Produces a normal QQ plot with a line of equality and a confidence band (by default) of the input data. This is basically a prettier version of qqnorm from the stats package.
QQnorm(xdata, col = c(4, 6), ylab = "Sample Quantiles", xlab = "Theoretical Quantiles",
main = "Normal Q-Q Plot", ylim = NULL, ci = TRUE, qqlwd = 1, ...)
the data. If a matrix, the data are collapsed.
vector of 2, first is point color, second is line color (default is blue-4 and magenta-6).
y-axis label (default is 'Sample Quantiles').
x-axis label (default is 'Theoretical Quantiles').
plot title (default is 'Normal Q-Q Plot')
limits on y-axis (default is the most beautiful limits ever).
if TRUE (default) draws pointwise 99.99% CIs as a band.
If FALSE or 0, no CI is drawn. Alternately, enter a percentage
(e.g., either ci=95 or ci=.95 will work).
line width of the qqline (default is 1).
other graphical parameters sent to tsplot.
D.S. Stoffer
If you want a graphic to check normality of your data in xdata, just enter QQnorm(xdata) and sit back and enjoy the beauty of this script (you may want to wear sunglasses).
For confidence levels, various values are allowed. For example, 95% limits can be obtained as ci=95 or ci=.95, both of which are conventional. However, ci=5, or ci=.05 will also work for 95% intervals (so you can not go below 50%). If you ask for a confidence level of 100% or larger, you will get the default without a warning and maybe you are unconventional.
You can find demonstrations of astsa capabilities at FUN WITH ASTSA.
The most recent version of the package can be found at https://github.com/nickpoison/astsa/.
In addition, the News and ChangeLog files are at https://github.com/nickpoison/astsa/blob/master/NEWS.md.
The webpages for the texts and some help on using R for time series analysis can be found at https://nickpoison.github.io/.