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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> | |||
==Applications== | |||
The function ''T''(''h'', ''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, 169–180.</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, 81–94.</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), 1–25. | |||
</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, 1075–1090.</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(h, a), named after statistician Donald Bruce Owen, is defined by
Applications
The function T(h, a) 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
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
- Why You Should Care about the Obscure (Wolfram blog post)
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- ↑ Sowden, R R and Ashford, J R (1969). "Computation of the bivariate normal integral". Applied Statististics, 18, 169–180.
- ↑ Donelly, T G (1973). "Algorithm 462. Bivariate normal distribution". Commun. Ass. Comput.Mach., 16, 638.
- ↑ Schervish, M H (1984). "Multivariate normal probabilities with error bound". Applied Statistics, 33, 81–94.
- ↑ Patefield, M. and Tandy, D. (2000) "Fast and accurate Calculation of Owen’s T-Function", Journal of Statistical Software, 5 (5), 1–25.
- ↑ Owen, D B (1956). "Tables for computing bivariate normal probabilities". Annals of Mathematical Statistics, 27, 1075–1090.
- ↑ Template:Harvtxt