Difference between revisions of "Power function of a test"
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− | + | A function characterizing the quality of a [[Statistical test|statistical test]]. Suppose that, based on a realization $ x $ | |
+ | of a random vector $ X $ | ||
+ | with values in a sampling space $ ( X , B , {\mathsf P} _ \theta ) $, | ||
+ | $ \theta \in \Theta $, | ||
+ | it is necessary to test the hypothesis $ H _ {0} $ | ||
+ | according to which the probability distribution $ {\mathsf P} _ \theta $ | ||
+ | of $ X $ | ||
+ | belongs to a subset $ H _ {0} = \{ { {\mathsf P} _ \theta } : {\theta \in \Theta _ {0} \subset \Theta } \} $, | ||
+ | against the alternative $ H _ {1} $ | ||
+ | according to which | ||
− | + | $$ | |
+ | {\mathsf P} _ \theta \in H _ {1} = \ | ||
+ | \{ { {\mathsf P} _ \theta } : {\theta \in \Theta _ {1} = \Theta \setminus | ||
+ | \Theta _ {0} } \} | ||
+ | , | ||
+ | $$ | ||
− | + | and let $ \phi ( \cdot ) $ | |
+ | be the critical function of the statistical test intended for testing $ H _ {0} $ | ||
+ | against $ H _ {1} $. | ||
+ | Then | ||
− | In the theory of statistical hypothesis testing, founded by J. Neyman and E. Pearson, the problem of testing a compound hypothesis | + | $$ \tag{* } |
+ | \beta ( \theta ) = \ | ||
+ | \int\limits _ { \mathfrak X } \phi ( x) d {\mathsf P} _ \theta ( x) ,\ \ | ||
+ | \theta \in \Theta = \Theta _ {0} \cup \Theta _ {1} , | ||
+ | $$ | ||
+ | |||
+ | is called the power function of the statistical test with critical function $ \phi $. | ||
+ | It follows from (*) that $ \beta ( \theta ) $ | ||
+ | gives the probabilities with which the statistical test for testing $ H _ {0} $ | ||
+ | against $ H _ {1} $ | ||
+ | rejects the hypothesis $ H _ {0} $ | ||
+ | if $ X $ | ||
+ | is subject to the law $ {\mathsf P} _ \theta $, | ||
+ | $ \theta \in \Theta $. | ||
+ | |||
+ | In the theory of statistical hypothesis testing, founded by J. Neyman and E. Pearson, the problem of testing a compound hypothesis $ H _ {0} $ | ||
+ | against a compound alternative $ H _ {1} $ | ||
+ | is formulated in terms of the power function of a test and consists of the construction of a test maximizing $ \beta ( \theta ) $, | ||
+ | when $ \theta \in \Theta $, | ||
+ | under the condition that $ \beta ( \theta ) \leq \alpha $ | ||
+ | for all $ \theta \in \Theta _ {0} $, | ||
+ | where $ \alpha $( | ||
+ | $ 0 < \alpha < 1 $) | ||
+ | is called the significance level of the test — a given admissible probability of the error of rejecting $ H _ {0} $ | ||
+ | when it is in fact true. | ||
====References==== | ====References==== | ||
<table><TR><TD valign="top">[1]</TD> <TD valign="top"> E.L. Lehmann, "Testing statistical hypotheses" , Wiley (1959)</TD></TR><TR><TD valign="top">[2]</TD> <TD valign="top"> H. Cramér, "Mathematical methods of statistics" , Princeton Univ. Press (1946)</TD></TR><TR><TD valign="top">[3]</TD> <TD valign="top"> B.L. van der Waerden, "Mathematische Statistik" , Springer (1957)</TD></TR></table> | <table><TR><TD valign="top">[1]</TD> <TD valign="top"> E.L. Lehmann, "Testing statistical hypotheses" , Wiley (1959)</TD></TR><TR><TD valign="top">[2]</TD> <TD valign="top"> H. Cramér, "Mathematical methods of statistics" , Princeton Univ. Press (1946)</TD></TR><TR><TD valign="top">[3]</TD> <TD valign="top"> B.L. van der Waerden, "Mathematische Statistik" , Springer (1957)</TD></TR></table> |
Latest revision as of 08:07, 6 June 2020
A function characterizing the quality of a statistical test. Suppose that, based on a realization $ x $
of a random vector $ X $
with values in a sampling space $ ( X , B , {\mathsf P} _ \theta ) $,
$ \theta \in \Theta $,
it is necessary to test the hypothesis $ H _ {0} $
according to which the probability distribution $ {\mathsf P} _ \theta $
of $ X $
belongs to a subset $ H _ {0} = \{ { {\mathsf P} _ \theta } : {\theta \in \Theta _ {0} \subset \Theta } \} $,
against the alternative $ H _ {1} $
according to which
$$ {\mathsf P} _ \theta \in H _ {1} = \ \{ { {\mathsf P} _ \theta } : {\theta \in \Theta _ {1} = \Theta \setminus \Theta _ {0} } \} , $$
and let $ \phi ( \cdot ) $ be the critical function of the statistical test intended for testing $ H _ {0} $ against $ H _ {1} $. Then
$$ \tag{* } \beta ( \theta ) = \ \int\limits _ { \mathfrak X } \phi ( x) d {\mathsf P} _ \theta ( x) ,\ \ \theta \in \Theta = \Theta _ {0} \cup \Theta _ {1} , $$
is called the power function of the statistical test with critical function $ \phi $. It follows from (*) that $ \beta ( \theta ) $ gives the probabilities with which the statistical test for testing $ H _ {0} $ against $ H _ {1} $ rejects the hypothesis $ H _ {0} $ if $ X $ is subject to the law $ {\mathsf P} _ \theta $, $ \theta \in \Theta $.
In the theory of statistical hypothesis testing, founded by J. Neyman and E. Pearson, the problem of testing a compound hypothesis $ H _ {0} $ against a compound alternative $ H _ {1} $ is formulated in terms of the power function of a test and consists of the construction of a test maximizing $ \beta ( \theta ) $, when $ \theta \in \Theta $, under the condition that $ \beta ( \theta ) \leq \alpha $ for all $ \theta \in \Theta _ {0} $, where $ \alpha $( $ 0 < \alpha < 1 $) is called the significance level of the test — a given admissible probability of the error of rejecting $ H _ {0} $ when it is in fact true.
References
[1] | E.L. Lehmann, "Testing statistical hypotheses" , Wiley (1959) |
[2] | H. Cramér, "Mathematical methods of statistics" , Princeton Univ. Press (1946) |
[3] | B.L. van der Waerden, "Mathematische Statistik" , Springer (1957) |
Power function of a test. Encyclopedia of Mathematics. URL: http://encyclopediaofmath.org/index.php?title=Power_function_of_a_test&oldid=14564