Difference between revisions of "Dist serial correl"

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[[Category:Doc Status C]] <!-- For Lumina use, do not change -->
 
[[Category:Doc Status C]] <!-- For Lumina use, do not change -->
  
= Dist_serial_correl(x,r,i) =
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== Dist_serial_correl(x, r, i) ==
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Generates an array ''y'' over index «i» where each y[i] has a marginal  distribution identical to «x», and serial rank correlation of «r» with y[i-1]. 
  
Generates an array y over index i where each y[i] has a marginal  distribution identical to x, and serial rank correlation of r with y[i-1].  If x is indexed by i,  each y[i] has the same marginal distribution as x[i], but with samples reordered to have the specified rank correlation r between successive values.  If r is indexed by i, r[i=k] specifies the rank correlation between y[i=k] and y[i=k-1].  Then the first correlation, r[i=1], is ignored.
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If «x» is indexed by «i»,  each y[i] has the same marginal distribution as x[i], but with samples reordered to have the specified rank correlation «r» between successive values.   
  
In Mid context, it returns [[Mid]](x).
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If «r» is indexed by «i», r[i = k] specifies the rank correlation between y[i = k] and y[i = k - 1].  Then the first correlation, r[i = 1], is ignored.
  
Note: The result retains no probabilistic dependence on x.
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In [[Mid]] context, it returns [[Mid]](x).
  
= Library =
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The result retains no probabilistic dependence on «x».
  
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== Library ==
 
Multivariate Distributions.ana
 
Multivariate Distributions.ana
  
= See Also =
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== See Also ==
 
 
 
* [[Normal_serial_correl]]
 
* [[Normal_serial_correl]]
 
* [[Dist_additive_growth]]
 
* [[Dist_additive_growth]]
 
* [[Dist_compound_growth]]
 
* [[Dist_compound_growth]]
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* [[Multivariate distributions]]

Revision as of 03:23, 28 January 2016


Dist_serial_correl(x, r, i)

Generates an array y over index «i» where each y[i] has a marginal distribution identical to «x», and serial rank correlation of «r» with y[i-1].

If «x» is indexed by «i», each y[i] has the same marginal distribution as x[i], but with samples reordered to have the specified rank correlation «r» between successive values.

If «r» is indexed by «i», r[i = k] specifies the rank correlation between y[i = k] and y[i = k - 1]. Then the first correlation, r[i = 1], is ignored.

In Mid context, it returns Mid(x).

The result retains no probabilistic dependence on «x».

Library

Multivariate Distributions.ana

See Also

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