qqthin                package:hddplot                R Documentation

_a _v_e_r_s_i_o_n _o_f _q_q_p_l_o_t() _t_h_a_t _t_h_i_n_s _o_u_t _p_o_i_n_t_s _t_h_a_t _o_v_e_r_p_l_o_t

_D_e_s_c_r_i_p_t_i_o_n:

     QQ-plots with large numbers of points typically generate graphics
     files that are unhelpfully large.  This function handles the
     problem by removing points that are, for all practical purposes,
     redundant

_U_s_a_g_e:

     qqthin(x, y, ends = c(0.01, 0.99), eps = 0.001, xlab = deparse(substitute(x)), adj.xlab = NULL, ylab = deparse(substitute(y)), show.line = TRUE, centerline = TRUE, ...)

_A_r_g_u_m_e_n_t_s:

       x: ordered values of 'x' will be plotted on the x-axis

       y: ordered values of 'y' will be plotted on the y-axis

    ends: outside these cumulative proportions of numbers of points, 
          all points will be included in the graph

     eps: controls the extent of overplotting

    xlab: label for x-axis

adj.xlab: positioning of x-label

    ylab: label for y-axis

show.line: logical; show the line y=x?

centerline: logical; draw a line though the part of the graph where
          some points have been omitted?

     ...: additional graphics parameters

_D_e_t_a_i_l_s:

_V_a_l_u_e:

     Gives a qqplot

_N_o_t_e:

_A_u_t_h_o_r(_s):

     John Maindonald

_R_e_f_e_r_e_n_c_e_s:

     ~put references to the literature/web site here ~

_S_e_e _A_l_s_o:

_E_x_a_m_p_l_e_s:

     mat <- matrix(rnorm(1000), ncol=20)
     cl <- factor(rep(1:3, c(7,9,4)))
     Fstats <- aovFbyrow(x = mat, cl = cl)
     qqthin(qf(ppoints(length(Fstats)), 2, 17), Fstats, eps=0.01)

     ## The function is currently defined as
     function(x, y, ends=c(.01,.99), eps=0.001, 
                xlab = deparse(substitute(x)), adj.xlab=NULL,
                ylab = deparse(substitute(y)), show.line=TRUE,
                centerline=TRUE, ...){
         ## qqthin() is a substitute for qqplot(), that thins
         ## out plotted points from the region where they are
         ## dense.  Apart from the overlaid curve that shows
         ## the region where points have been thinned, it may
         ## be hard to distinguish the result of qqthin()
         ## from that of qqplot()
         xlab <- xlab
         ylab <- ylab
         x <- sort(x)
         y <- sort(y)
         dx<-diff(x)
         epsdist <- sqrt(diff(range(x))^2+diff(range(y))^2)*eps
         dx<-0.5*(c(dx[1],dx)+c(dx,dx[length(dx)]))
         dy<-diff(y)
         dy<-0.5*(c(dy[1],dy)+c(dy,dy[length(dy)]))
         dpoints <- epsdist/sqrt(dx^2+dy^2)
         ## dpoints is a local measure of the number of points
         ## per unit distance along the diagonal, with the unit
         ## set to approximately eps*(length of diagonal)
         dig<-floor(dpoints)+1
         ## dig is, roughly, the number of points per unit distance.
         ## We wish to retain one point per unit distance.  For this
         ## retain points where cdig rounds to an integer. For such
         ## points, cdig has increased by approx 1, relative to the
         ## previous point that is retained.
         cdig<-round(cumsum(1/dig))
         subs<-match(unique(cdig), cdig)
         if(is.null(adj.xlab))
         plot(x[subs], y[subs], xlab=xlab, ylab=ylab)
         else {
           plot(x[subs], y[subs], xlab="", ylab=ylab)
           mtext(side=1, xlab, adj=adj.xlab, line=par()$mgp[1])
         }
         if(any(diff(subs)>1)){
         n1 <- min(subs[c(diff(subs),0)>1])
         n2 <- max(subs[c(0,diff(subs))>1])
         ns1 <- match(n1, subs)
         ns2 <- match(n2, subs)
         print(paste("Graph retains", length(subs), "points."))
         if(centerline)
           lines(smooth.spline(x[subs[ns1:ns2]], y[subs[ns1:ns2]]),
                 col="grey", lwd=2)
                 }
         if(show.line)abline(0, 1, col="red")
       }

