monomvn.s3              package:monomvn              R Documentation

_S_u_m_m_a_r_i_z_i_n_g _m_o_n_o_m_v_n _o_u_t_p_u_t

_D_e_s_c_r_i_p_t_i_o_n:

     Summarizing, printing, and plotting the contents of a
     '"monomvn"'-class object

_U_s_a_g_e:

     ## S3 method for class 'monomvn':
     summary(object, Si = FALSE, ...)
     ## S3 method for class 'summary.monomvn':
     print(x, ...)
     ## S3 method for class 'summary.monomvn':
     plot(x, gt0 = FALSE, main = NULL,
          xlab = "number of zeros", ...)

_A_r_g_u_m_e_n_t_s:

  object: a '"monomvn"'-class object that must be named 'object' for
          the generic methods 'summary.monomvn' 

       x: a '"monomvn"'-class object that must be named 'x' for generic
          printing and plotting via 'print.summary.monomvn' and
          'plot.summary.monomvn' 

      Si: boolean indicating whether 'object$S' should be inverted and
          inspected for zeros within 'summary.monomvn', indicating
          pairwise independence; default is 'FALSE' 

     gt0: boolean indicating whether the histograms in
          'plot.summary.monomvn' should exclude columns of 'object$S'
          or 'Si' without any zero entries 

    main: optional text to be added to the main title of the histograms
          produced by the generic 'plot.summary.monomvn' 

    xlab: label for the x-axes of the histograms produced by
          'plot.summary.monomvn'; otherwise default
          automatically-generated text is used 

     ...: passed to 'print.monomvn', or 'plot.default'

_D_e_t_a_i_l_s:

     These functions work on the output from both 'monomvn' and
     'bmonomvn'.

     'print.monomvn' prints the 'call' followed by a summary of the
     regression  method used at each iteration of the algorithm.  It
     also indicates how many completely observed features (columns)
     there were in the data. For non-least-squares regressions (i.e.,
     'plsr', 'lars' and 'lm.ridge' methods) and indication of the
     method used for selecting the number of components (i.e., 'CV',
     'LOO', etc., or 'none') is provided

     'summary.monomvn' summarizes information about the number of zeros
     in the estimated covariance matrix 'object$S' and its inverse

     'print.summary.monomvn' calls 'print.monomvn' on the 'object' and
     then prints the result of 'summary.monomvn'

     'plot.summary.monomvn' makes histograms of the number of zeros in
     the columns of 'object$S' and its inverse

_V_a_l_u_e:

     'summary.monomvn' returns a '"summary.monomvn"'-class object,
     which is a 'list' containing (a subset of) the items below.  The
     other functions do not return values.

     obj: the '"monomvn"'-class 'object' 

    marg: the proportion of zeros in 'object$S' 

      S0: a vector containing the number of zeros in each column of
          'object$S' 

    cond: if input 'Si = TRUE' this field contains the proportion of
          zeros in the inverse of 'object$S' 

     Si0: if input 'Si = TRUE' this field contains a vector with the
          number of zeros in each column of the inverse of 'object$S' 

_N_o_t_e:

     There is one further S3 function for '"monomvn"'-class objects
     that has its own help file: 'plot.monomvn'

_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:

     'bmonomvn', 'monomvn', 'plot.monomvn'

