chart.QQPlot {PerformanceAnalytics}R Documentation

Plot a QQ chart


Plot the return data against any theoretical distribution.


chart.QQPlot(R, distribution = "norm", ylab = NULL, xlab = paste(distribution, "Quantiles"), main = NULL, las = par("las"), envelope = FALSE, labels = FALSE, col = c(1, 4), lwd = 2, pch = 1, cex = 1, line = c("quartiles", "robust", "none"), element.color = "darkgray", cex.axis = 0.8, cex.legend = 0.8, cex.lab = 1, cex.main = 1, ...)


R an xts, vector, matrix, data frame, timeSeries or zoo object of asset returns
distribution root name of comparison distribution - e.g., 'norm' for the normal distribution; 't' for the t-distribution. See examples for other ideas.
xlab set the x-axis label, as in plot
ylab set the y-axis label, as in plot
main set the chart title, same as in plot
las set the direction of axis labels, same as in plot
envelope confidence level for point-wise confidence envelope, or 'FALSE' for no envelope.
labels vector of point labels for interactive point identification, or 'FALSE' for no labels.
col color for points and lines; the default is the second entry in the current color palette (see 'palette' and 'par').
lwd set the line width, as in plot
pch symbols to use, see also plot
cex symbols to use, see also plot
line '"quartiles"' to pass a line through the quartile-pairs, or '"robust"' for a robust-regression line; the latter uses the 'rlm' function in the 'MASS' package. Specifying 'line = "none"' suppresses the line.
element.color provides the color for drawing chart elements, such as the box lines, axis lines, etc. Default is "darkgray"
cex.legend The magnification to be used for sizing the legend relative to the current setting of 'cex'
cex.axis The magnification to be used for axis annotation relative to the current setting of 'cex'
cex.lab The magnification to be used for x- and y-axis labels relative to the current setting of 'cex'
cex.main The magnification to be used for the main title relative to the current setting of 'cex'.
... any other passthru parameters to the distribution function


A Quantile-Quantile (QQ) plot is a scatter plot designed to compare the data to the theoretical distributions to visually determine if the observations are likely to have come from a known population. The empirical quantiles are plotted to the y-axis, and the x-axis contains the values of the theorical model. A 45-degree reference line is also plotted. If the empirical data come from the population with the choosen distribution, the points should fall approximately along this reference line. The larger the departure from the reference line, the greater the evidence that the data set have come from a population with a different distribution.


QQ Plot


John Fox, ported by Peter Carl


main code forked/borrowed/ported from the excellent:
Fox, John (2007) car: Companion to Applied Regression,

See Also



x = checkData(managers[,2, drop = FALSE], na.rm = TRUE, method = "vector")
# Panel 1, Normal distribution
chart.QQPlot(x, main = "Normal Distribution", distribution = 'norm', envelope=0.95)
# Panel 2, Log-Normal distribution
fit = fitdistr(1+x, 'lognormal')
chart.QQPlot(1+x, main = "Log-Normal Distribution", envelope=0.95, distribution='lnorm')#, meanlog = fit$estimate[[1]], sdlog = fit$estimate[[2]])
## Not run: 
# Panel 3, Skew-T distribution
fit = st.mle(y=x)
chart.QQPlot(x, main = "Skew T Distribution", envelope=0.95, distribution = 'st', location = fit$dp[[1]], scale = fit$dp[[2]], shape = fit$dp[[3]], df=fit$dp[[4]])
#Panel 4: Stable Parietian
fit.stable = stableFit(x,doplot=FALSE)
chart.QQPlot(x, main = "Stable Paretian Distribution", envelope=0.95, distribution = 'stable', alpha = fit.stable@fit$estimate[[1]], beta = fit.stable@fit$estimate[[2]], gamma = fit.stable@fit$estimate[[3]], delta = fit.stable@fit$estimate[[4]], pm = 0)
## End(Not run)

[Package PerformanceAnalytics version 0.9.9-5 Index]