vioplot               package:vioplot               R Documentation

_v_i_o_l_i_n _p_l_o_t

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

     Produce violin plot(s) of the given (grouped) values.

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

     vioplot( x, ..., range=1.5, h, ylim, names, horizontal=FALSE, 
       col="magenta", border="black", lty=1, lwd=1, rectCol="black", 
       colMed="white", pchMed=19, at, add=FALSE, wex=1, 
       drawRect=TRUE)

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

       x: data vector

     ...: additional data vectors

   range: a factor to calculate the upper/lower adjacent values

       h: the height for the density estimator, if omit as explained in
          sm.density, h will be set to an optimum

    ylim: y limits

   names: one label, or a vector of labels for the datas must match the
          number of datas given

col, border, lty, lwd: Graphical parameters for the violin passed to
          lines and polygon

rectCol, colMed, pchMed: Graphical parameters to control the look of
          the box

drawRect: logical. the box is drawn if 'TRUE'.

      at: position of each violin. Default to '1:n'

     add: logical. if FALSE (default) a new plot is created

     wex: relative expansion of the violin. 

horizontal: logical. horizontal or vertical violins

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

     A violin plot is a combination of a box plot and a kernel density
     plot.  Specifically, it starts with a box plot. It then adds a
     rotated kernel density plot to each side of the box plot.

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

     Daniel Adler dadler@uni-goettingen.de

     Romain Francois francoisromain@free.fr ; <URL:
     http://francoisromain.free.fr> :  horizontal violins and
     additionnal graphical parameters

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

     Hintze, J. L. and R. D. Nelson (1998).  _Violin plots: a box
     plot-density trace synergism._  The American Statistician,
     52(2):181-4.

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

     'boxplot' 'sm'

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

       # box- vs violin-plot 
       par(mfrow=c(2,1))
       mu<-2
       si<-0.6
       bimodal<-c(rnorm(1000,-mu,si),rnorm(1000,mu,si)) 
       uniform<-runif(2000,-4,4)
       normal<-rnorm(2000,0,3)
       vioplot(bimodal,uniform,normal)
       boxplot(bimodal,uniform,normal)
       
       # add to an existing plot
       x <- rnorm(100)
       y <- rnorm(100)
       plot(x, y, xlim=c(-5,5), ylim=c(-5,5))
       vioplot(x, col="tomato", horizontal=TRUE, at=-4, add=TRUE,lty=2, rectCol="gray")
       vioplot(y, col="cyan", horizontal=FALSE, at=-4, add=TRUE,lty=2)

