Scatter plot function — plot

Scatterplot with contours of the (kernel) estimated density

plot_twin(
  data,
  marginal.args = list(),
  kernsmooth.args = list(),
  xlab,
  ylab,
  col = "black",
  col2 = "lightblue",
  alpha = 0.3,
  grid = TRUE,
  side.plot = TRUE,
  ...
)

Arguments

data: bivariate data to plot (data.frame or matrix with 2 columns)
marginal.args: argumemts to marginal estimator (`density` continuous data, `barplot` for categorical )
kernsmooth.args: arguments to 2d-kernel smoother
xlab: x-axis label
ylab: y-axis label
col: color of points
col2: color of contour / density plot
alpha: transparency level of points
grid: should grid be added to the plot
side.plot: If TRUE subplots of the marginal distributions are added to the plot
...: arguments to lower level plot functions

Author

Klaus Kähler Holst

Examples

data("twinbmi", package="mets")
twinwide <- fast.reshape(twinbmi, id="tvparnr",varying=c("bmi"))
datamz <- log(subset(twinwide, zyg=="MZ")[,c("bmi1","bmi2")])

# continuous variables
plot_twin(datamz)


# categorical variables
datamz2 <- datamz
datamz2[, 1] <- cut(datamz[, 1], 4)
datamz2[, 2] <- cut(datamz[, 2], 4)
plot_twin(datamz2, color = TRUE)


# survival variables
cens1 <- rbinom(nrow(datamz), 1, 0.5)
cens2 <- rbinom(nrow(datamz), 1, 0.5)
datamz2[, 1] <- Event(datamz[, 1], cens1)
datamz2[, 2] <- suppressWarnings(Event(datamz[, 2], cens2))
plot_twin(datamz2)


rm(datamz, datamz2, cens1, cens2)