distribution              package:dse2              R Documentation

_P_l_o_t _d_i_s_t_r_i_b_u_t_i_o_n _o_f _e_s_t_i_m_a_t_e_s

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

     Plot distribution of estimates.

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

         distribution(obj, ...)
          distribution(obj, bandwidth=0.2, series=NULL)
          distribution(obj, bandwidth=0.2, series=NULL)
          distribution(obj, ...)
          distribution(obj,  Sort=F, bandwidth=0.2,
             graphs.per.page=5)
          distribution(obj, mod=T, invert=F, Sort=F,
             bandwidth=0.2, select=NULL)

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

     obj: An object as returned by eval.estimation.

    Sort: If Sort is true then sort is applied. This helps (a bit) with
          estimation methods like black.box which may not return
          parameters of the same length or in the same order.

bandwidth: Passed to `density' or `ksmooth'.

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

     `ksmooth' is applied if available to get a smoothed  estimate of
     the distribution of the estimates. If `ksmooth' is not available
     then `density' is applied if it is available.

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

     None

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

     `eval.estimation'

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

     if(is.R()) data("eg1.DSE.data.diff", package="dse1")
     model <- est.VARX.ls(TSdata(output=output.data(eg1.DSE.data.diff)), max.lag=2)
     # now use this as the true model
     z <-  eval.estimation(model, 
         estimation="est.VARX.ls", estimation.args=list(max.lag=2))
     distribution(z) 
     tfplot(z)

