dpakes | R Documentation |
Probability density, cumulative distribution function, quantile function, and random generation for the Pakes distribution.
dpakes(x, zeta)
ppakes(q, zeta)
qpakes(p, zeta)
rpakes(n, zeta)
x , q |
Numeric vector of quantiles. |
p |
Numeric vector of probabilities |
n |
Number of observations. |
zeta |
Mean of distribution. A single, non-negative, numeric value. |
These functions concern the probability distribution of the random variable
X = \sum_{n=1}^\infty \prod_{j=1}^n U_j^{1/\zeta}
where U_1, U_2, \ldots
are independent
random variables uniformly distributed on [0,1]
and \zeta
is a parameter.
This distribution arises in many contexts. For example,
for a homogeneous Poisson point process in two-dimensional space
with intensity \lambda
,
the standard Gaussian kernel estimator of intensity
with bandwidth \sigma
, evaluated at any fixed location u
,
has the same distribution as (\lambda/\zeta) X
where
\zeta = 2 \pi \lambda\sigma^2
.
Following the usual convention,
dpakes
computes the probability density,
ppakes
the cumulative distribution function,
and qpakes
the quantile function,
and rpakes
generates random variates with this distribution.
The computation is based on a recursive integral equation for the cumulative distribution function, due to Professor Tony Pakes, presented in Baddeley, Moller and Pakes (2008). The solution uses the fact that the random variable satisfies the distributional equivalence
X \equiv U^{1/\zeta} (1 + X)
where U
is uniformly distributed on [0,1]
and independent
of X
.
A numeric vector.
Adrian Baddeley.
Baddeley, A., Moller, J. and Pakes, A.G. (2008) Properties of residuals for spatial point processes, Annals of the Institute of Statistical Mathematics 60, 627–649.
curve(dpakes(x, 1.5), to=4)
rpakes(3, 1.5)
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