qq
is a generic function used to show quantile-quantile plot.
The function invokes particular methods
which depend on the class
of the first argument.
So the function makes a quantile quantile plot for univariate POT models.
qq(fitted, …)# S3 method for uvpot
qq(fitted, main, xlab, ylab, ci = TRUE, …)
A fitted object. When using the POT package, an object
of class 'uvpot'
. Most often, the
return of the fitgpd
function.
The title of the graphic. If missing, the title is set to
"QQ-plot"
.
The labels for the x and y axis. If missing, they are
set to "Model"
and "Empirical"
respectively.
Logical. If TRUE
(the default), 95% intervals are
plotted.
Other arguments to be passed to the plot
function.
A graphical window.
The quantile quantile plot consists of plotting the observed quantiles in function of the theoretical ones. The theoretical quantiles \(Q_{Theo, j}\) are computed from the fitted GPD, that is:
$$Q_{Theo, j} = F^{-1}(p_j)$$ where \(F^{-1}\) is the fitted quantile function and \(p_j\) are empirical probabilities defined by :
$$p_{j:n} = \frac{j - 0.35}{n}$$ where \(n\) is the total number of observations - see Hosking (1995).
If the theoretical model is correct, then points should be ``near'' the line \(y=x\).
Hosking, J. R. M. and Wallis, J. R. (1995). A comparison of unbiased and plotting-position estimators of L moments. Water Resources Research. 31(8): 2019--2025.
# NOT RUN {
x <- rgpd(75, 1, 2, 0.1)
pwmu <- fitgpd(x, 1, "pwmu")
qq(pwmu)
# }
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