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<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c0270104.png" /></td> </tr></table>
 
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c0270104.png" /></td> </tr></table>
  
where <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c0270105.png" /> is the [[Empirical distribution|empirical distribution]] function constructed from the sample <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c0270106.png" /> and <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c0270107.png" /> is a certain non-negative function defined on the interval <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c0270108.png" /> such that <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c0270109.png" />, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701010.png" /> and <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701011.png" /> are integrable on <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701012.png" />. Tests of this type, based on the  "square metric" , were first considered by H. Cramér [[#References|[1]]] and R. von Mises [[#References|[2]]]. N.V. Smirnov proposed putting <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701013.png" />, and showed that in that case, if the hypothesis <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701014.png" /> is valid and <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701015.png" />, the statistic <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701016.png" /> has in the limit an [[Chi-squared test| "omega-squared"  distribution]], independent of the hypothetical distribution function <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701017.png" />. A statistical test for testing <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701018.png" /> based on the statistic <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701019.png" />, is called an <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701020.png" /> (Cramér–von Mises–Smirnov) test, and the numerical value of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701022.png" /> is found using the following representation:
+
where <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c0270105.png" /> is the [[Empirical distribution|empirical distribution]] function constructed from the sample <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c0270106.png" /> and <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c0270107.png" /> is a certain non-negative function defined on the interval <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c0270108.png" /> such that <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c0270109.png" />, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701010.png" /> and <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701011.png" /> are integrable on <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701012.png" />. Tests of this type, based on the  "square metric" , were first considered by H. Cramér {{Cite|C}} and R. von Mises {{Cite|M}}. N.V. Smirnov proposed putting <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701013.png" />, and showed that in that case, if the hypothesis <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701014.png" /> is valid and <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701015.png" />, the statistic <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701016.png" /> has in the limit an [[Chi-squared test| "omega-squared"  distribution]], independent of the hypothetical distribution function <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701017.png" />. A statistical test for testing <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701018.png" /> based on the statistic <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701019.png" />, is called an <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701020.png" /> (Cramér–von Mises–Smirnov) test, and the numerical value of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701022.png" /> is found using the following representation:
  
 
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701023.png" /></td> </tr></table>
 
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701023.png" /></td> </tr></table>
  
where <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701024.png" /> is the variational series based on the sample <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701025.png" />. According to the <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701026.png" /> test with significance level <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701027.png" />, the hypothesis <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701028.png" /> is rejected whenever <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701029.png" />, where <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701030.png" /> is the upper <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701031.png" />-quantile of the distribution of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701032.png" />, i.e. <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701033.png" />. T.W. Anderson and D.A. Darling proposed a similarly constructed test, based on the statistic <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701034.png" /> (see [[#References|[5]]]).
+
where <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701024.png" /> is the variational series based on the sample <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701025.png" />. According to the <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701026.png" /> test with significance level <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701027.png" />, the hypothesis <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701028.png" /> is rejected whenever <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701029.png" />, where <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701030.png" /> is the upper <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701031.png" />-quantile of the distribution of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701032.png" />, i.e. <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701033.png" />. T.W. Anderson and D.A. Darling proposed a similarly constructed test, based on the statistic <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701034.png" /> (see {{Cite|AD}}).
  
 
====References====
 
====References====
<table><TR><TD valign="top">[1]</TD> <TD valign="top"H. Cramér,  "Sannolikhetskalkylen och nåcgra av dess användningar" , Stockholm  (1926)</TD></TR><TR><TD valign="top">[2]</TD> <TD valign="top"R. von Mises,  "Mathematical theory of probability and statistics"  (1964)  (Translated from German)</TD></TR><TR><TD valign="top">[3]</TD> <TD valign="top">  N.V. Smirnov,  "On the <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701035.png" />-distribution of von Mises"  ''Mat. Sb.'' , '''2''' :  5  (1937)  pp. 973–993  (In Russian)  (French abstract)</TD></TR><TR><TD valign="top">[4]</TD> <TD valign="top"L.N. Bol'shev,  N.V. Smirnov,  "Tables of mathematical statistics" , ''Libr. math. tables'' , '''46''' , Nauka  (1983)  (In Russian)  (Processed by L.S. Bark and E.S. Kedrova)</TD></TR><TR><TD valign="top">[5]</TD> <TD valign="top">  T.W. Anderson,  D.A. Darling,  "Asymptotic theory of certain  "goodness-of-fit"  criteria based on stochastic processes"  ''Ann. of Math. Stat.'' , '''23'''  (1952)  pp. 193–212</TD></TR></table>
+
{|
 
+
|valign="top"|{{Ref|C}}|| H. Cramér,  "Sannolikhetskalkylen och nåcgra av dess användningar" , Stockholm  (1926)
 
+
|-
 +
|valign="top"|{{Ref|M}}|| R. von Mises,  "Mathematical theory of probability and statistics"  (1964)  (Translated from German)
 +
|-
 +
|valign="top"|{{Ref|S}}|| N.V. Smirnov,  "On the <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701035.png" />-distribution of von Mises"  ''Mat. Sb.'' , '''2''' :  5  (1937)  pp. 973–993  (In Russian)  (French abstract)
 +
|-
 +
|valign="top"|{{Ref|BS}}|| L.N. Bol'shev,  N.V. Smirnov,  "Tables of mathematical statistics" , ''Libr. math. tables'' , '''46''' , Nauka  (1983)  (In Russian)  (Processed by L.S. Bark and E.S. Kedrova)
 +
|-
 +
|valign="top"|{{Ref|AD}}|| T.W. Anderson,  D.A. Darling,  "Asymptotic theory of certain  "goodness-of-fit"  criteria based on stochastic processes"  ''Ann. of Math. Stat.'' , '''23'''  (1952)  pp. 193–212
 +
|}
  
 
====Comments====
 
====Comments====
 
Usually, the choice <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701036.png" /> is simply called the Cramér–von Mises test in Western literature. However, Smirnov first proposed making this choice and rewrote the statistic in the distribution-free form above. The limit distribution of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701037.png" /> is independent of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701038.png" /> whatever the choice of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701039.png" />. (The term  "square metric"  refers to the expression <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701040.png" />, not to some choice of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701041.png" />.) Cramér actually considered the test with <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701042.png" /> replaced by <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701043.png" />, while von Mises used <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701044.png" />.
 
Usually, the choice <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701036.png" /> is simply called the Cramér–von Mises test in Western literature. However, Smirnov first proposed making this choice and rewrote the statistic in the distribution-free form above. The limit distribution of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701037.png" /> is independent of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701038.png" /> whatever the choice of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701039.png" />. (The term  "square metric"  refers to the expression <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701040.png" />, not to some choice of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701041.png" />.) Cramér actually considered the test with <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701042.png" /> replaced by <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701043.png" />, while von Mises used <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/c/c027/c027010/c02701044.png" />.
  
An alternative to [[#References|[1]]] is [[#References|[a1]]].
+
An alternative to {{Cite|C}} is {{Cite|C2}}.
  
 
====References====
 
====References====
<table><TR><TD valign="top">[a1]</TD> <TD valign="top">  H. Cramér,  "On the composition of elementary errors II"  ''Skand. Aktuarietidskr.''  (1928)  pp. 171–280</TD></TR></table>
+
{|
 +
|valign="top"|{{Ref|C2}}|| H. Cramér,  "On the composition of elementary errors II"  ''Skand. Aktuarietidskr.''  (1928)  pp. 171–280
 +
|}

Revision as of 14:53, 11 May 2012

2020 Mathematics Subject Classification: Primary: 62G10 [MSN][ZBL]

A non-parametric test for testing a hypothesis which states that independent and identically-distributed random variables have a given continuous distribution function . The Cramér–von Mises test is based on a statistic of the type

where is the empirical distribution function constructed from the sample and is a certain non-negative function defined on the interval such that , and are integrable on . Tests of this type, based on the "square metric" , were first considered by H. Cramér [C] and R. von Mises [M]. N.V. Smirnov proposed putting , and showed that in that case, if the hypothesis is valid and , the statistic has in the limit an "omega-squared" distribution, independent of the hypothetical distribution function . A statistical test for testing based on the statistic , is called an (Cramér–von Mises–Smirnov) test, and the numerical value of is found using the following representation:

where is the variational series based on the sample . According to the test with significance level , the hypothesis is rejected whenever , where is the upper -quantile of the distribution of , i.e. . T.W. Anderson and D.A. Darling proposed a similarly constructed test, based on the statistic (see [AD]).

References

[C] H. Cramér, "Sannolikhetskalkylen och nåcgra av dess användningar" , Stockholm (1926)
[M] R. von Mises, "Mathematical theory of probability and statistics" (1964) (Translated from German)
[S] N.V. Smirnov, "On the -distribution of von Mises" Mat. Sb. , 2 : 5 (1937) pp. 973–993 (In Russian) (French abstract)
[BS] L.N. Bol'shev, N.V. Smirnov, "Tables of mathematical statistics" , Libr. math. tables , 46 , Nauka (1983) (In Russian) (Processed by L.S. Bark and E.S. Kedrova)
[AD] T.W. Anderson, D.A. Darling, "Asymptotic theory of certain "goodness-of-fit" criteria based on stochastic processes" Ann. of Math. Stat. , 23 (1952) pp. 193–212

Comments

Usually, the choice is simply called the Cramér–von Mises test in Western literature. However, Smirnov first proposed making this choice and rewrote the statistic in the distribution-free form above. The limit distribution of is independent of whatever the choice of . (The term "square metric" refers to the expression , not to some choice of .) Cramér actually considered the test with replaced by , while von Mises used .

An alternative to [C] is [C2].

References

[C2] H. Cramér, "On the composition of elementary errors II" Skand. Aktuarietidskr. (1928) pp. 171–280
How to Cite This Entry:
Cramér-von Mises test. Encyclopedia of Mathematics. URL: http://encyclopediaofmath.org/index.php?title=Cram%C3%A9r-von_Mises_test&oldid=23240
This article was adapted from an original article by M.S. Nikulin (originator), which appeared in Encyclopedia of Mathematics - ISBN 1402006098. See original article