boxplotlog              package:StatDA              R Documentation

_B_o_x_p_l_o_t_l_o_g

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

     The function boxplot plots a boxplot of the data with respect to
     the logarithmic transformed values of the whiskers. See also
     details.

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

     boxplotlog(x, ..., range = 1.5, width = NULL, varwidth = FALSE, notch = FALSE,
     outline = TRUE, names, plot = TRUE, border = par("fg"), col = NULL, log = "",
     pars = list(boxwex = 0.8, staplewex = 0.5, outwex = 0.5), horizontal = FALSE,
     add = FALSE, at = NULL)

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

       x: data 

     ...: further arguments for creating the list 

   range: this determines how far the plot "whiskers" extend from the
          box. If range is positive, the most extreme data point which
          is no more than range times the length of the box away from
          the box. A value of zero causes the whiskers to extend to the
          data extremes. 

   width: a vector giving the relative widths of the boxes making up
          the plot 

varwidth: if varwidth is TRUE, the boxes are drawn with widths
          proportional to the square-roots of the number of
          observations in the groups. 

   notch: if notch is TRUE, a notch is drawn in each side of the boxes 

 outline: if outline is FALSE, the outliers are not drawn 

   names: define the names of the attributes 

    plot: if plot is TRUE the boxplot is plotted in the current plot 

  border: character or numeric (vector) which indicates the color of
          the box borders 

     col: defines the colour 

     log: character, indicating if any axis should be drawn in
          logarithmic scale 

    pars: some graphical parameters can be specified 

horizontal: logical parameter indicating if the boxplots should be
          horizontal; FALSE means vertical boxes 

     add: if TRUE the boxplot is added to the current plot 

      at: numeric vector giving the locations of the boxplots 

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

     Sometimes a boxplot of the original data does not identify
     outliers because the boxplot assumes normal distribution.
     Therefore the data are logarithmically transformed and values for
     plotting the boxplot are calculated. After that the data are
     backtransformed and the boxplot is plotted with respect to the
     logarithmic results. Now the outliers are identified.

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

   stats: a vector of length 5, containing the extreme of the lower
          whisker, the lower "hinge", the median, the upper "hinge" and
          the extreme of the upper whisker (backtransformed)

       n: the number of non-NA observations in the sample

    conf: the lower and upper extremes of the "notch"

     out: the values of any data points which lie beyond the extremes
          of the whiskers (backtransformed)

   group: the group

   names: the attributes

     Returns a boxplot which is calculated with the log-transformed
     data.

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

     Peter Filzmoser <P.Filzmoser@tuwien.ac.at>

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

     C. Reimann, P. Filzmoser, R.G. Garrett, and R. Dutter: Statistical
     Data Analysis Explained. Applied Environmental Statistics with R.
     John Wiley and Sons Inc. To appear.

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

     data(chorizon)
     Ba=chorizon[,"Ba"]

     boxplotlog((Ba),horizontal=TRUE,xlab="Ba [mg/kg]",cex.lab=1.4,pch=3,cex=1.5)

