etahat              package:calibrator              R Documentation

_E_x_p_e_c_t_a_t_i_o_n _o_f _c_o_m_p_u_t_e_r _o_u_t_p_u_t

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

     Returns the apostiori expectation of the computer program at a
     particular point with a particular set of parameters, given the
     code output.

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

     etahat(D1, D2, H1, y, E.theta, extractor, phi)

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

      D1: Matrix of code observation points and parameters

      D2: Matrix of field observation points

      H1: Basis functions

       y: Code observations corresponding to rows of 'D1'

 E.theta: expectation wrt theta; see details

extractor: Extractor function

   theta: Parameters

     phi: Hyperparameters

_D_e_t_a_i_l_s:

     Argument 'E.theta' is officially a function that, given x,y
     returns E_theta(h1(x,theta)).

     However, if supplied a non-function (this is tested by
     'is.function()' in the code), 'E.theta' is interpreted as values
     of theta to use.  Recycling is carried out by function 'D1.fun()'

_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:

     'p.page4'

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

     data(toys)

     etahat(D1=D1.toy, D2=D2.toy, H1=H1.toy, y=y.toy, E.theta=E.theta.toy, extractor=extractor.toy, phi=phi.toy)

     # Now try giving E.theta=1:3, which will be interpreted as a value for theta:
     etahat(D1=D1.toy, D2=D2.toy, H1=H1.toy, y=y.toy, E.theta=1:3, extractor=extractor.toy, phi=phi.toy)

