decomp2sigma             package:mclust             R Documentation

_C_o_n_v_e_r_t _m_i_x_t_u_r_e _c_o_m_p_o_n_e_n_t _c_o_v_a_r_i_a_n_c_e_s _t_o _m_a_t_r_i_x _f_o_r_m.

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

     Converts covariances from a parameterization by  eigenvalue
     decomposition  or cholesky factorization to representation as a
     3-D array.

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

     decomp2sigma(d, G, scale, shape, orientation, ...)

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

       d: The dimension of the data.  

       G: The number of components in the mixture model.  

   scale: Either a _G_-vector giving the scale of the covariance (the
          _d_th root of its determinant) for each component in the
          mixture model, or a single numeric value if the scale is the
          same for each component.   

   shape: Either a _G_ by _d_ matrix in which the _k_th column is the
          shape of the covariance matrix (normalized to have
          determinant 1) for the _k_th component, or a _d_-vector
          giving a common shape for all components.  

orientation: Either a _d_ by _d_ by _G_ array whose '[,,k]'th entry is
          the orthonomal matrix of eigenvectors of the covariance
          matrix of the _k_th component, or a _d_ by _d_ orthonormal
          matrix if the mixture components have a common orientation.
          The 'orientation' component of 'decomp' can be omitted in
          spherical and diagonal models, for which the principal
          components are parallel to the coordinate axes so that the
          orientation matrix is the identity.   

     ...: Catches unused arguments from an indirect or list call via
          'do.call'. 

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

     A 3-D array whose '[,,k]'th component is the  covariance matrix of
     the _k_th component in an MVN mixture model.

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

     C. Fraley and A. E. Raftery (2002). Model-based clustering,
     discriminant analysis, and density estimation. _Journal of the
     American Statistical Association 97:611-631_. 

     C. Fraley and A. E. Raftery (2006). MCLUST Version 3 for R: Normal
     Mixture Modeling and Model-Based Clustering,  Technical Report no.
     504, Department of Statistics, University of Washington.

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

     'sigma2decomp'

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

     meEst <- meVEV(iris[,-5], unmap(iris[,5])) 
     names(meEst)
     meEst$parameters$variance

     dec <- meEst$parameters$variance
     decomp2sigma(d=dec$d, G=dec$G, shape=dec$shape, scale=dec$scale,
                  orientation = dec$orientation)
     ## Not run: 
     do.call("decomp2sigma", dec)  ## alternative call
     ## End(Not run)

