NMixPredDensJoint2           package:mixAK           R Documentation

_P_a_i_r_w_i_s_e _b_i_v_a_r_i_a_t_e _p_r_e_d_i_c_t_i_v_e _d_e_n_s_i_t_y

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

     This function serves as an inference tool for the MCMC output
     obtained using the function 'NMixMCMC'. It computes estimated
     posterior predictive densities for each pair of margins.

_U_s_a_g_e:

     NMixPredDensJoint2(x, ...)

     ## Default S3 method:
     NMixPredDensJoint2(x, scale, K, w, mu, Li, Krandom=TRUE, ...)

     ## S3 method for class 'NMixMCMC':
     NMixPredDensJoint2(x, grid, lgrid=50, scaled=FALSE, ...)

     ## S3 method for class 'NMixMCMC':
     NMixPredDensJoint2(x, grid, lgrid=50, scaled=FALSE, ...)

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

       x: an object of class 'NMixMCMC' for
          'NMixPredDensJoint2.NMixMCMC' function.

          an object of class 'NMixMCMC' for
          'NMixPlugDensJoint2.NMixMCMC' function.

          A list with the grid values (see below) for
          'NMixPredDensJoint2.default' function. 

   scale: a two component list giving the 'shift' and the 'scale'. If
          not given, shift is equal to zero and scale is equal to one.

       K: either a number (when 'Krandom'='FALSE') or a numeric vector
          with the chain for the number of mixture components.

       w: a numeric vector with the chain for the mixture weights.

      mu: a numeric vector with the chain for the mixture means.

      Li: a numeric vector with the chain for the mixture inverse
          variances (lower triangles only).

 Krandom: a logical value which indicates whether the number of mixture
          components changes from one iteration to another.

    grid: a list with the grid values for each margin in which the
          predictive density should be evaluated.

          If 'grid' is not specified, it is created automatically using
          the information from the posterior summary statistics stored
          in 'x'. 

   lgrid: a length of the grid used to create the 'grid' if that is not
          specified.

  scaled: if 'TRUE', the density of shifted and scaled data is
          summarized. The shift and scale vector are taken from the
          'scale' component of the object 'x'.

     ...: optional additional arguments.

_V_a_l_u_e:

     An object of class 'NMixPredDensJoint2' which has the following
     components:   

       x: a list with the grid values for each margin. The components
          of the list are named 'x1', ... or take names from 'grid'
          argument.

   freqK: frequency table for the values of K (numbers of mixture
          components) in the MCMC chain.

   propK: proportions derived from 'freqK'.

MCMC.length: the length of the MCMC used to compute the predictive
          densities.

    dens: a list with the computed predictive densities for each pair
          of margins. The components of the list are named '1-2',
          '1-3', ..., i.e., 'dens[[1]]'='dens[["1-2"]]' is the pairwise
          predictive density for margins 1 and 2, etc. Each component
          of the 'list' is a matrix in such a form that it can be
          directly passed together with the proper components of 'x' to
          the plotting functions like 'contour' or 'image'. 

   densK: a list with the computed predictive densities for each
          margin, conditioned further by K. The components of the list
          are named '1-2', '1-3', .... That is, 'dens[[1]][[1]]' =
          'dens[["1-2"]][[1]]' is the pairwise predictive  density for
          margins 1 and 2 conditioned by K=1, 'dens[[1]][[2]]' =
          'dens[["1-2"]][[2]]' is the pairwise predictive density for
          margins 1 and 2 conditioned by K=2 etc.

          Note that 'densK' provides some additional information only
          when 'Krandom' = 'TRUE' or when 'x' results from the
          'NMixMCMC' call to the reversible jump MCMC. 

     There is also a 'plot' method implemented for the resulting
     object.

_A_u_t_h_o_r(_s):

     Arno&#353t Kom&#225rek arnost.komarek[AT]mff.cuni.cz

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

     Kom&#225rek, A. A new R package for Bayesian estimation of
     multivariate normal mixtures allowing for selection  of the number
     of components and interval-censored data. _Computational
     Statistics and Data Analysis_, *53*, 3932-3947.

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

     'plot.NMixPredDensJoint2', 'NMixMCMC', 'GLMM_MCMC',
     'NMixPredDensMarg'.

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

     ## See additional material available in 
     ## YOUR_R_DIR/library/mixAK/doc/
     ## or YOUR_R_DIR/site-library/mixAK/doc/
     ## - files Galaxy.pdf, Faithful.pdf, Tandmob.pdf

