plot.cggd                package:cggd                R Documentation

_P_l_o_t _m_e_t_h_o_d _f_o_r _c_g_g_d _o_b_j_e_c_t_s

_D_e_s_c_r_i_p_t_i_o_n:

     Produce a plot of a cggd fit. The default is a complete
     coefficient path.

_U_s_a_g_e:

     plot.cggd(x, steps=5, breaks = TRUE, first_k=1,last_k=Inf, xvar=c("step","t"),omit.zeros = TRUE, eps = 1e-10, ...)

_A_r_g_u_m_e_n_t_s:

       x: cggd object

   steps: Number of steps to sample coefficients between each model
          iteration.

  breaks: If 'TRUE', then vertical lines are drawn at each break point
          in the piecewise linear coefficient paths

 first_k: The starting k, model iteration, to plot from.

  last_k: The final k, model iteration, to plot from.

    xvar: The type of x variable against which to plot. 'xvar=step'
          plots against iteration steps of the model (default).
          'xvar=t' plots against the _time_ along the coefficient path.

omit.zeros: When the number of variables  is much greater than the
          number of observations, many coefficients will never be
          nonzero; this logical (default 'TRUE') avoids plotting these
          zero coefficents

     eps: Definition of zero above, default is '1e-10'

     ...: Additonal arguments for generic plot. Can be used to set
          xlims, change colors, line widths, etc

_V_a_l_u_e:

     NULL

_A_u_t_h_o_r(_s):

     Cun-Hui Zhang and Ofer Melnik

_R_e_f_e_r_e_n_c_e_s:

     Cun-Hui Zhang (2007) "Continuous Generalized Gradient Descent"
     _Journal of Computational and Graphical Statistics_ ; see also
     <URL: http://stat.rutgers.edu/~cunhui/software/CGGD.html>.

_E_x_a_m_p_l_e_s:

     data(housing)
     attach(housing)
     object <- cggd(x,y)
     plot(object)
     detach(housing)

