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, ...)
          ## S3 method for class 'TSdata':
          distribution(obj, bandwidth=0.2, 
                  select.inputs = seq(length= nseriesInput(obj)),
                  select.outputs= seq(length=nseriesOutput(obj)), ...)
          ## Default S3 method:
          distribution(obj, bandwidth=0.2, series=NULL, ...)
          ## S3 method for class 'coefEstEval':
          distribution(obj,  Sort=FALSE, bandwidth=0.2,
             graphs.per.page=5, ...)
          ## S3 method for class 'rootsEstEval':
          distribution(obj, mod=TRUE, invert=FALSE, Sort=FALSE,
             bandwidth=0.2, select=NULL, ...)

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

     obj: an object as returned by EstEval.

    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'.

graphs.per.page: integer indicating number of graphs to place on a
          page.

  series: series to be plotted. (passed to selectSeries)

select.inputs: series to be plotted. (passed to selectSeries)

select.outputs: series to be plotted. (passed to selectSeries)

     ...: arguments passed to other methods.

  invert: logical indicating if the inverse of roots should be plotted

     mod: logical indicating if the modulus of roots should be plotted

  select: integer vector indicating roots to be plotted. If select  is
          not NULL then roots are sorted by magnitude and only the 
          indicated roots are plotted. For example, select=c(1,2)  will
          plot only  the two largest roots.

_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:

     'EstEval'

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

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

