Owen's T function

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

The function was first introduced by Owen in 1956.[1]


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[2][3] and, from there, in the calculation of multivariate normal distribution probabilities.[4] It also frequently appears in various integrals involving Gaussian functions.

Computer algorithms for the accurate calculation of this function are available;[5] quadrature having been employed since the 1970s. [6]


Here Φ(x) is the standard normal cumulative density function

More properties can be found in the literature.[7]


  1. ^ Owen, D B (1956). "Tables for computing bivariate normal probabilities". Annals of Mathematical Statistics, 27, 1075–1090.
  2. ^ Sowden, R R and Ashford, J R (1969). "Computation of the bivariate normal integral". Applied Statististics, 18, 169–180.
  3. ^ Donelly, T G (1973). "Algorithm 462. Bivariate normal distribution". Commun. Ass. Comput.Mach., 16, 638.
  4. ^ Schervish, M H (1984). "Multivariate normal probabilities with error bound". Applied Statistics, 33, 81–94.
  5. ^ Patefield, M. and Tandy, D. (2000) "Fast and accurate Calculation of Owen’s T-Function", Journal of Statistical Software, 5 (5), 1–25.
  6. ^ JC Young and Christoph Minder. Algorithm AS 76
  7. ^ Owen (1980)
  • Owen, D. (1980). "A table of normal integrals". Communications in Statistics: Simulation and Computation. B9: 389–419. 


  • 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[edit]