Is there any lemma or theorem about chernoff bound inequality in HOL-probability?
In Isabelle2021, no.
In the development version, yes:
https://isabelle.in.tum.de/repos/isabelle/file/tip/src/HOL/Analysis/Set_Integral.thy
https://isabelle.in.tum.de/repos/isabelle/file/tip/src/HOL/Analysis/Nonnegative_Lebesgue_Integration.thy
(search for "chernoff")
The proofs are very short, so if you really need those bounds, you can just copy them out from there.
ok, so I guess there is no discrete version of chernoff bound, is that right?
All the chernoff bound we have is based on measure theory and integral?
Well, the discrete case is a just a simple special case of this
Discrete probability stuff in Isabelle is usually done with the pmf
type ('a pmf
is the type of discrete probability distributions over a type 'a
). You can convert an 'a pmf
into an 'a measure
with the measure_pmf
function. If you simply plug in measure_pmf p
for some PMF p
in the theorems above, you have the discrete version.
Then the integrals are just sums (finite sums if your PMFs have finite support).
Well I totally agree, do you have some concrete example in probability to show how to switch continuous results into discrete one
Not sure how readable it is, but here I first prove Hoeffding's inequality for general measures and then use it for Bernoulli distributions, which are discrete: https://isabelle.in.tum.de/repos/isabelle/file/tip/src/HOL/Probability/Hoeffding.thy
perfect. btw do you see any article about like using any inequality we established in AFP into some result about game theory?
I don't understand this question.
Last updated: Dec 21 2024 at 16:20 UTC