sr_shape: sr_shape
In micss: Modified Iterative Cumulative Sum of Squares Algorithm
sr_shape R Documentation
sr_shape
Description
Computes the scale parameter for the GEV approximation
to the distribution of kappa_test statistic
Usage
sr_shape(t, alpha, lmax = NULL)
Arguments
t
Sample size
alpha
Value of the tail index between 2 and 4
lmax
Maximum lag to be used for the long-run estimation of the fourth order moment of the
innovations. If not specified it is generated automatically depending on the sample size.
Details
Used internally by cv.kappa and p.val.kappa
Value
Shape parameter
References
J.L. Carrion-i-Silvestre & A. Sansó (2026): Testing for Constant Unconditional Variance in Heavy-Tailed Time Series. Communications in Statistics - Simulation and Computation. doi:10.1080/03610918.2026.2615207
micss documentation built on March 17, 2026, 5:06 p.m.
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| sr_shape | R Documentation |
sr_shape
Description
Computes the scale parameter for the GEV approximation to the distribution of kappa_test statistic
Usage
sr_shape(t, alpha, lmax = NULL)
Arguments
t |
Sample size |
alpha |
Value of the tail index between 2 and 4 |
lmax |
Maximum lag to be used for the long-run estimation of the fourth order moment of the innovations. If not specified it is generated automatically depending on the sample size. |
Details
Used internally by cv.kappa and p.val.kappa
Value
Shape parameter
References
J.L. Carrion-i-Silvestre & A. Sansó (2026): Testing for Constant Unconditional Variance in Heavy-Tailed Time Series. Communications in Statistics - Simulation and Computation. doi:10.1080/03610918.2026.2615207
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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