influencPlot               package:car               R Documentation

_R_e_g_r_e_s_s_i_o_n _I_n_f_l_u_e_n_c_e _P_l_o_t

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

     This function creates a "bubble" plot of studentized residuals by
     hat values, with the areas of the circles representing the
     observations proportional to Cook's distances. Vertical reference
     lines are drawn at twice and three times the average hat value,
     horizontal reference lines at -2, 0, and 2 on the
     studentized-residual scale.

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

     influencePlot(model, ...)

     ## S3 method for class 'lm':
     influencePlot(model, scale=10, col=c(1,2), identify=c(TRUE, FALSE, "auto"),
                     labels=names(rstud), cex.identify=par("cex"), col.identify=par("col"), ...)

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

   model: a linear or generalized-linear model.

   scale: a factor to adjust the size of the circles.

     col: colors for plotting points that do not and do have noteworthy
          Cook's distances.

identify: identify points; if 'TRUE', the default, identify points
          interactively; if '"auto"' then points with large Cook's
          distances will automatically be identified.

  labels: a vector of observation labels.

cex.identify, col.identify: for point labels.

     ...: arguments to pass to the 'plot' function.

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

     Returns the indices of identified points.

_N_o_t_e:

     This function used to be named 'influence.plot'; the name was
     changed to avoid confusion with the 'influence' generic function.

_A_u_t_h_o_r(_s):

     John Fox jfox@mcmaster.ca

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

     J. Fox (2002)  _An R and S-PLUS Companion to Applied Regression_.
     Sage.

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

     'cookd', 'rstudent', 'hatvalues'

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

         influencePlot(lm(prestige ~ income + education, data=Duncan), 
             identify="auto")

