bagplot               package:aplpack               R Documentation

_b_a_g_p_l_o_t, _a _b_i_v_a_r_i_a_t_e _b_o_x_p_l_o_t

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

     'compute.bagplot()' computes an object describing a bagplot of a
     bivariate data set.  'plot.bagplot()' plots a bagplot object. 
     'bagplot()' computes and plots a bagplot.

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

     bagplot(x, y, factor = 3, approx.limit = 300,  
            show.outlier = TRUE, show.whiskers = TRUE, 
            show.looppoints = TRUE, show.bagpoints = TRUE,
            show.loophull = TRUE, show.baghull = TRUE, 
            create.plot = TRUE, add = FALSE, pch = 16, cex = 0.4, 
            dkmethod = 2, precision = 1, verbose = FALSE, 
            debug.plots = "no",   col.loophull="#aaccff", 
            col.looppoints="#3355ff", col.baghull="#7799ff", 
            col.bagpoints="#000088", transparency=FALSE, ...
     )

     compute.bagplot(x, y, factor = 3, approx.limit = 300, 
            dkmethod = 2, precision = 1, verbose = FALSE, 
            debug.plots = "no")

     plot.bagplot(x,  
            show.outlier = TRUE, show.whiskers = TRUE, 
            show.looppoints = TRUE, show.bagpoints = TRUE,
            show.loophull = TRUE, show.baghull = TRUE, 
            add = FALSE, pch = 16, cex = 0.4, verbose = FALSE, 
            col.loophull="#aaccff", col.looppoints="#3355ff", 
            col.baghull="#7799ff", col.bagpoints="#000088", 
            transparency=FALSE,...)

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

       x: x values of a data set;  in 'bagplot': an object of class
          'bagplot' computed by 'compute.bagplot' 

       y: y values of the data set 

  factor: factor defining the loop 

approx.limit: precision of approximation, default: 300 

show.outlier: if TRUE outlier are shown 

show.whiskers: if TRUE whiskers are shown 

show.looppoints: if TRUE loop points are plottet 

show.bagpoints: if TRUE bag points are plottet 

show.loophull: if TRUE the loop is plotted 

show.baghull: if TRUE the bag is plotted 

create.plot: if FALSE no plot is created 

     add: if TRUE the bagplot is added to an existing plot 

     pch: sets the plotting character 

     cex: sets characters size

dkmethod: 1 or 2, there are two method of   approximating the bag, 
          currently under construction

precision: precision of approximation, default: 1 

 verbose: automatic commenting of calculations  

debug.plots: developers' tool for debugging 

col.loophull: color of loop hull 

col.looppoints: color of the points of the loop 

col.baghull: color of bag hull 

col.bagpoints: color of the points of the bag 

transparency: see section details 

     ...: additional graphical parameters 

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

     A bagplot is a bivariate generalization of the well known boxplot.
     It has been proposed by Rousseeuw, Ruts, and Tukey. In the
     bivariate case the box of the boxplot changes to a  convex hull,
     the bag of bagplot. In the bag are 50 percent of all points. The
     fence separates points in the fence from  points outside. It is
     computed by increasing the the bag. The loop is defined as the
     convex polygon containing  all points inside the fence.  If all
     points are on a straight line you get a classical boxplot.
     'bagplot()' plots bagplots that are very similar  to the one
     described in Rousseeuw et al.  Remarks: The two dimensional median
     is approximated. There are known difficulties with small data sets
      (But I think it is not wise to make a (graphical)  summary of
     e.g. 10 points.)

     In case people want to plot multiple (overlappIng) bagplots, it is
     convenient if the plots are semi-transparent. For this reason the
     'transparency' flag has been added to the bagplot command.  If
     'transparency==TRUE' the alpha layer is set to '99' (hex). This
     causes the bagplots to appear semi-transparent, but ONLY if the
     output device is PDF and opened using: 'pdf(file="filename.pdf",
     version="1.4")'.  For this reason, the default is
     'transparency==FALSE'.  This feature as well as the arguments to
     specify different colors has been proposed by Wouter Meuleman.

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

     'compute.bagplot' returns an object of class 'bagplot' that could
     be plotted by  'plot.bagplot()'.

_N_o_t_e:

     The development of the function has not been finished.  Version
     02/2006

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

     Peter Wolf

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

     P. J. Rousseeuw, I. Ruts, J. W. Tukey (1999): The bagplot: a
     bivariate boxplot, The American Statistician, vol. 53, no. 4,
     382-387

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

     'boxplot'

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

       # example: 100 random points and one outlier
       dat<-cbind(rnorm(100)+100,rnorm(100)+300)
       dat<-rbind(dat,c(105,295))
       bagplot(dat,factor=2.5,create.plot=TRUE,approx.limit=300,
          show.outlier=TRUE,show.looppoints=TRUE,
          show.bagpoints=TRUE,dkmethod=2,
          show.whiskers=TRUE,show.loophull=TRUE,
          show.baghull=TRUE,verbose=FALSE)
       # example of Rousseeuw et al., see R-package rpart
       cardata <- structure(as.integer(c(2560, 2345, 1845, 2260, 2440,
        2285, 2275, 2350, 2295, 1900, 2390, 2075, 2330, 3320, 2885,
        3310, 2695, 2170, 2710, 2775, 2840, 2485, 2670, 2640, 2655,
        3065, 2750, 2920, 2780, 2745, 3110, 2920, 2645, 2575, 2935,
        2920, 2985, 3265, 2880, 2975, 3450, 3145, 3190, 3610, 2885,
        3480, 3200, 2765, 3220, 3480, 3325, 3855, 3850, 3195, 3735,
        3665, 3735, 3415, 3185, 3690, 97, 114, 81, 91, 113, 97, 97,
        98, 109, 73, 97, 89, 109, 305, 153, 302, 133, 97, 125, 146,
        107, 109, 121, 151, 133, 181, 141, 132, 133, 122, 181, 146,
        151, 116, 135, 122, 141, 163, 151, 153, 202, 180, 182, 232,
        143, 180, 180, 151, 189, 180, 231, 305, 302, 151, 202, 182,
        181, 143, 146, 146)), .Dim = as.integer(c(60, 2)), 
        .Dimnames = list(NULL, c("Weight", "Disp.")))
       bagplot(cardata,factor=3,show.baghull=TRUE,
         show.loophull=TRUE,precision=1,dkmethod=2)
       title("car data Chambers/Hastie 1992")
       # points of y=x*x
       bagplot(x=1:30,y=(1:30)^2,verbose=FALSE,dkmethod=2)
       # one dimensional subspace
       bagplot(x=1:100,y=1:100)

