Difference between revisions of "Bayes formula"
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− | + | A formula with which it is possible to compute a posteriori probabilities of events (or of hypotheses) from a priori probabilities. Let $ A _ {1} \dots A _ {n} $ | |
+ | be a complete group of incompatible events: $ \cup A _ {i} = \Omega $, | ||
+ | $ A _ {i} \Gamma \cap A _ {j} = \emptyset $ | ||
+ | if $ i \neq j $. | ||
+ | Then the a posteriori probability $ {\mathsf P} (A _ {i} \mid B) $ | ||
+ | of event $ A _ {i} $ | ||
+ | if given that event $ B $ | ||
+ | with $ {\mathsf P} (B)>0 $ | ||
+ | has already occurred may be found by Bayes' formula: | ||
− | + | $$ \tag{* } | |
+ | {\mathsf P} (A _ {i} \mid B ) = \ | ||
− | + | \frac{ {\mathsf P} (A _ {i} ) {\mathsf P} (B \mid A _ {i} ) }{\sum _ { i=1 } ^ { n } {\mathsf P} (A _ {i} ) {\mathsf P} (B \mid A _ {i} ) } | |
+ | , | ||
+ | $$ | ||
− | where | + | where $ {\mathsf P} (A _ {i} ) $ |
+ | is the a priori probability of $ A _ {i} $, | ||
+ | $ {\mathsf P} (B \mid A _ {i} ) $ | ||
+ | is the conditional probability of event $ B $ | ||
+ | occurring given event $ A _ {i} $( | ||
+ | with $ {\mathsf P} (A _ {i} ) > 0 $) | ||
+ | has taken place. The formula was demonstrated by T. Bayes in 1763. | ||
+ | |||
+ | Formula (*) is a special case of the following abstract variant of Bayes' formula. Let $ \theta $ | ||
+ | and $ \xi $ | ||
+ | be random elements with values in measurable spaces $ ( \Theta , B _ \Theta ) $ | ||
+ | and $ (X, B _ {X} ) $ | ||
+ | and let $ {\mathsf E} | g ( \theta ) | < \infty $. | ||
+ | Put, for any set $ A \in F _ \xi = \sigma \{ \omega : {\xi ( \omega ) } \} $, | ||
+ | |||
+ | $$ | ||
+ | G(A) = \int\limits _ \Omega | ||
+ | g ( \theta ( \omega )) | ||
+ | {\mathsf E} [I _ {A} ( \omega ) \mid F _ \theta ] | ||
+ | ( \omega ) {\mathsf P} (d \omega ), | ||
+ | $$ | ||
+ | |||
+ | where $ F _ \theta = \sigma \{ \omega : {\theta ( \omega ) } \} $ | ||
+ | and $ I _ {A} ( \omega ) $ | ||
+ | is the indicator of the set $ A $. | ||
+ | Then the measure $ G $ | ||
+ | is absolutely continuous with respect to the measure $ {\mathsf P} $( | ||
+ | $ G \ll {\mathsf P} $) | ||
+ | and $ {\mathsf E} [g ( \theta ) \mid F _ \xi ] ( \omega ) = (dG / d {\mathsf P} ) ( \omega ) $, | ||
+ | where $ (dG / d {\mathsf P} ) ( \omega ) $ | ||
+ | is the Radon–Nikodým derivative of $ G $ | ||
+ | with respect to $ {\mathsf P} $. | ||
====References==== | ====References==== | ||
<table><TR><TD valign="top">[1]</TD> <TD valign="top"> A.N. Kolmogorov, "Foundations of the theory of probability" , Chelsea, reprint (1950) (Translated from Russian)</TD></TR></table> | <table><TR><TD valign="top">[1]</TD> <TD valign="top"> A.N. Kolmogorov, "Foundations of the theory of probability" , Chelsea, reprint (1950) (Translated from Russian)</TD></TR></table> | ||
− | |||
− | |||
====Comments==== | ====Comments==== | ||
− | |||
====References==== | ====References==== | ||
<table><TR><TD valign="top">[a1]</TD> <TD valign="top"> R.S. Liptser, A.N. Shiryaev, "Statistics of random processes" , '''1''' , Springer (1977) pp. Section 7.9 (Translated from Russian)</TD></TR></table> | <table><TR><TD valign="top">[a1]</TD> <TD valign="top"> R.S. Liptser, A.N. Shiryaev, "Statistics of random processes" , '''1''' , Springer (1977) pp. Section 7.9 (Translated from Russian)</TD></TR></table> |
Latest revision as of 10:33, 29 May 2020
A formula with which it is possible to compute a posteriori probabilities of events (or of hypotheses) from a priori probabilities. Let $ A _ {1} \dots A _ {n} $
be a complete group of incompatible events: $ \cup A _ {i} = \Omega $,
$ A _ {i} \Gamma \cap A _ {j} = \emptyset $
if $ i \neq j $.
Then the a posteriori probability $ {\mathsf P} (A _ {i} \mid B) $
of event $ A _ {i} $
if given that event $ B $
with $ {\mathsf P} (B)>0 $
has already occurred may be found by Bayes' formula:
$$ \tag{* } {\mathsf P} (A _ {i} \mid B ) = \ \frac{ {\mathsf P} (A _ {i} ) {\mathsf P} (B \mid A _ {i} ) }{\sum _ { i=1 } ^ { n } {\mathsf P} (A _ {i} ) {\mathsf P} (B \mid A _ {i} ) } , $$
where $ {\mathsf P} (A _ {i} ) $ is the a priori probability of $ A _ {i} $, $ {\mathsf P} (B \mid A _ {i} ) $ is the conditional probability of event $ B $ occurring given event $ A _ {i} $( with $ {\mathsf P} (A _ {i} ) > 0 $) has taken place. The formula was demonstrated by T. Bayes in 1763.
Formula (*) is a special case of the following abstract variant of Bayes' formula. Let $ \theta $ and $ \xi $ be random elements with values in measurable spaces $ ( \Theta , B _ \Theta ) $ and $ (X, B _ {X} ) $ and let $ {\mathsf E} | g ( \theta ) | < \infty $. Put, for any set $ A \in F _ \xi = \sigma \{ \omega : {\xi ( \omega ) } \} $,
$$ G(A) = \int\limits _ \Omega g ( \theta ( \omega )) {\mathsf E} [I _ {A} ( \omega ) \mid F _ \theta ] ( \omega ) {\mathsf P} (d \omega ), $$
where $ F _ \theta = \sigma \{ \omega : {\theta ( \omega ) } \} $ and $ I _ {A} ( \omega ) $ is the indicator of the set $ A $. Then the measure $ G $ is absolutely continuous with respect to the measure $ {\mathsf P} $( $ G \ll {\mathsf P} $) and $ {\mathsf E} [g ( \theta ) \mid F _ \xi ] ( \omega ) = (dG / d {\mathsf P} ) ( \omega ) $, where $ (dG / d {\mathsf P} ) ( \omega ) $ is the Radon–Nikodým derivative of $ G $ with respect to $ {\mathsf P} $.
References
[1] | A.N. Kolmogorov, "Foundations of the theory of probability" , Chelsea, reprint (1950) (Translated from Russian) |
Comments
References
[a1] | R.S. Liptser, A.N. Shiryaev, "Statistics of random processes" , 1 , Springer (1977) pp. Section 7.9 (Translated from Russian) |
Bayes formula. Encyclopedia of Mathematics. URL: http://encyclopediaofmath.org/index.php?title=Bayes_formula&oldid=16075