| qqt {limma} | R Documentation |
Plots the quantiles of a data sample against the theoretical quantiles of a Student's t distribution.
qqt(y, df = Inf, ylim = range(y), main = "Student's t Q-Q Plot",
xlab = "Theoretical Quantiles", ylab = "Sample Quantiles", plot.it = TRUE, ...)
qqf(y, df1, df2, ylim=range(y), main= "F Distribution Q-Q Plot",
xlab = "Theoretical Quantiles", ylab = "Sample Quantiles", plot.it = TRUE, ...)
y |
a numeric vector or array containing the data sample |
df |
degrees of freedom for the t-distribution. The default |
df1 |
numerator degrees of freedom for the F-distribution. |
df2 |
denominator degrees of freedom for the F-distribution. |
ylim |
plotting range for |
main |
main title for the plot |
xlab |
x-axis title for the plot |
ylab |
y-axis title for the plot |
plot.it |
whether or not to produce a plot |
... |
other arguments to be passed to |
This function is analogous to qqnorm for normal probability plots.
In fact qqt(y,df=Inf) is identical to qqnorm(y) in all respects except the default title on the plot.
A list is invisibly returned containing the values plotted in the QQ-plot:
x |
theoretical quantiles of the t-distribution or F-distribution |
y |
the data sample, same as input |
Gordon Smyth
# See also the lmFit examples y <- rt(50,df=4) qqt(y,df=4) abline(0,1)