meat                package:sandwich                R Documentation

_A _S_i_m_p_l_e _M_e_a_t _M_a_t_r_i_x _E_s_t_i_m_a_t_o_r

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

     Estimating the variance of the estimating functions of a
     regression model by cross products of the empirical estimating
     functions.

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

     meat(x, adjust = FALSE, ...)

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

       x: a fitted model object.

  adjust: logical. Should a finite sample adjustment be made? This
          amounts to multiplication with 

                               n/(n-k)

          where 

                                  n

          is the number of observations and 

                                  k

          the number of estimated parameters.

     ...: arguments passed to the 'estfun' function.

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

     For some theoretical background along with implementation details
     see Zeileis (2006).

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

     A 

                                k x k

     matrix corresponding containing the scaled cross products of the
     empirical estimating functions.

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

     Zeileis A (2006), Object-oriented Computation of Sandwich
     Estimators. _Journal of Statistical Software_, *16*(9), 1-16. URL
     <URL: http://www.jstatsoft.org/v16/i09/>.

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

     'sandwich', 'bread', 'estfun'

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

     x <- sin(1:10)
     y <- rnorm(10)
     fm <- lm(y ~ x)

     meat(fm)
     meatHC(fm, type = "HC")
     meatHAC(fm)

