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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

Install

install.packages('natural')

Monthly Downloads

122

Version

0.9.0

License

GPL-3

Maintainer

Guo Yu

Last Published

January 16th, 2018

Functions in natural (0.9.0)

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