pAD
computes the cumulative distribution function,
and qAD
computes the quantile function,
of the null distribution of the Anderson-Darling test
statistic.
pAD(q, n = Inf, lower.tail = TRUE, fast=TRUE)
qAD(p, n = Inf, lower.tail = TRUE, fast=TRUE)
Numeric vector of quantiles (values for which the cumulative probability is required).
Numeric vector of probabilities.
Integer. Sample size for the Anderson-Darling test.
Logical. If TRUE
(the default),
probabilities are \(P(X \le q)\),
and otherwise they are \(P(X > q)\).
Logical value indicating whether to use a fast algorithm
or a slower, more accurate algorithm, in the case n=Inf
.
A numeric vector of the same length as p
or q
.
pAD
uses the algorithms and C code described
in Marsaglia and Marsaglia (2004).
qAD
uses uniroot
to find the
quantiles.
The argument fast
applies only when n=Inf
and determines whether the asymptotic distribution is approximated
using the faster algorithm adinf
(accurate to 4-5 places)
or the slower algorithm ADinf
(accurate to 11 places)
described in Marsaglia and Marsaglia (2004).
Anderson, T.W. and Darling, D.A. (1952) Asymptotic theory of certain 'goodness-of-fit' criteria based on stochastic processes. Annals of Mathematical Statistics 23, 193--212.
Anderson, T.W. and Darling, D.A. (1954) A test of goodness of fit. Journal of the American Statistical Association 49, 765--769.
Marsaglia, G. and Marsaglia, J. (2004) Evaluating the Anderson-Darling Distribution. Journal of Statistical Software 9 (2), 1--5. February 2004. 10.18637/jss.v009.i02
# NOT RUN {
pAD(1.1, n=5)
pAD(1.1)
pAD(1.1, fast=FALSE)
qAD(0.5, n=5)
qAD(0.5)
# }
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