Parents (Total: 11)

The searched file hash is included in 11 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
FileSize	1777292
MD5	D6DAF84F324F3265D49A2842E01A8A7B
PackageDescription	Lasso and Elastic-Net Regularized Generalized Linear Models 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. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the paper Introduction to Glmnet.
PackageMaintainer	Debian R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageName	r-cran-glmnet
PackageSection	gnu-r
PackageVersion	4.1-2
SHA-1	BDF70762F0EB0B6C297DBFECF273FB21C5FB1FD4
SHA-256	AA5B861CD50CEFC3BE62FFE585569BCB7D74C0C5A3AE1AFB62C966F7233DE1C6

Key	Value
FileSize	1771080
MD5	C660FC0A571F7EB1DCEE6E59A0DA8E84
PackageDescription	Lasso and Elastic-Net Regularized Generalized Linear Models 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. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the paper Introduction to Glmnet.
PackageMaintainer	Debian R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageName	r-cran-glmnet
PackageSection	gnu-r
PackageVersion	4.1-2
SHA-1	3789845F0DFF284065234D1A236D9697FC997A8E
SHA-256	871934825BA7C6033904FA8633E793B46AE5BD564A2922708DC1117A5854DAE1

Key	Value
FileSize	1785236
MD5	6B87943DC40F7CD31FD78A5EA535CEFC
PackageDescription	Lasso and Elastic-Net Regularized Generalized Linear Models 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. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the paper Introduction to Glmnet.
PackageMaintainer	Debian R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageName	r-cran-glmnet
PackageSection	gnu-r
PackageVersion	4.1-2
SHA-1	E6632E19957265A1A266A9E37C6EBECA6C1E6E6F
SHA-256	E68D2ACFB1F7AE2CC473521474D4282D731F9C1C5BB40D7519F4FCF0E380816B

Key	Value
FileSize	1782212
MD5	C05E459AD1EDED67CCD956813A503529
PackageDescription	Lasso and Elastic-Net Regularized Generalized Linear Models 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. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the paper Introduction to Glmnet.
PackageMaintainer	Debian R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageName	r-cran-glmnet
PackageSection	gnu-r
PackageVersion	4.1-2
SHA-1	E765A9A49734B2F8DD57DE91B7358214C6772B20
SHA-256	7996C19E83A43A818DD0D6489B12BC243D358F82D3AED92451B4392DC2E17B7D

Key	Value
FileSize	1782936
MD5	A95EC865448CF36EA5F2E44CCD3A6E70
PackageDescription	Lasso and Elastic-Net Regularized Generalized Linear Models 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. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the paper Introduction to Glmnet.
PackageMaintainer	Debian R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageName	r-cran-glmnet
PackageSection	gnu-r
PackageVersion	4.1-2
SHA-1	2D8FF03F8FD5D29923A1236B670B33AFD7C33DD5
SHA-256	96D94CC49D85CC4D8667B8920C0F071F60F8DAE9840A76F964D4F3B5A851E6B2

Key	Value
FileSize	1784572
MD5	865BE0E276B721CCAB6ECAE06D652A39
PackageDescription	Lasso and Elastic-Net Regularized Generalized Linear Models 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. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the paper Introduction to Glmnet.
PackageMaintainer	Debian R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageName	r-cran-glmnet
PackageSection	gnu-r
PackageVersion	4.1-2
SHA-1	2B9D5C7977E69C0375FBEBECC1A9D377E1048D47
SHA-256	827BE2B261B783CDF483E6B488512B1D3A9EDB35B73D592624E5C9EC94FF3547

Key	Value
FileSize	1779200
MD5	239F60C3B6C829FE165B8FFB6B76D2F2
PackageDescription	Lasso and Elastic-Net Regularized Generalized Linear Models 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. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the paper Introduction to Glmnet.
PackageMaintainer	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	r-cran-glmnet
PackageSection	gnu-r
PackageVersion	4.1-1
SHA-1	C4E4A3DFBDD55180E9E7A6AD3561EEDA1E4F8CB5
SHA-256	FB72B2435992B339AC8217D366B017E3976BE585DA0DB9D21C50BCED6D783060

Key	Value
FileSize	1776492
MD5	1B874660D62FA4AB1A06AF99CD72550F
PackageDescription	Lasso and Elastic-Net Regularized Generalized Linear Models 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. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the paper Introduction to Glmnet.
PackageMaintainer	Debian R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageName	r-cran-glmnet
PackageSection	gnu-r
PackageVersion	4.1-2
SHA-1	B411FC29B5881D8A275D1DBD16B58EA4C6BAAEC5
SHA-256	BB6B59CEC048CC42CB26D0E81AA32492F687D3ECDECAAE784BAF1E4ABAA39B16

Key	Value
FileSize	1790636
MD5	0FDDF512F1FA49E1C58B6B0642246758
PackageDescription	Lasso and Elastic-Net Regularized Generalized Linear Models 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. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the paper Introduction to Glmnet.
PackageMaintainer	Debian R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageName	r-cran-glmnet
PackageSection	gnu-r
PackageVersion	4.1-2
SHA-1	503CCC991AA0BDEAB2E66CCD239093B948761A71
SHA-256	32FB520FDDE1FE9B438CDD7539605714C13B84776763A3DCB2C3E48F64E85BD3

Key	Value
FileSize	1801916
MD5	3302DC2AF988BD50D171112B1BF7381A
PackageDescription	Lasso and Elastic-Net Regularized Generalized Linear Models 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. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the paper Introduction to Glmnet.
PackageMaintainer	Debian R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageName	r-cran-glmnet
PackageSection	gnu-r
PackageVersion	4.1-2
SHA-1	B89E84EB36581C861DEA21EE704122D8DDE1C17C
SHA-256	42C96BE12DA81C761D805F3E753B0711EB576AE7BA0C8133F1A89DC7229E789B

Key	Value
FileSize	1777680
MD5	D2D31253673425EF5760936999E9622E
PackageDescription	Lasso and Elastic-Net Regularized Generalized Linear Models 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. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the paper Introduction to Glmnet.
PackageMaintainer	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	r-cran-glmnet
PackageSection	gnu-r
PackageVersion	4.1-2
SHA-1	6E6D70092464B3D26A65561E29824ECEBF79DDF4
SHA-256	93204997EC5CCA41B1CA2485DF218F0961D61B561315B634965EE551EDB32F1C