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)

_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

_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

_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)

