gp_pwm | R Documentation |
Uses the methodology of Hosking and Wallis (1987) to estimate the parameters of the generalised Pareto (GP) distribution.
gp_pwm(gp_data, u = 0)
gp_data |
A numeric vector of raw data, assumed to be a random sample from a probability distribution. |
u |
A numeric scalar. A threshold. The GP distribution is fitted to
the excesses of |
A list with components
est
: A numeric vector. PWM estimates of GP parameters
\sigma
(scale) and \xi
(shape).
se
: A numeric vector. Estimated standard errors of
\sigma
and \xi
.
cov
: A numeric matrix. Estimate covariance matrix of the
the PWM estimators of \sigma
and \xi
.
Hosking, J. R. M. and Wallis, J. R. (1987) Parameter and Quantile Estimation for the Generalized Pareto Distribution. Technometrics, 29(3), 339-349. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.2307/1269343")}.
gp
for details of the parameterisation of the GP
distribution.
u <- quantile(gom, probs = 0.65)
gp_pwm(gom, u)
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