Theorems like the Lovász Local Lemma?analog of principle of inclusion-exclusionprobabilities of increasing events under different product measures.Can you explain the description of the Lovasz Local Lemma by Moser+Tardos?To what extent can the following zero-one laws be relaxed?A question on independenceHelp with derivation of probability density of event generation & event detectionWhat is the early history of the concepts of probabilistic independence and conditional probability/expectation?Fixing (non)-independency of a the subfamilies of finitely many events.Negative association in a “k out of n” processWhat's the probability of two independent events in time domain?

Theorems like the Lovász Local Lemma?


analog of principle of inclusion-exclusionprobabilities of increasing events under different product measures.Can you explain the description of the Lovasz Local Lemma by Moser+Tardos?To what extent can the following zero-one laws be relaxed?A question on independenceHelp with derivation of probability density of event generation & event detectionWhat is the early history of the concepts of probabilistic independence and conditional probability/expectation?Fixing (non)-independency of a the subfamilies of finitely many events.Negative association in a “k out of n” processWhat's the probability of two independent events in time domain?













3












$begingroup$


The Lovász Local Lemma gives a probability bound in a context where there are many events that are "not quite" independent.



What other theorems exist in this genre? That is, what other theorems have a hypothesis of the form "Let events E_1, E_2, ... satisfy [relaxed form of independence]" and a conclusion of the form "Then the probability of [compound event] satisfies [inequality]"?



(I hope this question isn't too broad. I frequently encounter problems with events that are "almost independent", either in the sense that most subsets are independent or in the sense that the probabilities of compound events are well-approximated by assuming independence, and I am looking for general tools that may be helpful when these situations come up.)










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$endgroup$







  • 1




    $begingroup$
    See pdfs.semanticscholar.org/6631/…
    $endgroup$
    – Sam Hopkins
    3 hours ago






  • 2




    $begingroup$
    Talagrand’s concentration inequality in particular is very powerful for this kind of thing.
    $endgroup$
    – Sam Hopkins
    3 hours ago















3












$begingroup$


The Lovász Local Lemma gives a probability bound in a context where there are many events that are "not quite" independent.



What other theorems exist in this genre? That is, what other theorems have a hypothesis of the form "Let events E_1, E_2, ... satisfy [relaxed form of independence]" and a conclusion of the form "Then the probability of [compound event] satisfies [inequality]"?



(I hope this question isn't too broad. I frequently encounter problems with events that are "almost independent", either in the sense that most subsets are independent or in the sense that the probabilities of compound events are well-approximated by assuming independence, and I am looking for general tools that may be helpful when these situations come up.)










share|cite|improve this question









$endgroup$







  • 1




    $begingroup$
    See pdfs.semanticscholar.org/6631/…
    $endgroup$
    – Sam Hopkins
    3 hours ago






  • 2




    $begingroup$
    Talagrand’s concentration inequality in particular is very powerful for this kind of thing.
    $endgroup$
    – Sam Hopkins
    3 hours ago













3












3








3


1



$begingroup$


The Lovász Local Lemma gives a probability bound in a context where there are many events that are "not quite" independent.



What other theorems exist in this genre? That is, what other theorems have a hypothesis of the form "Let events E_1, E_2, ... satisfy [relaxed form of independence]" and a conclusion of the form "Then the probability of [compound event] satisfies [inequality]"?



(I hope this question isn't too broad. I frequently encounter problems with events that are "almost independent", either in the sense that most subsets are independent or in the sense that the probabilities of compound events are well-approximated by assuming independence, and I am looking for general tools that may be helpful when these situations come up.)










share|cite|improve this question









$endgroup$




The Lovász Local Lemma gives a probability bound in a context where there are many events that are "not quite" independent.



What other theorems exist in this genre? That is, what other theorems have a hypothesis of the form "Let events E_1, E_2, ... satisfy [relaxed form of independence]" and a conclusion of the form "Then the probability of [compound event] satisfies [inequality]"?



(I hope this question isn't too broad. I frequently encounter problems with events that are "almost independent", either in the sense that most subsets are independent or in the sense that the probabilities of compound events are well-approximated by assuming independence, and I am looking for general tools that may be helpful when these situations come up.)







pr.probability probabilistic-method






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asked 3 hours ago









AustinAustin

1763




1763







  • 1




    $begingroup$
    See pdfs.semanticscholar.org/6631/…
    $endgroup$
    – Sam Hopkins
    3 hours ago






  • 2




    $begingroup$
    Talagrand’s concentration inequality in particular is very powerful for this kind of thing.
    $endgroup$
    – Sam Hopkins
    3 hours ago












  • 1




    $begingroup$
    See pdfs.semanticscholar.org/6631/…
    $endgroup$
    – Sam Hopkins
    3 hours ago






  • 2




    $begingroup$
    Talagrand’s concentration inequality in particular is very powerful for this kind of thing.
    $endgroup$
    – Sam Hopkins
    3 hours ago







1




1




$begingroup$
See pdfs.semanticscholar.org/6631/…
$endgroup$
– Sam Hopkins
3 hours ago




$begingroup$
See pdfs.semanticscholar.org/6631/…
$endgroup$
– Sam Hopkins
3 hours ago




2




2




$begingroup$
Talagrand’s concentration inequality in particular is very powerful for this kind of thing.
$endgroup$
– Sam Hopkins
3 hours ago




$begingroup$
Talagrand’s concentration inequality in particular is very powerful for this kind of thing.
$endgroup$
– Sam Hopkins
3 hours ago










1 Answer
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active

oldest

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4












$begingroup$

A large number of results for sums $W$ of possibly dependent indicators of events (that is, for sums of possibly dependent Bernoulli random variables) $X_i$ have been obtained by the Chen--Stein method. See e.g. Theorem 1, which gives an upper bound on the total variation distance between the distribution of such a sum $W$ and a corresponding Poisson distribution in terms of certain characteristics $b_1,b_2,b_3$ of the strength of the dependence between the $X_i$'s (defined in formulas (4)--(6) of that paper).






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    1 Answer
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    1 Answer
    1






    active

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    4












    $begingroup$

    A large number of results for sums $W$ of possibly dependent indicators of events (that is, for sums of possibly dependent Bernoulli random variables) $X_i$ have been obtained by the Chen--Stein method. See e.g. Theorem 1, which gives an upper bound on the total variation distance between the distribution of such a sum $W$ and a corresponding Poisson distribution in terms of certain characteristics $b_1,b_2,b_3$ of the strength of the dependence between the $X_i$'s (defined in formulas (4)--(6) of that paper).






    share|cite|improve this answer









    $endgroup$

















      4












      $begingroup$

      A large number of results for sums $W$ of possibly dependent indicators of events (that is, for sums of possibly dependent Bernoulli random variables) $X_i$ have been obtained by the Chen--Stein method. See e.g. Theorem 1, which gives an upper bound on the total variation distance between the distribution of such a sum $W$ and a corresponding Poisson distribution in terms of certain characteristics $b_1,b_2,b_3$ of the strength of the dependence between the $X_i$'s (defined in formulas (4)--(6) of that paper).






      share|cite|improve this answer









      $endgroup$















        4












        4








        4





        $begingroup$

        A large number of results for sums $W$ of possibly dependent indicators of events (that is, for sums of possibly dependent Bernoulli random variables) $X_i$ have been obtained by the Chen--Stein method. See e.g. Theorem 1, which gives an upper bound on the total variation distance between the distribution of such a sum $W$ and a corresponding Poisson distribution in terms of certain characteristics $b_1,b_2,b_3$ of the strength of the dependence between the $X_i$'s (defined in formulas (4)--(6) of that paper).






        share|cite|improve this answer









        $endgroup$



        A large number of results for sums $W$ of possibly dependent indicators of events (that is, for sums of possibly dependent Bernoulli random variables) $X_i$ have been obtained by the Chen--Stein method. See e.g. Theorem 1, which gives an upper bound on the total variation distance between the distribution of such a sum $W$ and a corresponding Poisson distribution in terms of certain characteristics $b_1,b_2,b_3$ of the strength of the dependence between the $X_i$'s (defined in formulas (4)--(6) of that paper).







        share|cite|improve this answer












        share|cite|improve this answer



        share|cite|improve this answer










        answered 2 hours ago









        Iosif PinelisIosif Pinelis

        19.8k22259




        19.8k22259



























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