estimateLambda: Estimate the tuning parameter of lasso regression
In shuxiaoc/outference: Valid Inference in Linear Regression Corrected for Outlier Removal
Description
Usage
Arguments
Value
Description
This function returns λ = E[||X^T ε||_∞] / n,
where ε ~ N(0, σ^2 I).
Usage
1
estimateLambda(X, sigma, nsim = 1000)
Arguments
X,
the design matrix.
sigma,
the noise level.
nsim,
the number of Monte Carlo simulations to run.
Value
This function returns the value of tuning parameter.
shuxiaoc/outference documentation built on July 8, 2019, 8:30 p.m.
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Description Usage Arguments Value
Description
This function returns λ = E[||X^T ε||_∞] / n, where ε ~ N(0, σ^2 I).
Usage
1 | estimateLambda(X, sigma, nsim = 1000)
|
Arguments
X, |
the design matrix. |
sigma, |
the noise level. |
nsim, |
the number of Monte Carlo simulations to run. |
Value
This function returns the value of tuning parameter.
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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