lambda.global: Global Thresholding Value
In SeoncheolPark/SphereWaveu:
Description
Usage
Arguments
Value
References
See Also
Description
This function calculates global thresholding value for spherical wavelet estimator.
Usage
1
lambda.global(swd, policy, nthresh, value, Q)
Arguments
swd
an object of class ‘swd’
policy
threshold technique. At present the possible policies are
‘"universal"’, ‘"probability"’, ‘"fdr"’, ‘"Lorentz"’ and ‘"sure"’.
nthresh
the number of resolution levels to be thresholded in the decomposition
value
the user supplied threshold represented by quantile level of ‘"probability"’ policy.
Q
parameter for the false discovery rate of ‘"fdr"’ policy.
Value
lam
global thresholding value
References
Donoho, D.~L. and Johnstone, I.~M. (1994) Ideal spatial
adaptation by wavelet shrinkage. Biometrika, 81,
425–455.
Oh, H-S. (1999) Spherical wavelets and their statistical analysis with applications to meteorological data. Ph.D. Thesis,
Department of Statistics, Texas A\&M University, College Station.
Oh, H-S. and Li, T-H. (2004) Estimation of global temperature fields from scattered observations by
a spherical-wavelet-based spatially adaptive method. Journal of the Royal Statistical Society
Ser. B, 66, 221–238.
See Also
SeoncheolPark/SphereWaveu documentation built on May 29, 2019, 12:04 a.m.
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Description Usage Arguments Value References See Also
Description
This function calculates global thresholding value for spherical wavelet estimator.
Usage
1 | lambda.global(swd, policy, nthresh, value, Q)
|
Arguments
swd |
an object of class ‘swd’ |
policy |
threshold technique. At present the possible policies are ‘"universal"’, ‘"probability"’, ‘"fdr"’, ‘"Lorentz"’ and ‘"sure"’. |
nthresh |
the number of resolution levels to be thresholded in the decomposition |
value |
the user supplied threshold represented by quantile level of ‘"probability"’ policy. |
Q |
parameter for the false discovery rate of ‘"fdr"’ policy. |
Value
lam |
global thresholding value |
References
Donoho, D.~L. and Johnstone, I.~M. (1994) Ideal spatial adaptation by wavelet shrinkage. Biometrika, 81, 425–455.
Oh, H-S. (1999) Spherical wavelets and their statistical analysis with applications to meteorological data. Ph.D. Thesis, Department of Statistics, Texas A\&M University, College Station.
Oh, H-S. and Li, T-H. (2004) Estimation of global temperature fields from scattered observations by a spherical-wavelet-based spatially adaptive method. Journal of the Royal Statistical Society Ser. B, 66, 221–238.
See Also
R Package Documentation
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