Vd                package:calibrator                R Documentation

_V_a_r_i_a_n_c_e _m_a_t_r_i_x _f_o_r _d

_D_e_s_c_r_i_p_t_i_o_n:

     Variance matrix for d, as per the bottom of page 1 of the
     supplement

_U_s_a_g_e:

     Vd(D1, D2, theta, phi)

_A_r_g_u_m_e_n_t_s:

      D1: matrix of code run points

      D2: matrix of observation points

   theta: Parameters

     phi: hyperparameters

_A_u_t_h_o_r(_s):

     Robin K. S. Hankin

_R_e_f_e_r_e_n_c_e_s:

     M. C. Kennedy and A. O'Hagan 2001. "Bayesian calibration of
     computer models".  Journal of the Royal Statistical Society B,
     63(3) pp425-464

     M. C. Kennedy and A. O'Hagan 2001.  "Supplementary details on
     Bayesian calibration of computer models", Internal report,
     University of Sheffield.  Available at <URL:
     http://www.shef.ac.uk/~st1ao/ps/calsup.ps>

     R. K. S. Hankin 2005. "Introducing BACCO, an R bundle for Bayesian
     analysis of computer code output", Journal of Statistical
     Software, 14(16)

_S_e_e _A_l_s_o:

     'H.fun','V1','V2','C1'

_E_x_a_m_p_l_e_s:

     data(toys)
     Vd(D1=D1.toy, D2=D2.toy, theta=theta.toy, phi=phi.toy)

