- Owen's T function
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In mathematics, Owen's T function T(h, a), named after statistician Donald Bruce Owens, is defined by
Contents
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]
Computer algorithms for the accurate calculation of this function are available.[4] The function was first introduced by Owen in 1956.[5]
References
- ^ 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". Ann. Math. Statist., 27, 1075–1090.
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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