Chernoff bound and Q-function

Shortcuts: Differences, Similarities, Jaccard Similarity Coefficient, References.

Difference between Chernoff bound and Q-function

Chernoff bound vs. Q-function

In probability theory, the Chernoff bound, named after Herman Chernoff but due to Herman Rubin, gives exponentially decreasing bounds on tail distributions of sums of independent random variables. In statistics, the Q-function is the tail distribution function of the standard normal distribution.

Similarities between Chernoff bound and Q-function

Chernoff bound and Q-function have 0 things in common (in Unionpedia).

The list above answers the following questions

What Chernoff bound and Q-function have in common
What are the similarities between Chernoff bound and Q-function

Chernoff bound and Q-function Comparison

Chernoff bound has 30 relations, while Q-function has 12. As they have in common 0, the Jaccard index is 0.00% = 0 / (30 + 12).

References

This article shows the relationship between Chernoff bound and Q-function. To access each article from which the information was extracted, please visit:

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