spline.corr: Spline correction for Fraser-Reid approximations
In mev: Modelling of Extreme Values
spline.corr R Documentation
Spline correction for Fraser-Reid approximations
Description
The tangent exponential model can be numerically unstable for values close to r = 0.
This function corrects these incorrect values, which are interpolated using splines.
The function takes as input an object of class fr and returns the same object with
different rstar values.
Usage
spline.corr(fr, method = c("cobs", "smooth.spline"))
Arguments
fr
an object of class fr, normally the output of gpd.tem or gev.tem.
method
string for the method, either cobs (constrained robust B-spline from eponym package) or smooth.spline
Details
If available, the function uses cobs from the eponym package. The latter handles constraints and smoothness penalties, and is more robust than the equivalent smooth.spline.
Value
an object of class fr, containing as additional arguments spline and a modified rstar argument.
Warning
While penalized (robust) splines often do a good job at capturing and correcting for numerical outliers and NA, it
may also be driven by unusual values lying on the profile log-likelihood the curve or fail to detect outliers (or falsely identifying ‘correct’ values as outliers). The user should always validate by comparing the plots of both the uncorrected (raw) output of the object with that of spline.corr.
mev documentation built on Sept. 11, 2024, 8:14 p.m.
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| spline.corr | R Documentation |
Spline correction for Fraser-Reid approximations
Description
The tangent exponential model can be numerically unstable for values close to r = 0.
This function corrects these incorrect values, which are interpolated using splines.
The function takes as input an object of class fr and returns the same object with
different rstar values.
Usage
spline.corr(fr, method = c("cobs", "smooth.spline"))
Arguments
fr |
an object of class |
method |
string for the method, either |
Details
If available, the function uses cobs from the eponym package. The latter handles constraints and smoothness penalties, and is more robust than the equivalent smooth.spline.
Value
an object of class fr, containing as additional arguments spline and a modified rstar argument.
Warning
While penalized (robust) splines often do a good job at capturing and correcting for numerical outliers and NA, it
may also be driven by unusual values lying on the profile log-likelihood the curve or fail to detect outliers (or falsely identifying ‘correct’ values as outliers). The user should always validate by comparing the plots of both the uncorrected (raw) output of the object with that of spline.corr.
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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