

commonprob2sigma(bindata)                    R Documentation

_C_a_l_c_u_l_a_t_e _a _C_o_v_a_r_i_a_n_c_e _M_a_t_r_i_x _f_o_r _t_h_e _N_o_r_m_a_l _D_i_s_t_r_i_b_u_t_i_o_n
_o_u_t _o_f _a _M_a_t_r_i_x _o_f _J_o_i_n_t _P_r_o_b_a_b_i_l_i_t_e_s_.

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

     Computes a covariance matrix for a normal distribution
     which corresponds to a binary distribution with
     marginal probabilites given by `diag(commonprob)' and
     pairwise probabilities given by `commonprob'.

     For the simulations the values of `simulvals' are used.

     If a non-valid covariance matrix is the result, the
     program stops with an error in the case of NA arguments
     and yields are warning message if the matrix is not
     positive definite.

_U_s_a_g_e_:

     commonprob2sigma(commonprob, simulvals)

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

commonprob: Matrix of Pairwise Probabilities.

simulvals: Array received by `simul.commonprob'.

_V_a_l_u_e_:

     A covariance matrix is returned with the same dimen-
     sions as `commonprob'.

_A_u_t_h_o_r_(_s_)_:

     Friedrich Leisch

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

     Friedrich Leisch, Andreas Weingessel and Kurt Hornik
     (1998). On the generation of correlated artificial
     binary data. Working Paper Series, SFB ``Adaptive
     Information Systems and Modelling in Economics and Man-
     agement Science'', Vienna University of Economics,
     <URL: http://www.wu-wien.ac.at/am>

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

     `simul.commonprob'

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

     m <- cbind(c(1/2,1/5,1/6),c(1/5,1/2,1/6),c(1/6,1/6,1/2))
     sigma <- commonprob2sigma(m)

