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natural (version 0.9.0)
Estimating the Error Variance in a High-Dimensional Linear Model
Description
Implementation of the two error variance estimation methods in high-dimensional linear models of Yu, Bien (2017)
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Version
Version
0.9.0
Install
install.packages('natural')
Monthly Downloads
106
Version
0.9.0
License
GPL-3
Maintainer
Guo Yu
Last Published
January 16th, 2018
Functions in natural (0.9.0)
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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
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
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
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
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
plot.natural.cv
plot a natural.cv object
plot.natural.path
plot a natural.path object