BIC                  package:stats4                  R Documentation

_B_a_y_e_s_i_a_n _I_n_f_o_r_m_a_t_i_o_n _C_r_i_t_e_r_i_o_n

_D_e_s_c_r_i_p_t_i_o_n:

     This generic function calculates the Bayesian information
     criterion, also known as Schwarz's Bayesian criterion (SBC), for
     one or several fitted model objects for which a log-likelihood
     value can be obtained, according to the formula -2*log-likelihood
     + npar*log(nobs), where npar  represents the number of parameters
     and nobs the number of observations in the fitted model.

_U_s_a_g_e:

     BIC(object, ...)

_A_r_g_u_m_e_n_t_s:

  object: An object of a suitable class for the BIC to be calculated -
          usually a '"logLik"' object or an object for which a 'logLik'
          method exists. 

     ...: Some methods for this generic function may take additional,
          optional arguments.  At present none do.

_V_a_l_u_e:

     Returns a numeric value with the corresponding BIC.

_R_e_f_e_r_e_n_c_e_s:

     Schwarz, G. (1978) "Estimating the Dimension of a Model", Annals
     of Statistics, 6, 461-464.

_S_e_e _A_l_s_o:

     'logLik-methods', 'AIC-methods'

_E_x_a_m_p_l_e_s:

     data(swiss)
     lm1 <- lm(Fertility ~ . , data = swiss)
     AIC(lm1)
     BIC(lm1)

