STK: a Small (Matlab/Octave) Toolbox for Kriging
 STK_DISTRIB_STUDENT_EI computes the Student expected improvement

 CALL: EI = stk_distrib_student_ei (Z, NU)

    computes the expected improvement of a Student random variable with NU
    degrees of freedom above the threshold Z.

 CALL: EI = stk_distrib_student_ei (Z, NU, MU, SIGMA)

    computes the expected improvement of a Student random variable with NU
    degrees of freedom, location parameter MU and scale parameter SIGMA,
    above the threshold Z.

 CALL: EI = stk_distrib_student_ei (Z, NU, MU, SIGMA, MINIMIZE)

    computes the expected improvement of a Student random variable with NU
    degrees of freedom, location parameter MU and scale parameter SIGMA,
    below the threshold Z if MINIMIZE is true, above the threshold Z
    otherwise.

 REFERENCES

   [1] R. Benassi, J. Bect and E. Vazquez.  Robust Gaussian process-based
       global optimization using a fully Bayesian expected improvement
       criterion.  In: Learning and Intelligent Optimization (LION 5),
       LNCS 6683, pp. 176-190, Springer, 2011

   [2] B. Williams, T. Santner and W. Notz.  Sequential Design of Computer
       Experiments to Minimize Integrated Response Functions. Statistica
       Sinica, 10(4):1133-1152, 2000.

 See also stk_distrib_normal_ei