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In mathematics, '''Owen's T function''' ''T''(''h'', ''a''), named after [[statistician]] Donald Bruce Owen, is defined by


:<math>
T(h,a)=\frac{1}{2\pi}\int_{0}^{a} \frac{e^{-\frac{1}{2} h^2 (1+x^2)}}{1+x^2}  dx \quad \left(-\infty < h, a < +\infty\right).
</math>


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==Applications==
The function ''T''(''h'',&nbsp;''a'') gives the probability of the event (''X>h'' and 0''<Y<a*X'') where ''X'' and ''Y'' are [[statistically independent|independent]] [[standard normal distribution|standard normal]] [[random variable]]s.
This function can be used to calculate [[bivariate normal distribution]] probabilities<ref>Sowden, R R and Ashford, J R (1969). "Computation of the bivariate normal integral". ''Applied Statististics'', 18, 169&ndash;180.</ref><ref>Donelly, T G (1973). "Algorithm 462. Bivariate normal distribution". ''Commun. Ass. Comput.Mach.'', 16, 638.</ref> and, from there, in the calculation of [[multivariate normal distribution]] probabilities.<ref>Schervish, M H (1984). "Multivariate normal probabilities with [[error bound]]". ''Applied Statistics'', 33, 81&ndash;94.</ref>
It also frequently appears in [[List of integrals of Gaussian functions|various integrals involving Gaussian functions]].
 
Computer algorithms for the accurate calculation of this function are available.<ref>Patefield, M. and Tandy, D(2000) "[http://www.jstatsoft.org/v05/i05/paper Fast and accurate Calculation of Owen’s T-Function]", ''Journal of Statistical Software'', 5 (5), 1&ndash;25.
</ref> The function was first introduced by Owen in 1956.<ref>Owen, D B (1956). "Tables for computing bivariate normal probabilities". ''Annals of Mathematical Statistics'',
27, 1075&ndash;1090.</ref>
 
==Properties==
: <math> T(h,0) = 0 </math>
: <math> T(0,a) = \frac{1}{2\pi} \arctan(a) </math>
: <math> T(-h,a) = T(h,a) </math>
: <math> T(h,-a) = -T(h,a) </math>
: <math> T(h,a) + T(ah,\frac{1}{a}) = \frac{1}{2} \left(\Phi(h) + \Phi(ah)\right) + \Phi(h)\Phi(ah) \quad \mbox{if} \quad a \geq 0 </math>
: <math> T(h,a) + T(ah,\frac{1}{a}) = \frac{1}{2} \left(\Phi(h) + \Phi(ah)\right) + \Phi(h)\Phi(ah) - \frac{1}{2} \quad \mbox{if} \quad a < 0 </math>
: <math> T(h, 1) = \frac{1}{2} \Phi(h) \left(1 - \Phi(h)\right) </math>
: <math> \int T(0,x) \mathrm{d}x = x T(0,x) - \frac{1}{4 \pi} \ln(1+x^2) + C </math>
More properties can be found in the literature.<ref>{{harvtxt|Owen|1980}}</ref>
 
==References==
{{reflist}}
 
* {{cite journal
  | last1 = Owen | first1 = D.
  | year = 1980
  | title = A table of normal integrals
  | journal = Communications in Statistics: Simulation and Computation
  | pages = 389–419
  | volume = B9
  | ref = harv
  }}
 
==Software==
* [http://people.sc.fsu.edu/~burkardt/f_src/owens/owens.html Owen's T function] (user web site) - offers C++, FORTRAN77, FORTRAN90, and MATLAB libraries released under the LGPL license [[LGPL]]
* Owen's T-function is implemented in [[Mathematica]] since version 8, as [http://reference.wolfram.com/mathematica/ref/OwenT.html OwenT].
 
==External links==
* [http://blog.wolfram.com/2010/10/07/why-you-should-care-about-the-obscure/ Why You Should Care about the Obscure] (Wolfram blog post)
 
[[Category:Multivariate statistics]]
[[Category:Computational statistics]]
[[Category:Functions related to probability distributions]]
 
 
{{statistics-stub}}

Revision as of 19:51, 27 January 2014

In mathematics, Owen's T function T(ha), named after statistician Donald Bruce Owen, is defined by

T(h,a)=12π0ae12h2(1+x2)1+x2dx(<h,a<+).

Applications

The function T(ha) gives the probability of the event (X>h and 0<Y<a*X) where X and Y are independent standard normal random variables.

This function can be used to calculate bivariate normal distribution probabilities[1][2] and, from there, in the calculation of multivariate normal distribution probabilities.[3] It also frequently appears in various integrals involving Gaussian functions.

Computer algorithms for the accurate calculation of this function are available.[4] The function was first introduced by Owen in 1956.[5]

Properties

T(h,0)=0
T(0,a)=12πarctan(a)
T(h,a)=T(h,a)
T(h,a)=T(h,a)
T(h,a)+T(ah,1a)=12(Φ(h)+Φ(ah))+Φ(h)Φ(ah)ifa0
T(h,a)+T(ah,1a)=12(Φ(h)+Φ(ah))+Φ(h)Φ(ah)12ifa<0
T(h,1)=12Φ(h)(1Φ(h))
T(0,x)dx=xT(0,x)14πln(1+x2)+C

More properties can be found in the literature.[6]

References

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Software

  • Owen's T function (user web site) - offers C++, FORTRAN77, FORTRAN90, and MATLAB libraries released under the LGPL license LGPL
  • Owen's T-function is implemented in Mathematica since version 8, as OwenT.

External links


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  1. Sowden, R R and Ashford, J R (1969). "Computation of the bivariate normal integral". Applied Statististics, 18, 169–180.
  2. Donelly, T G (1973). "Algorithm 462. Bivariate normal distribution". Commun. Ass. Comput.Mach., 16, 638.
  3. Schervish, M H (1984). "Multivariate normal probabilities with error bound". Applied Statistics, 33, 81–94.
  4. Patefield, M. and Tandy, D. (2000) "Fast and accurate Calculation of Owen’s T-Function", Journal of Statistical Software, 5 (5), 1–25.
  5. Owen, D B (1956). "Tables for computing bivariate normal probabilities". Annals of Mathematical Statistics, 27, 1075–1090.
  6. Template:Harvtxt