commonprob2sigma           package:bindata           R Documentation

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_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 dimensions 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 Management 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)

