Qn                package:robustbase                R Documentation

_R_o_b_u_s_t _L_o_c_a_t_i_o_n-_F_r_e_e _S_c_a_l_e _E_s_t_i_m_a_t_e _M_o_r_e _E_f_f_i_c_i_e_n_t _t_h_a_n _M_A_D

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

     Compute the robust scale estimator Qn, an efficient alternative to
     the MAD.

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

     Qn(x, constant = 2.2219, finite.corr = missing(constant))

     s_Qn(x, mu.too = FALSE, ...)

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

       x: numeric vector of observations.

constant: number by which the result is multiplied; the default
          achieves consisteny for normally distributed data.

finite.corr: logical indicating if the finite sample bias correction
          factor should be applied.  Default to 'TRUE' unless
          'constant' is specified.

  mu.too: logical indicating if the 'median(x)' should also be returned
          for 's_Qn()'.

     ...: potentially further arguments for 's_Qn()' passed to 'Qn()'.

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

     ............  FIXME ........

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

     'Qn()' returns a number, the Qn robust scale estimator, scaled to
     be consistent for sigma^2 and i.i.d. Gaussian observatsions,
     optionally bias corrected for finite samples.

     's_Qn(x, mu.too=TRUE)' returns a length-2 vector with location
     (mu) and scale; this is typically only useful for 'covOGK(*,
     sigmamu = s_Qn)'.

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

     Original Fortran code: Christophe Croux and Peter Rousseeuw
     rousse@wins.uia.ac.be. 
      Port to C and R: Martin Maechler, maechler@R-project.org

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

     Rousseeuw, P.J. and Croux, C. (1993) Alternatives to the Median
     Absolute Deviation, _Journal of the American Statistical
     Association_ *88*, 1273-1283.

     Christophe Croux and Peter J. Rousseeuw (1992) Time-Efficient
     Algorithms for Two Highly Robust Estimators of Scale,
     _Computational Statistics, Vol. 1_, ed. Dodge and Whittaker,
     Physica-Verlag Heidelberg, 411-428;
      also available from <URL:
     http://win-www.uia.ac.be/u/statis/abstract/Timeff92.htm>.

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

     'mad' for the 'most robust' but much less efficient scale
     estimator; 'Sn' for a similar faster but less efficient
     alternative; 'scaleTau2'.

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

     set.seed(153)
     x <- sort(c(rnorm(80), rt(20, df = 1)))
     s_Qn(x, mu.too = TRUE)
     Qn(x, finite.corr = FALSE)

