sureshrink.mse: SURE estimate of risk

In asus: Adaptive SURE Thresholding Using Side Information

SURE estimate of risk

Description

Stein's Unbiased Risk Estimate for the sureshrink estimator

Usage

sureshrink.mse(d, v.d, type = 1, t = 0)

Arguments

d	an n vector of observations
v.d	an n vector of variances for each component of d
type	set type=1 if you want the thresholding parameter t to be estimated. Otherwise set type = 0 in which case you must provide t. Default is type = 1
t	soft thresholding parameter. If type = 1, then t is estimated whereas if type = 0 then you must provide t. Default is t = 0 (and type = 1)

Details

Estimates the risk of the surehsrink estimator of Donoho and Johnstone (1995).

Value

1. sure.est - SURE estimate of risk

2. t - estimated threshold (meaningless if type = 0)

References

1. Charles M Stein. Estimation of the mean of a multivariate normal distribution. The annals of Statistics, pages 1135-1151, 1981

2. David L Donoho and Iain M Johnstone. Adapting to unknown smoothness via wavelet shrinkage. Journal of the american statistical association, 90(432):1200-1224, 1995

See Also

sureshrink,asus

Examples

library(asus)
set.seed(42)
d<-rnorm(10,2,1)
v.d<- rep(1,10)
mse<-sureshrink.mse(d,v.d)

asus documentation built on Aug. 24, 2023, 5:10 p.m.