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Difference between revisions of "Serial correlation coefficient"

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A statistic that serves as an estimator of the [[Auto-correlation|auto-correlation]] (auto-correlation function) of a [[Time series|time series]]. Let <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/s/s084/s084640/s0846401.png" /> be a time series. The serial correlation coefficient of order <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/s/s084/s084640/s0846402.png" /> is the statistic <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/s/s084/s084640/s0846403.png" /> defined by the formula
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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/s/s084/s084640/s0846404.png" /></td> <td valign="top" style="width:5%;text-align:right;">(*)</td></tr></table>
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A statistic that serves as an estimator of the [[Auto-correlation|auto-correlation]] (auto-correlation function) of a [[Time series|time series]]. Let  $  x _ {1} \dots x _ {N} $
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be a time series. The serial correlation coefficient of order  $  k $
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is the statistic  $  r _ {k} $
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defined by the formula
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$$ \tag{* }
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r _ {k}  = \
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\frac{
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\frac{1}{N - k }
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\sum _ {i = 1 } ^ { {N }  - k } \{ \xi _ {i,k} \xi _ {i+} k,k \} }{\left [
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\frac{1}{N - k }
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\left \{ \sum _ {i = 1 } ^ { {N }  - k } \xi _ {i,k}  ^ {2} \right \}
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\frac{1}{N - k }
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\left \{ \sum _ {i = 1 } ^ { {N }  - k } \xi _ {i+} k,k  ^ {2} \right \}
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\right ]  ^ {1/2} }
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,
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$$
  
 
where
 
where
  
<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/s/s084/s084640/s0846405.png" /></td> </tr></table>
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$$
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\xi _ {i,k}  = x _ {i} - {
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\frac{1}{N - k }
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} \sum _ {i = 1 } ^ { {N }  - k }
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x _ {i} .
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$$
  
Statistics close to (*) but of a slightly simpler form are also used as serial correlation coefficients. The set of serial correlation coefficients is called a correlogram; this term is also used for the graph of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/s/s084/s084640/s0846406.png" /> as a function of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/s/s084/s084640/s0846407.png" />.
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Statistics close to (*) but of a slightly simpler form are also used as serial correlation coefficients. The set of serial correlation coefficients is called a correlogram; this term is also used for the graph of $  r _ {k} $
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as a function of $  k $.
  
Under various assumptions regarding the distribution of the <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/s/s084/s084640/s0846408.png" />, there are exact and approximate expressions for the distribution of the serial correlation coefficients, and of their moments. Serial correlation coefficients are used in statistical problems to discover the dependence of terms in a time series.
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Under various assumptions regarding the distribution of the $  x _ {i} $,  
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there are exact and approximate expressions for the distribution of the serial correlation coefficients, and of their moments. Serial correlation coefficients are used in statistical problems to discover the dependence of terms in a time series.
  
 
As well as the term  "serial correlation coefficient" , the term  "sampling auto-correlationsampling auto-correlation"  is used.
 
As well as the term  "serial correlation coefficient" , the term  "sampling auto-correlationsampling auto-correlation"  is used.

Revision as of 08:13, 6 June 2020


A statistic that serves as an estimator of the auto-correlation (auto-correlation function) of a time series. Let $ x _ {1} \dots x _ {N} $ be a time series. The serial correlation coefficient of order $ k $ is the statistic $ r _ {k} $ defined by the formula

$$ \tag{* } r _ {k} = \ \frac{ \frac{1}{N - k } \sum _ {i = 1 } ^ { {N } - k } \{ \xi _ {i,k} \xi _ {i+} k,k \} }{\left [ \frac{1}{N - k } \left \{ \sum _ {i = 1 } ^ { {N } - k } \xi _ {i,k} ^ {2} \right \} \frac{1}{N - k } \left \{ \sum _ {i = 1 } ^ { {N } - k } \xi _ {i+} k,k ^ {2} \right \} \right ] ^ {1/2} } , $$

where

$$ \xi _ {i,k} = x _ {i} - { \frac{1}{N - k } } \sum _ {i = 1 } ^ { {N } - k } x _ {i} . $$

Statistics close to (*) but of a slightly simpler form are also used as serial correlation coefficients. The set of serial correlation coefficients is called a correlogram; this term is also used for the graph of $ r _ {k} $ as a function of $ k $.

Under various assumptions regarding the distribution of the $ x _ {i} $, there are exact and approximate expressions for the distribution of the serial correlation coefficients, and of their moments. Serial correlation coefficients are used in statistical problems to discover the dependence of terms in a time series.

As well as the term "serial correlation coefficient" , the term "sampling auto-correlationsampling auto-correlation" is used.

References

[1] T.M. Anderson, "The statistical analysis of time series" , Wiley (1971)
[2] M.G. Kendall, A. Stuart, "The advanced theory of statistics" , 3. Design and analysis, and time series , Griffin (1966)
[3] E.J. Hannan, "Time series analysis" , Methuen , London (1960)
How to Cite This Entry:
Serial correlation coefficient. Encyclopedia of Mathematics. URL: http://encyclopediaofmath.org/index.php?title=Serial_correlation_coefficient&oldid=11666
This article was adapted from an original article by V.G. Ushakov (originator), which appeared in Encyclopedia of Mathematics - ISBN 1402006098. See original article