Subject: Re: [boost] [histogram] Variance
Date: 2018-09-26 13:16:55
Sorry to get back to the issue of variance. I am unsure about the justification of choosing the variance based on the Poisson distribution instead of the binomial distribution.
My understanding is that the Poisson distribution is based on a distribution of a number of event given a continuous domain of opportunities (say a period of time). Whereas a binomial distribution is for a number of event for a discrete number of opportunities (say coin flips).
Both seem appropriate in some use cases. However, the histogram class has no sense of the passage of time, whereas it does know the number of discrete opportunities (every time operator () is called). And the typical use of histogram seems to be to distribute a given number of samples over the bins that they belong to.
So, would it not be more appropriate to estimate variance based on the binomial distribution?
I am not a statistician, so happy to be put right.
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