

_M_e_d_i_a_n _P_o_l_i_s_h _o_f _a _M_a_t_r_i_x

     medpolish(x, eps=0.01, maxiter=10, trace.iter = TRUE)

     plot(medpolish.obj)
     print(medpolish.obj)

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

     `medpolish' fits an additive "two-way" (constant + rows
     + columns) model to the values given in `x' using
     Tukey's median polish procedure.

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

     Sweeping out for row and column effects continues until
     the proportional reduction in the sum of absolute resi-
     duals is less than `eps' or until there have been `max-
     iter' iterations.  The sum of absolute residuals is
     printed at each iteration of the fitting process, if
     `trace.iter' is `TRUE'.

     `medpolish' returns an object of class `medpolish' (see
     below).  There are printing and plotting methods for
     this class, which are invoked via by the generics
     `print' and `plot'.

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

     An object of class `medpolish' with the following named
     components:

 overall: the fitted constant term.

     row: the fitted row effects.

     col: the fitted column effects.

residuals: the residuals.

    name: the name of the dataset.

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

     Tukey (1977). E.D.A; see ref. in `line'.

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

     `median'; `aov' which for a mean instead of median
     decomposition.

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

     ## Deaths from sport parachuting;  from ABC of EDA, p.224:
     deaths <-
         rbind(c(14,15,14),
               c( 7, 4, 7),
               c( 8, 2,10),
               c(15, 9,10),
               c( 0, 2, 0))
     dimnames(deaths) <- list(c("1-24", "25-74", "75-199", "200++", "NA"),
                              paste(1973:1975))
     deaths
     (med.d <- medpolish(deaths))
     plot(med.d)
     ## Check decomposition:
     all(deaths == med.d$overall + outer(med.d$row,med.d$col, "+") + med.d$resid)

