rmono                package:monomvn                R Documentation

_R_a_n_d_o_m_l_y _I_m_p_o_s_e _a _M_o_n_o_t_o_n_e _M_i_s_s_i_n_g_n_e_s_s _P_a_t_t_e_r_n

_D_e_s_c_r_i_p_t_i_o_n:

     Randomly impose a monotone missingness pattern by replacing the
     ends of each column of the input matrix by a random number of
     'NA's

_U_s_a_g_e:

     rmono(x, m = 7, ab = NULL)

_A_r_g_u_m_e_n_t_s:

       x: data 'matrix' 

       m: minimum number of non-'NA' entries in each column 

      ab: a two-vector of alpha ('ab[1]') and beta ('ab[2]') parameters
          to a Beta(alpha, beta) distribution describing the proportion
          of 'NA' entries in each column. The default setting 'ab =
          NULL' yields a uniform distribution 

_D_e_t_a_i_l_s:

     The returned 'x' always has one (randomly selected) complete
     column, and no column has fewer than 'm' non-missing entries. 
     Otherwise, the proportion of missing entries in each column can be
     uniform, or it can have a beta distribution with parameters alpha
     ('ab[1]') and beta ('ab[2]')

_V_a_l_u_e:

     returns a 'matrix' with the same dimensions as the input 'x'

_A_u_t_h_o_r(_s):

     Robert B. Gramacy bobby@statslab.cam.ac.uk

_R_e_f_e_r_e_n_c_e_s:

     <URL: http://www.statslab.cam.ac.uk/~bobby/monomvn.html>

_S_e_e _A_l_s_o:

     'randmvn'

_E_x_a_m_p_l_e_s:

     out <- randmvn(10, 3)
     rmono(out$x)

