Bounding a truncated normal with a gamma

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To find a gamma distribution that bounds a truncated normal distribution from above, select a shape parameter A that ensures the gamma's probability density function (pdf) diverges at x=0. Define f as the difference between the gamma pdf and the truncated normal pdf, which depends on the variables x and B. Use numeric analysis to solve the equations f(x,A,B)=0 and the derivative condition ∂f/∂x(x,A,B)=0 for the unknowns x and B. Eliminate any solutions where the second derivative ∂²f/∂x²(x,A,B) is less than or equal to zero. This process can be repeated for various values of A to discover multiple bounding curves.
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So say I have a truncated normal. That is, N(mu,sigma) that is from 0 to infinity only.

I need to find a Gamma such that a constant C*Gamma(A,B) is always above N(mu, sigma). How would I go about finding such a A, B that would work given fixed mu and sigma?
 
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Choose a value of ##A##, the gamma's shape parameter. It will have to be a value that makes the gamma's pdf diverge to infinity at ##x=0##, because otherwise the pdf will be zero there, and so will be below the normal pdf.
Let ##f## be the pdf of the gamma minus the pdf of the truncated normal. It will be a function of ##x, A, B##, of which only two (##x, B##) are unknown.
Use numeric analysis to solve the following two equations for ##x## and ##B##.

1. ##f(x,A,B)=0##
2. ##\frac{\partial f}{\partial x}(x,A,B)=0##.

Remove any solutions where ##\frac{\partial^2 f}{\partial x^2}(x,A,B)\leq 0##.

What remains will be parameters of curves that have the property you seek. The gamma pdf curve will touch that of the normal, but not go below it. There may be more than one such curve.

You can repeat this for different admissible values of ##A## to get additional sets of solutions.
 
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