergeometric function, but it terms. The constant is 1/$sum$. It is a function of x, not $theta$
    $endgroup$
    – Rafael
    Nov 28 '18 at 9:34










  • $begingroup$
    The terms are the probabilities.
    $endgroup$
    – Rafael
    Nov 28 '18 at 9:35














0












0








0





$begingroup$


What is please the Laplace transform (moment generating function $M(t)$) of a generalised hypergeometric distribution shown below
$$p_X(x)=Kcdotfrac{(a_1)_xdots(a_p)_x}{(b_1)_xdots(b_q)_x}cdotfrac{theta^x}{x!}$$
for $theta>0$ and some constant $K$?



Meaning $$mathcal{L}left{ p_X(x)right} left(sright)=Kcdotsum_{xgeq0}frac{(a_1)_xdots(a_p)_x}{(b_1)_xdots(b_q)_x}cdotfrac{theta^x}{x!}e^{-xs}
$$
In the case you would know also the cumulant generating function $K(t)=log M(t)$, I would be most obliged.










share|cite|improve this question









$endgroup$




What is please the Laplace transform (moment generating function $M(t)$) of a generalised hypergeometric distribution shown below
$$p_X(x)=Kcdotfrac{(a_1)_xdots(a_p)_x}{(b_1)_xdots(b_q)_x}cdotfrac{theta^x}{x!}$$
for $theta>0$ and some constant $K$?



Meaning $$mathcal{L}left{ p_X(x)right} left(sright)=Kcdotsum_{xgeq0}frac{(a_1)_xdots(a_p)_x}{(b_1)_xdots(b_q)_x}cdotfrac{theta^x}{x!}e^{-xs}
$$
In the case you would know also the cumulant generating function $K(t)=log M(t)$, I would be most obliged.







laplace-transform hypergeometric-function moment-generating-functions cumulants






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share|cite|improve this question











share|cite|improve this question




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asked Nov 27 '18 at 18:18









Rafael Rafael

465




465












  • $begingroup$
    You need an integral sign just after the equal sign in the second formula...
    $endgroup$
    – Jean Marie
    Nov 27 '18 at 18:36










  • $begingroup$
    in the discrete case it is a sum e.g. here
    $endgroup$
    – Rafael
    Nov 27 '18 at 18:40












  • $begingroup$
    Your formulas are incomplete : you need a summation symbol Σ in your first equation and an integral sign $int_0^{infty}$... before summation symbol Σ in the second equation.
    $endgroup$
    – Jean Marie
    Nov 27 '18 at 22:32










  • $begingroup$
    my first equation is meant not to be a generalised hypergeometric function, but it terms. The constant is 1/$sum$. It is a function of x, not $theta$
    $endgroup$
    – Rafael
    Nov 28 '18 at 9:34










  • $begingroup$
    The terms are the probabilities.
    $endgroup$
    – Rafael
    Nov 28 '18 at 9:35


















  • $begingroup$
    You need an integral sign just after the equal sign in the second formula...
    $endgroup$
    – Jean Marie
    Nov 27 '18 at 18:36










  • $begingroup$
    in the discrete case it is a sum e.g. here
    $endgroup$
    – Rafael
    Nov 27 '18 at 18:40












  • $begingroup$
    Your formulas are incomplete : you need a summation symbol Σ in your first equation and an integral sign $int_0^{infty}$... before summation symbol Σ in the second equation.
    $endgroup$
    – Jean Marie
    Nov 27 '18 at 22:32










  • $begingroup$
    my first equation is meant not to be a generalised hypergeometric function, but it terms. The constant is 1/$sum$. It is a function of x, not $theta$
    $endgroup$
    – Rafael
    Nov 28 '18 at 9:34










  • $begingroup$
    The terms are the probabilities.
    $endgroup$
    – Rafael
    Nov 28 '18 at 9:35
















$begingroup$
You need an integral sign just after the equal sign in the second formula...
$endgroup$
– Jean Marie
Nov 27 '18 at 18:36




$begingroup$
You need an integral sign just after the equal sign in the second formula...
$endgroup$
– Jean Marie
Nov 27 '18 at 18:36












$begingroup$
in the discrete case it is a sum e.g. here
$endgroup$
– Rafael
Nov 27 '18 at 18:40






$begingroup$
in the discrete case it is a sum e.g. here
$endgroup$
– Rafael
Nov 27 '18 at 18:40














$begingroup$
Your formulas are incomplete : you need a summation symbol Σ in your first equation and an integral sign $int_0^{infty}$... before summation symbol Σ in the second equation.
$endgroup$
– Jean Marie
Nov 27 '18 at 22:32




$begingroup$
Your formulas are incomplete : you need a summation symbol Σ in your first equation and an integral sign $int_0^{infty}$... before summation symbol Σ in the second equation.
$endgroup$
– Jean Marie
Nov 27 '18 at 22:32












$begingroup$
my first equation is meant not to be a generalised hypergeometric function, but it terms. The constant is 1/$sum$. It is a function of x, not $theta$
$endgroup$
– Rafael
Nov 28 '18 at 9:34




$begingroup$
my first equation is meant not to be a generalised hypergeometric function, but it terms. The constant is 1/$sum$. It is a function of x, not $theta$
$endgroup$
– Rafael
Nov 28 '18 at 9:34












$begingroup$
The terms are the probabilities.
$endgroup$
– Rafael
Nov 28 '18 at 9:35




$begingroup$
The terms are the probabilities.
$endgroup$
– Rafael
Nov 28 '18 at 9:35










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