abline(a = NULL, b = NULL, h = NULL, v = NULL, reg = NULL, coef = NULL, untf = FALSE, ...)
lwd(possibly as vectors: see
xpdand the line characteristics
acan be specified on its own and is taken to contain the slope and intercept in vector form).
v= forms draw horizontal and vertical lines
at the specified coordinates.
coef form specifies the line by a vector containing the
slope and intercept.
reg is a regression object with a
If this returns a vector of length 1 then the value is taken to be the
slope of a line through the origin, otherwise, the first 2 values are
taken to be the intercept and slope.
untf is true, and one or both axes are log-transformed, then
a curve is drawn corresponding to a line in original coordinates,
otherwise a line is drawn in the transformed coordinate system. The
v parameters always refer to original coordinates.
xpd argument for clipping overrides
par("xpd") setting used otherwise.
Murrell, P. (2005) R Graphics. Chapman & Hall/CRC Press.
segmentsfor connected and arbitrary lines given by their endpoints.
## Setup up coordinate system (with x == y aspect ratio): plot(c(-2,3), c(-1,5), type = "n", xlab = "x", ylab = "y", asp = 1) ## the x- and y-axis, and an integer grid abline(h = 0, v = 0, col = "gray60") text(1,0, "abline( h = 0 )", col = "gray60", adj = c(0, -.1)) abline(h = -1:5, v = -2:3, col = "lightgray", lty = 3) abline(a = 1, b = 2, col = 2) text(1,3, "abline( 1, 2 )", col = 2, adj = c(-.1, -.1)) ## Simple Regression Lines: require(stats) sale5 <- c(6, 4, 9, 7, 6, 12, 8, 10, 9, 13) plot(sale5) abline(lsfit(1:10, sale5)) abline(lsfit(1:10, sale5, intercept = FALSE), col = 4) # less fitting z <- lm(dist ~ speed, data = cars) plot(cars) abline(z) # equivalent to abline(reg = z) or abline(coef = coef(z)) ## trivial intercept model abline(mC <- lm(dist ~ 1, data = cars)) ## the same as abline(a = coef(mC), b = 0, col = "blue")