

mixproj(mclust)                              R Documentation

_D_i_s_p_l_a_y_s _o_n_e _s_t_a_n_d_a_r_d _d_e_v_i_a_t_i_o_n _o_f _a_n _M_V_N _m_i_x_t_u_r_e _c_l_a_s_s_i_f_i_-
_c_a_t_i_o_n_.

_U_s_a_g_e_:

     mixproj(data, ms, partition, scale = F, newframe = T, k = 15, ...)

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

    data: a matrix of onservations.

      ms: The result of an `mstep' calculation (a list con-
          sisting of `mu' and `sigma' or `sigmasq').

partition: A integer vector giving an initail classification
          for each observation.

  dimens: A vector of length two giving the two variables of
          the data to be plotted.

   scale: A logical variable telling whether or not the same
          scale should be used for both variables so as to
          preserve geometry. The default does not use the
          same scale.

newframe: A logical variable indicating whether or not
          `frame' should be invoked before plotting. The
          default is to invoke `frame'.

       k: Number of subdivisions for plotting segments of
          ellipsoids. Default: 8.

     ...: use for the argument `symbols' indicating the
          desired symbols to be plotted (in the order that
          they appear in the classification).

_D_E_S_C_R_I_P_T_I_O_N_:

     Displays one standard deviation of an MVN mxiture clas-
     sification along with data in for selected pairs of
     coordinates.

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

     `mstep', `clpairs'

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

     data(iris)
     cl <- mhclass(mhtree(iris[,1:4], modelid = "VVV"),3)
     z <- me( iris[,1:4], modelid = "VVV", ctoz(cl))
     pars <- mstep(iris[,1:4], modelid="VVV", z)
     mixproj(iris[,1:4], ms=pars, partition=ztoc(z), dimens=c(1,2))

