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qqt

Student's t or Fisher's F Quantile-Quantile Plot


Description

Plots the quantiles of a data sample against the theoretical quantiles of a Student's t distribution.

Usage

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, ...)

Arguments

y

a numeric vector or array containing the data sample

df

degrees of freedom for the t-distribution. The default df=Inf represents the normal distribution.

df1

numerator degrees of freedom for the F-distribution.

df2

denominator degrees of freedom for the F-distribution.

ylim

plotting range for y

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 plot

Details

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.

Value

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 y

Author(s)

Gordon Smyth

See Also

Examples

#  See also the lmFit examples

y <- rt(50,df=4)
qqt(y,df=4)
abline(0,1)

limma

Linear Models for Microarray Data

v3.46.0
GPL (>=2)
Authors
Gordon Smyth [cre,aut], Yifang Hu [ctb], Matthew Ritchie [ctb], Jeremy Silver [ctb], James Wettenhall [ctb], Davis McCarthy [ctb], Di Wu [ctb], Wei Shi [ctb], Belinda Phipson [ctb], Aaron Lun [ctb], Natalie Thorne [ctb], Alicia Oshlack [ctb], Carolyn de Graaf [ctb], Yunshun Chen [ctb], Mette Langaas [ctb], Egil Ferkingstad [ctb], Marcus Davy [ctb], Francois Pepin [ctb], Dongseok Choi [ctb]
Initial release
2020-10-19

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