estfun               package:sandwich               R Documentation

_E_x_t_r_a_c_t _E_m_p_i_r_i_c_a_l _E_s_t_i_m_a_t_i_n_g _F_u_n_c_t_i_o_n_s

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

     Generic function for extracting the empirical estimating functions
     of a fitted model.

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

     estfun(x, ...)

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

       x: a fitted model object.

     ...: arguments passed to methods.

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

     A matrix containing the empirical estimating functions. Typically,
     this should be an n x k matrix corresponding to n observations and
     k parameters. The columns should be named as in 'coef' or 'terms',
     respectively.

     The estimating function (or score function) for a model is the
     derivative of the objective function with respect to the parameter
     vector. The empirical estimating functions is the evaluation of
     the estimating function at the observed data (n observations) and
     the estimated parameters (of dimension k).

_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:

     'lm', 'glm'

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

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

     ## estimating function: (y - x'beta) * x
     estfun(fm)
     residuals(fm) * cbind(1, x)

