

_M_e_d_i_a_n _A_b_s_o_l_u_t_e _D_e_v_i_a_t_i_o_n

     mad(x, center, constant=1.4826, na.rm=FALSE)

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

     `mad' provides a scale estimate based on the median
     absolute deviation.  The actual value calculated is
     `constant * (median(abs(x - center)))' with the default
     value of `center' being `median(x)'.

     The default `constant = 1.4826' is pprox Phi^{-1}(ac 3
     4)= 1.4826 ~=ensures consistency, i.e.,
     E[`mad'(X_1,...,X_n)] = sigma for X_i distributed as
     N(mu,sigma^2) and large n.

     If `na.rm' is `TRUE' then `NA' values are stripped from
     `x' before computation takes place.  If this is not
     done then an `NA' value in `x' will cause `mad' to
     return `NA'.

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

     `median', `var'.

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

     mad(c(1:9))
     print(mad(c(1:9),     constant=1)) ==
           mad(c(1:8,100), constant=1)       # = 2 ; TRUE

