Parents (Total: 4)

The searched file hash is included in 4 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
MD5	913CA99019D6C21897051A4F8991C327
PackageArch	x86_64
PackageDescription	Extremely efficient procedures for fitting the entire lasso or elastic-net regularization path for linear regression, logistic and multinomial regression models, Poisson regression and the Cox model. Two recent additions are the multiple-response Gaussian, and the grouped multinomial regression. The algorithm uses cyclical coordinate descent in a path-wise fashion.
PackageName	R-glmnet
PackageRelease	lp151.1.41
PackageVersion	2.0.18
SHA-1	56CD6BD10D0F9CB45C1D6C37F4D3D233E46EF875
SHA-256	C86A01688E6B2C7BB06E70980844BAD85E86EC8675BD45CC17CA7BF469198627

Key	Value
MD5	71E6911695FE5CD358381FE1837DD04E
PackageArch	x86_64
PackageDescription	Extremely efficient procedures for fitting the entire lasso or elastic-net regularization path for linear regression, logistic and multinomial regression models, Poisson regression and the Cox model. Two recent additions are the multiple-response Gaussian, and the grouped multinomial regression. The algorithm uses cyclical coordinate descent in a path-wise fashion.
PackageName	R-glmnet
PackageRelease	lp152.1.10
PackageVersion	2.0.18
SHA-1	014993F2B65FB9B93346002AE76A54F4289322BA
SHA-256	FDA5D5E397F62BD30A61E00467B821104DA0F78AC0D3697A41307B7F56B04BED

Key	Value
MD5	90F06A6E3B8B9372FB58602D8572B029
PackageArch	x86_64
PackageDescription	Extremely efficient procedures for fitting the entire lasso or elastic-net regularization path for linear regression, logistic and multinomial regression models, Poisson regression and the Cox model. Two recent additions are the multiple-response Gaussian, and the grouped multinomial regression. The algorithm uses cyclical coordinate descent in a path-wise fashion.
PackageName	R-glmnet
PackageRelease	lp150.1.26
PackageVersion	2.0.18
SHA-1	FF20AAA2DDA4E88A6A144191EFA122D866B6E842
SHA-256	464A4CE55769E5D0418F36F8E528A6A09978E02940FD1318F32197A21EAE9B3E

Key	Value
MD5	F771A4532EBC20E41886CE036F74B0FF
PackageArch	x86_64
PackageDescription	Extremely efficient procedures for fitting the entire lasso or elastic-net regularization path for linear regression, logistic and multinomial regression models, Poisson regression and the Cox model. Two recent additions are the multiple-response Gaussian, and the grouped multinomial regression. The algorithm uses cyclical coordinate descent in a path-wise fashion.
PackageName	R-glmnet
PackageRelease	lp153.1.9
PackageVersion	2.0.18
SHA-1	CD9AFF826B08965B25B59570F553D6D8E4A6E44D
SHA-256	AD2C1AFDD756D15842EB8465E8AFA2623B44A9988A69097A3E48A82AD690D235