Estimating the Error Variance in a High-Dimensional Linear Model


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Documentation for package ‘natural’ version 0.9.0

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natural-package natural: Natural and Organic lasso estimates of error variance in high-dimensional linear models
getLam_olasso Get the two (theoretical) values of lambdas used in the organic lasso
getLam_slasso Get the two (theoretical) values of lambdas used in scaled lasso
make_sparse_model Generate sparse linear model and random samples
natural natural: Natural and Organic lasso estimates of error variance in high-dimensional linear models
nlasso_cv Cross-validation for natural lasso
nlasso_path Fit a linear model with natural lasso
olasso Error standard deviation estimation using organic lasso
olasso_cv Cross-validation for organic lasso
olasso_path Fit a linear model with organic lasso
olasso_slow Solve organic lasso problem with a single value of lambda The lambda values are for slow rates, which could give less satisfying results
plot.natural.cv plot a natural.cv object
plot.natural.path plot a natural.path object
print.natural.path print a natural.path object
standardize Standardize the n -by- p design matrix X to have column means zero and ||X_j||_2^2 = n for all j