sbaic               package:scaleboot               R Documentation

_A_k_a_i_k_e'_s _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:

     Extract or modify the AIC values for models.

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

     sbaic(x,...)
     ## S3 method for class 'scaleboot':
     sbaic(x,k,...)
     ## S3 method for class 'scalebootv':
     sbaic(x,...)

     sbaic(x) <- value
     ## S3 replacement method for class 'scaleboot':
     sbaic(x) <- value
     ## S3 replacement method for class 'scalebootv':
     sbaic(x) <- value

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

       x: an object used to select a method. 

       k: numeric, the penalty per parameter to be used.

   value: numeric vector of AIC values for models.

     ...: 

_D_e_t_a_i_l_s:

     'sbaic' can be used to modify the 'aic' components for models in
     'x' as shown in the examples below.

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

     For an object of class '"scaleboot"', 'sbaic' returns a numeric
     vector of AIC values for models.  If 'k' is missing, then the
     'aic' components in the 'fi' vector of 'x' are returned.  If 'k'
     is specified, 'rss-k*df' is calculated for each model. For the
     usual AIC, k=2.  For the BIC (Schwarz's Bayesian information
     criterion), 'k=log(sum(x$nb))'.

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

     Hidetoshi Shimodaira

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

     Sakamoto, Y., Ishiguro, M., and Kitagawa G. (1986). _Akaike
     Information Criterion Statistics_. D. Reidel Publishing Company.

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

     'sbfit'.

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

     data(mam15)
     a <- mam15.relltest[["t4"]] # an object of class "scaleboot"
     sbaic(a) # print AIC for models
     sbaic(a,k=log(sum(a$nb))) # print BIC for models
     sbaic(a) <- sbaic(a,k=log(sum(a$nb))) # set BIC
     sbaic(a) # print BIC for models

