NMixPredCondDensJoint2         package:mixAK         R Documentation

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_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 estimates of
     pairwise bivariate conditional densities (given one margin)
     obtained by using posterior summary statistics (e.g., posterior
     means) of mixture weights, means and variances (plug-in estimate).

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

     NMixPredCondDensJoint2(x, ...)

     ## Default S3 method:
     NMixPredCondDensJoint2(x, icond, scale, K, w, mu, Li, Krandom=FALSE, ...)

     ## S3 method for class 'NMixMCMC':
     NMixPredCondDensJoint2(x, icond, grid, lgrid=50, scaled=FALSE, ...)

     ## S3 method for class 'GLMM_MCMC':
     NMixPredCondDensJoint2(x, icond, grid, lgrid=50, scaled=FALSE, ...)

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

       x: an object of class 'NMixMCMC' for
          'NMixPredCondDensJoint2.NMixMCMC' function.

          An object of class 'GLMM_MCMC' for
          'NMixPredCondDensJoint2.GLMM_MCMC' function.

          A list with the grid values (see below) for
          'NMixPredCondDensJoint2.default' function. 

   icond: index of the margin by which we want to condition 

   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
          density should be evaluated. The value of 'grid[[icond]]'
          determines the values by which we condition.

          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 'NMixPredCondDensJoint2' 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.

   icond: index of the margin by which we condition.

    dens: a list with the computed conditional densities for each value
          of 'x[[icond]]'. Each 'dens[[j]]' is again a list with
          conditional densities for each pair of margins given margin
          'icond' equal to 'x[[icond]][j]'. The value of
          'dens[[j]][[i-k]]' gives values of conditional density of the
          (i,k)-th margins given margin 'icond' equal to
          'x[[icond]][j]'. 

     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

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

     'plot.NMixPredCondDensJoint2', 'NMixMCMC', 'GLMM_MCMC'.

