plotcorr               package:ellipse               R Documentation

_P_l_o_t _c_o_r_r_e_l_a_t_i_o_n _m_a_t_r_i_x _e_l_l_i_p_s_e_s

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

     This function plots a correlation matrix using ellipse-shaped
     glyphs for each entry.  The ellipse represents a level curve of
     the density of a bivariate normal with the matching correlation.

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

     plotcorr(corr, outline = TRUE, col = "grey", numbers = FALSE, ...)

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

    corr: A matrix containing entries between '-1' and '1' to be
          plotted as correlations.   

 outline: Whether the ellipses should be outlined in the default
          colour. 

     col: Which colour(s) to use to fill the ellipses.   

 numbers: Whether to plot numerical correlations in place of ellipses. 
          If numbers is 'TRUE', then the correlations will be rounded
          to a single decimal place and placed on the plot. 

     ...: Additional graphical parameters. 

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

     The ellipses being plotted will be tangent to a unit character
     square, with the shape chosen to match the required correlation. 
     If 'numbers = FALSE', the 'col' vector will be recycled to colour
     each of the ellipses; if 'TRUE', it will be ignored.

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

     Murdoch, D.J. and Chow, E.D. (1996). A graphical display of large 
     correlation matrices. The American Statistician 50, 178-180.

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

     'ellipse'

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

     save.par <- par(ask = TRUE)    

     # Plot the correlation matrix for the mtcars data full model fit 
     data(mtcars)
     fit <- lm(mpg ~ ., mtcars)
     plotcorr(summary(fit, correlation = TRUE)$correlation)

     # Plot a second figure with numbers in place of the
     # ellipses
     plotcorr(summary(fit, correlation = TRUE)$correlation, numbers = TRUE)

     # Colour the ellipses to emphasize the differences
     corr.mtcars <- cor(mtcars)
     ord <- order(corr.mtcars[1,])
     xc <- corr.mtcars[ord, ord]
     plotcorr( xc, col=cm.colors(11)[5*xc + 6])

     par(save.par)

