blasso.s3              package:monomvn              R Documentation

_S_u_m_m_a_r_i_z_i_n_g _B_a_y_e_s_i_a_n _L_a_s_s_o _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
     '"blasso"'-class object containing samples from the posterior
     distribution of a Bayesian lasso model

_U_s_a_g_e:

     ## S3 method for class 'blasso':
     print(x, ...)
     ## S3 method for class 'blasso':
     summary(object, burnin = 0, ...)
     ## S3 method for class 'blasso':
     plot(x, which=c("coef", "s2", "lambda2", "gamma",
         "tau2i","omega2", "nu", "m", "pi"), subset = NULL, burnin = 0,
         ... )
     ## S3 method for class 'summary.blasso':
     print(x, ...)

_A_r_g_u_m_e_n_t_s:

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

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

  subset: a vector of indicies that can be used to specify the a subset
          of the columns of 'tau2i' or 'omega2' that are plotted as
          boxplots in order to reduce clutter 

  burnin: number of burn-in rounds to discard before reporting
          summaries and making plots.  Must be non-negative and less
          than 'x$T'

   which: indicates the parameter whose characteristics should be
          plotted; does not apply to the 'summary' 

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

_D_e_t_a_i_l_s:

     'print.blasso' prints the 'call' followed by a brief summary of
     the MCMC run and a suggestion to try the summary and plot
     commands.  

     'plot.blasso' uses an appropriate 'plot' command on the 'list'
     entries of the '"blasso"'-class object thus visually summarizing
     the samples from the posterior distribution of each parameter in
     the model depending on the 'which' argument supplied.

     'summary.blasso' uses the 'summary' command on the list entries of
     the '"blasso"'-class object thus summarizing the samples from the
     posterior distribution of each parameter in the model.

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

_V_a_l_u_e:

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

       B: a copy of the input argument 'thin' 

       T: total number of MCMC samples to be collected from 'x$T' 

    thin: number of MCMC samples to skip before a sample is collected
          (via thinning) from 'x$T' 

    coef: a joint 'summary' of 'x$mu' and the columns of 'x$beta', the
          regression coefficients 

      s2: a 'summary' of 'x$s2', the variance parameter 

 lambda2: a 'summary' of 'x$lambda2', the penalty parameter, when lasso
          or ridge regression is active 

 lambda2: a 'summary' of 'x$gamma', when the NG extensions to the lasso
          are used 

   tau2i: a 'summary' of the columns of the latent 'x$tau2i' parameters
          when lasso is active 

  omega2: a 'summary' of the columns of the latent 'x$omega2'
          parameters when Student-t errors are active 

      nu: a 'summary' of 'x$nu', the degrees of freedom parameter, when
          the Student-t model is active 

     bn0: the estimated posterior probability that the individual
          components of the regression coefficients 'beta' is  nonzero  

       m: a 'summary' the model order 'x$m': the number of non-zero
          regression coefficients 'beta' 

      pi: the estimated Binomial proportion in the prior for the model
          order when 2-vector input is provided for 'mprior' 

_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:

     'blasso'

