GPD_quantiles: Compute extreme quantile from GPD parameters
In EQRN: Extreme Quantile Regression Neural Networks for Risk Forecasting
GPD_quantiles R Documentation
Compute extreme quantile from GPD parameters
Description
Compute extreme quantile from GPD parameters
Usage
GPD_quantiles(p, p0, t_x0, sigma, xi)
Arguments
p
Probability level of the desired extreme quantile.
p0
Probability level of the (possibly varying) intermediate threshold/quantile.
t_x0
Value(s) of the (possibly varying) intermediate threshold/quantile.
sigma
Value(s) for the GPD scale parameter.
xi
Value(s) for the GPD shape parameter.
Value
The quantile value at probability level p.
EQRN documentation built on April 4, 2025, 12:45 a.m.
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| GPD_quantiles | R Documentation |
Compute extreme quantile from GPD parameters
Description
Compute extreme quantile from GPD parameters
Usage
GPD_quantiles(p, p0, t_x0, sigma, xi)
Arguments
p |
Probability level of the desired extreme quantile. |
p0 |
Probability level of the (possibly varying) intermediate threshold/quantile. |
t_x0 |
Value(s) of the (possibly varying) intermediate threshold/quantile. |
sigma |
Value(s) for the GPD scale parameter. |
xi |
Value(s) for the GPD shape parameter. |
Value
The quantile value at probability level p.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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