# Inverse of Gamma Distribution [closed]

I am using python to calculate Inverse of a CDF of gamma distribution (using scipy. stat.gamma.fit). But for probability value 1, it is coming infinite. If it is replaced from 1 to 0.99 it works but the values changes with the different number of significant figures. Like it is 61 for 0.99 and 130 for 0.9999.

I do not know the best way to handle these infinite values in my workflow.I need to get a ideals but valid inverse value for probabilities arbitrarily close to 1. But i don't know, how to decide how many digits are needed to round off the probability value. Also, I am not sure about, Will it be fine to round off?

Can we do something to get some meaningful information instead of inf value?

## closed as unclear what you're asking by Michael Chernick, kjetil b halvorsen, Peter Flom♦Feb 13 at 10:39

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• That sounds about right. Why do you think there is a “situation” here? – The Laconic Feb 13 at 5:50
• I need to get the best possible inverse value near to 1. But i don't know, how to decide the upto which digit it is needed to round off the probability value. Also, I am not sure about, Will it be fine to round off? – user10423946 Feb 13 at 7:17
• What does "best possible inverse value near to 1" mean? How near? – Peter Flom Feb 13 at 10:39
• The correct value of the inverse CDF of all Gamma distributions at the argument $1$ is $+\infty.$ It sounds like your software is giving you the right answer. – whuber Feb 13 at 14:38
• yes..that is correct but @ReeBt well explained my problem – user10423946 Feb 13 at 15:31