bic                  package:mclust                  R Documentation

_B_I_C _f_o_r _P_a_r_a_m_e_t_e_r_i_z_e_d _G_a_u_s_s_i_a_n _M_i_x_t_u_r_e _M_o_d_e_l_s

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

     Computes the BIC (Bayesian Information Criterion) for
     parameterized mixture models given the loglikelihood, the
     dimension of the data, and number of mixture components in the
     model.

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

     bic(modelName, loglik, n, d, G, noise=FALSE, equalPro=FALSE, ...)

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

modelName: A character string indicating the model. The help file for
          'mclustModelNames' describes the available models. 

  loglik: The loglikelihood for a data set with respect to the Gaussian
          mixture model specified in the 'modelName' argument. 

       n: The number of observations in the data used to compute
          'loglik'. 

       d: The dimension of the data used to compute 'loglik'. 

       G: The number of components in the Gaussian mixture model used
          to compute 'loglik'. 

   noise: A logical variable indicating whether or not the model
          includes an optional Poisson noise component. The default is
          to assume no noise component. 

equalPro: A logical variable indicating whether or not the components
          in the model are assumed to be present in equal proportion.
          The default is to assume unequal mixing proportions. 

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

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

     The BIC or Bayesian Information Criterion for the given input
     arguments.

_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:

     'nVarParams', 'mclustBIC', 'do.call'.

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

     n <- nrow(iris)
     d <- ncol(iris)-1
     G <- 3

     emEst <- me(modelName="VVI", data=iris[,-5], unmap(iris[,5]))
     names(emEst)

     args(bic)
     bic(modelName="VVI", loglik=emEst$loglik, n=n, d=d, G=G)
     ## Not run: do.call("bic", emEst)    ## alternative call

