coplot                 package:base                 R Documentation

_C_o_n_d_i_t_i_o_n_i_n_g _P_l_o_t_s

_D_e_s_c_r_i_p_t_i_o_n:

     This function produces two variants of the conditioning plots
     discussed in the reference below.

_U_s_a_g_e:

     coplot(formula, data, given.values, panel = points, rows, columns,
            show.given = TRUE, col = par("fg"), pch = par("pch"), 
            bar.bg = c(num = gray(0.8), fac = gray(0.95)),
            xlab = c(x.name, paste("Given :", a.name)),
            ylab = c(y.name, paste("Given :", b.name)),
            subscripts = FALSE,
            axlabels = function(f) abbreviate(levels(f)),
            number = 6, overlap = 0.5, xlim, ylim, ...) 
     co.intervals(x, number = 6, overlap = 0.5)

_A_r_g_u_m_e_n_t_s:

 formula: a formula describing the form of conditioning plot.  A
          formula of the form `y ~ x | a' indicates that plots of `y'
          versus `x' should be produced conditional on the variable
          `a'.  A formula of the form `y ~ x| a * b' indicates that
          plots of `y' versus `x' should be produced conditional on the
          two variables `a' and `b'.

          All three or four variables may be either numeric or factors.
          When `x' or `y' are factors, the result is almost as if
          `as.numeric()' was applied, whereas for factor `a' or `b',
          the conditioning (and its graphics if `show.given' is true)
          are adapted. 

    data: a data frame containing values for any variables in the
          formula.  By default the environment where `coplot' was
          called from is used.

given.values: a value or list of two values which determine how the
          conditioning on `a' and `b' is to take place.

          When there is no `b' (i.e., conditioning only on `a'),
          usually this is a matrix with two columns each row of which
          gives an interval, to be conditioned on, but is can also be a
          single vector of numbers or a set of factor levels (if the
          variable being conditioned on is a factor). In this case (no
          `b'), the result of `co.intervals' can be used directly as
          `given.values' argument. 

   panel: a `function(x, y, col, pch, ...)' which gives the action to
          be carried out in each panel of the display.  The default is
          `points'.

    rows: the panels of the plot are laid out in a `rows' by `columns'
          array.  `rows' gives the number of rows in the array.

 columns: the number of columns in the panel layout array.

show.given: logical (possibly of length 2 for 2 conditioning
          variables): should conditioning plots be shown for the
          corresponding conditioning variables (default `TRUE')

     col: a vector of colors to be used to plot the points.  If too
          short, the values are recycled.

     pch: a vector of plotting symbols or characters.  If too short,
          the values are recycled.

  bar.bg: a named vector with components `"num"' and `"fac"' giving the
          background colors for the (shingle) bars, for numeric and
          factor conditioning variables respectively.

    xlab: character; labels to use for the x axis and the first
          conditioning variable.  If only one label is given, it is
          used for the x axis and the default label is used for the
          conditioning variable.

    ylab: character; labels to use for the y axis and any second
          conditioning variable.

subscripts: logical: if true the panel function is given an additional
          (third) argument `subscripts' giving the subscripts of the
          data passed to that panel.

axlabels: function for creating axis (tick) labels when x or y are
          factors.

  number: integer; the number of conditioning intervals, for a and b,
          possibly of length 2.  It is only used if the corresponding
          conditioning variable is not a `factor'.

 overlap: numeric < 1; the fraction of overlap of the conditioning
          variables, possibly of length 2 for x and y direction.  When
          overlap < 0, there will be gaps between the data slices.

    xlim: the range for the x axis.

    ylim: the range for the y axis.

     ...: additional arguments to the panel function.

       x: a numeric vector.

_D_e_t_a_i_l_s:

     In the case of a single conditioning variable `a', when both
     `rows' and `columns' are unspecified, a ``close to square'' layout
     is chosen with `columns >= rows'.

     In the case of multiple `rows', the order of the panel plots is
     from the bottom and from the left (corresponding to increasing
     `a', typically).

_V_a_l_u_e:

     `co.intervals(., number, .)' returns a (`number' x 2) `matrix',
     say `ci',  where `ci[k,]' is the `range' of `x' values for the
     `k'-th interval.

_R_e_f_e_r_e_n_c_e_s:

     Cleveland, W. S. (1993) Visualizing Data. New Jersey: Summit
     Press.

_S_e_e _A_l_s_o:

     `pairs', `panel.smooth', `points'.

_E_x_a_m_p_l_e_s:

     ## Tonga Trench Earthquakes
     data(quakes)
     coplot(lat ~ long | depth, data = quakes)
     given.depth <- co.intervals(quakes$depth, number=4, overlap=.1)
     coplot(lat ~ long | depth, data = quakes, given.v=given.depth, rows=1)

     ## Conditioning on 2 variables:
     ll.dm <- lat ~ long | depth * mag
     coplot(ll.dm, data = quakes)
     coplot(ll.dm, data = quakes, number=c(4,7), show.given=c(TRUE,FALSE))
     coplot(ll.dm, data = quakes, number=c(3,7),
            overlap=c(-.5,.1)) # negative overlap DROPS values

     data(warpbreaks)
     ## given two factors
     coplot(breaks ~ 1:54 | wool * tension, data = warpbreaks, show.given = 0:1)
     coplot(breaks ~ 1:54 | wool * tension, data = warpbreaks,
            col = "red", bg = "pink", pch = 21,
            bar.bg = c(fac = "light blue"))

     ## Example with empty panels:
     data(state)
     attach(data.frame(state.x77))#> don't need `data' arg. below
     coplot(Life.Exp ~ Income | Illiteracy * state.region, number = 3,
            panel = function(x, y, ...) panel.smooth(x, y, span = .8, ...))
     ## y ~ factor -- not really sensical, but `show off':
     coplot(Life.Exp ~ state.region | Income * state.division,
            panel = panel.smooth)
     detach() # data.frame(state.x77)

