qev {evgam} | R Documentation |
Quantile estimation of a composite extreme value distribution
Description
Quantile estimation of a composite extreme value distribution
Usage
qev(
p,
loc,
scale,
shape,
m = 1,
alpha = 1,
theta = 1,
family,
tau = 0,
start = NULL
)
Arguments
p |
a scalar giving the quantile of the distribution sought |
loc |
a scalar, vector or matrix giving the location parameter |
scale |
as above, but scale parameter |
shape |
as above, but shape parameter |
m |
a scalar giving the number of values per return period unit, e.g. 365 for daily data giving annual return levels |
alpha |
a scalar, vector or matrix of weights if within-block variables not identically distributed and of different frequencies |
theta |
a scalar, vector or matrix of extremal index values |
family |
a character string giving the family for which return levels sought |
tau |
a scalar, vector or matrix of values giving the threshold quantile for the GPD (i.e. 1 - probability of exceedance) |
start |
a 2-vector giving starting values that bound the return level |
Details
If F
is the generalised extreme value or generalised Pareto
distribution, qev
solves
\prod_{j=1}^n \big\{F(z)\}^{m \alpha_j \theta_j} = p.
For both distributions, location, scale and shape parameters
are given by loc
, scale
and shape
. The
generalised Pareto distribution, for \xi \neq 0
and z > u
,
is parameterised as 1 - (1 - \tau) [1 + \xi (z - u) / \psi_u]^{-1/\xi}
,
where u
, \psi_u
and \xi
are its location, scale and shape
parameters, respectively, and \tau
corresponds to argument tau
.
Value
A scalar or vector of estimates of p
Examples
qev(0.9, c(1, 2), c(1, 1.1), .1, family="gev")
qev(0.99, c(1, 2), c(1, 1.1), .1, family="gpd", tau=0.9)