Description Usage Arguments Value Examples
The function implements algorithmic leveraging or linear regression using leverage score and uniform-based row subsampling. It replicates the simulation setting of Fig 1 in Ma et Al's in https://onlinelibrary.wiley.com/doi/full/10.1002/wics.1324.
1 | algo_leverage(y, X, r = 0.1, sample_size = r, method = "leverage")
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y |
The response vector with n entries |
X |
The covariates n by p matrix |
r |
Percentage of subsamples to be drwan; default set to 0.1 |
sample_size |
Number of subsamples to consider for regression |
method |
The type of subsampling: 'unif' for uniform-based, 'leverage' for leverage-score based |
The coefficient vector beta
1 | algo_leverage(rnorm(500), matrix(rnorm(1000),nrow=500), method='unif')
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