CODEWITHSUNDEEP
julia
Peter
Peter

Reputation: 4359

Discretizing a continuous probability distribution

Recognizing that this may be as much a statistical question as a coding question, let's say I have a normal distribution created using Distributions.jl:

using Distributions

mydist = Normal(0, 0.2)

Is there a good, straightforward way that I should go about discretizing such a distribution in order to get a PMF as opposed to a PDF?

In R, I found that the actuar package contains a function to discretize a continuous distribution. I failed to find anything similar for Julia, but thought I'd check here before rolling my own.

Upvotes: 3

Views: 1036

Answers (1)

Simon Byrne
Simon Byrne

Reputation: 7864

There isn't an inbuilt function to do it, but you can use a range object, combined with the cdf and diff functions to compute the values:

using Distributions
mydist = Normal(0, 0.2)
r = -3:0.1:3
d = diff(cdf(mydist, r))

Upvotes: 8

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