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	89024
MD5	BD1DB8F6A5E5FDCE14B05F2449A02128
PackageDescription	GNU R package for bias reduction in binomial-response GLMs Fit generalized linear models with binomial responses using either an adjusted-score approach to bias reduction or maximum penalized likelihood where penalization is by Jeffreys invariant prior. These procedures return estimates with improved frequentist properties (bias, mean squared error) that are always finite even in cases where the maximum likelihood estimates are infinite (data separation). Fitting takes place by fitting generalized linear models on iteratively updated pseudo-data. The interface is essentially the same as 'glm'. More flexibility is provided by the fact that custom pseudo-data representations can be specified and used for model fitting. Functions are provided for the construction of confidence intervals for the reduced-bias estimates.
PackageMaintainer	Debian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
PackageName	r-cran-brglm
PackageSection	gnu-r
PackageVersion	0.5-9-1
SHA-1	55192F9A78060F356DB23169E17A2C7C1D98A56B
SHA-256	B86D8906BD80EA6A0BEAE0FE912AA0A8673FE2E9C5EC71742DD025ED34AA14B0

Key	Value
FileSize	89288
MD5	B1D1313BB69FEB5A80A1137A4E0E00A9
PackageDescription	GNU R package for bias reduction in binomial-response GLMs Fit generalized linear models with binomial responses using either an adjusted-score approach to bias reduction or maximum penalized likelihood where penalization is by Jeffreys invariant prior. These procedures return estimates with improved frequentist properties (bias, mean squared error) that are always finite even in cases where the maximum likelihood estimates are infinite (data separation). Fitting takes place by fitting generalized linear models on iteratively updated pseudo-data. The interface is essentially the same as 'glm'. More flexibility is provided by the fact that custom pseudo-data representations can be specified and used for model fitting. Functions are provided for the construction of confidence intervals for the reduced-bias estimates.
PackageMaintainer	Debian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
PackageName	r-cran-brglm
PackageSection	gnu-r
PackageVersion	0.5-9-1
SHA-1	CA2EFFB1F6EC5FB668AAF7F91B188ADA2F875921
SHA-256	D3201D3890994CA0C7E4E14947109B2E7F984FCA0DBF661332AE16EA881816D7

Key	Value
FileSize	89426
MD5	78B8C7EB69C27166C68BEC4BFF654EA2
PackageDescription	GNU R package for bias reduction in binomial-response GLMs Fit generalized linear models with binomial responses using either an adjusted-score approach to bias reduction or maximum penalized likelihood where penalization is by Jeffreys invariant prior. These procedures return estimates with improved frequentist properties (bias, mean squared error) that are always finite even in cases where the maximum likelihood estimates are infinite (data separation). Fitting takes place by fitting generalized linear models on iteratively updated pseudo-data. The interface is essentially the same as 'glm'. More flexibility is provided by the fact that custom pseudo-data representations can be specified and used for model fitting. Functions are provided for the construction of confidence intervals for the reduced-bias estimates.
PackageMaintainer	Debian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
PackageName	r-cran-brglm
PackageSection	gnu-r
PackageVersion	0.5-9-1
SHA-1	388A33BD297FCFCFFFE2A934179A9BF4A733754D
SHA-256	48E0802D8E2B3F7CBDA02C695799D3A4424F3F6ECD7BC40837AB67C8FCCECA59

Key	Value
FileSize	89458
MD5	77E4004EC493129DAE26035476045254
PackageDescription	GNU R package for bias reduction in binomial-response GLMs Fit generalized linear models with binomial responses using either an adjusted-score approach to bias reduction or maximum penalized likelihood where penalization is by Jeffreys invariant prior. These procedures return estimates with improved frequentist properties (bias, mean squared error) that are always finite even in cases where the maximum likelihood estimates are infinite (data separation). Fitting takes place by fitting generalized linear models on iteratively updated pseudo-data. The interface is essentially the same as 'glm'. More flexibility is provided by the fact that custom pseudo-data representations can be specified and used for model fitting. Functions are provided for the construction of confidence intervals for the reduced-bias estimates.
PackageMaintainer	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	r-cran-brglm
PackageSection	gnu-r
PackageVersion	0.5-9-1
SHA-1	FF36C2942DB1C3F4A69FB4929ABFE8A033CF927D
SHA-256	9031D9D029149F09E4BF81187FE527C362812FBCB8B13090719CB630F3BE6C8C

Key	Value
FileSize	89122
MD5	07560355A888C368361AB0D151799F5D
PackageDescription	GNU R package for bias reduction in binomial-response GLMs Fit generalized linear models with binomial responses using either an adjusted-score approach to bias reduction or maximum penalized likelihood where penalization is by Jeffreys invariant prior. These procedures return estimates with improved frequentist properties (bias, mean squared error) that are always finite even in cases where the maximum likelihood estimates are infinite (data separation). Fitting takes place by fitting generalized linear models on iteratively updated pseudo-data. The interface is essentially the same as 'glm'. More flexibility is provided by the fact that custom pseudo-data representations can be specified and used for model fitting. Functions are provided for the construction of confidence intervals for the reduced-bias estimates.
PackageMaintainer	Debian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
PackageName	r-cran-brglm
PackageSection	gnu-r
PackageVersion	0.5-9-1
SHA-1	00770E752F8C5FB157A88D154E3469783D8C9C5C
SHA-256	56FCBE23F2249C0BA6AF4DD02119EA3C73E640201AAFDFE93E917A7F6DEA96C8

Key	Value
FileSize	90598
MD5	C49BF7326A78CDF084B01831FB83A593
PackageDescription	GNU R package for bias reduction in binomial-response GLMs Fit generalized linear models with binomial responses using either an adjusted-score approach to bias reduction or maximum penalized likelihood where penalization is by Jeffreys invariant prior. These procedures return estimates with improved frequentist properties (bias, mean squared error) that are always finite even in cases where the maximum likelihood estimates are infinite (data separation). Fitting takes place by fitting generalized linear models on iteratively updated pseudo-data. The interface is essentially the same as 'glm'. More flexibility is provided by the fact that custom pseudo-data representations can be specified and used for model fitting. Functions are provided for the construction of confidence intervals for the reduced-bias estimates.
PackageMaintainer	Debian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
PackageName	r-cran-brglm
PackageSection	gnu-r
PackageVersion	0.5-9-1
SHA-1	65CDD9343BDF173EC49857B43CA2982DE72F66A1
SHA-256	01BD2A9AD5765B10B9CAC5D62039D93AA6CBE4A191F2EE8798AE4351B4BDC631

Key	Value
FileSize	89156
MD5	EB1A7E78490E2B354C8ACEBC1105A25E
PackageDescription	GNU R package for bias reduction in binomial-response GLMs Fit generalized linear models with binomial responses using either an adjusted-score approach to bias reduction or maximum penalized likelihood where penalization is by Jeffreys invariant prior. These procedures return estimates with improved frequentist properties (bias, mean squared error) that are always finite even in cases where the maximum likelihood estimates are infinite (data separation). Fitting takes place by fitting generalized linear models on iteratively updated pseudo-data. The interface is essentially the same as 'glm'. More flexibility is provided by the fact that custom pseudo-data representations can be specified and used for model fitting. Functions are provided for the construction of confidence intervals for the reduced-bias estimates.
PackageMaintainer	Debian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
PackageName	r-cran-brglm
PackageSection	gnu-r
PackageVersion	0.5-9-1
SHA-1	AC3E78CB912A5CA38FCC94979013486F2DE11538
SHA-256	4752D9CD9A38D6EA2B41E2532303B91058437DD2B8DC2847D321D431B28059E8

Key	Value
FileSize	89254
MD5	8A9014CBE27D6AB2CEF6587DD36FDC18
PackageDescription	GNU R package for bias reduction in binomial-response GLMs Fit generalized linear models with binomial responses using either an adjusted-score approach to bias reduction or maximum penalized likelihood where penalization is by Jeffreys invariant prior. These procedures return estimates with improved frequentist properties (bias, mean squared error) that are always finite even in cases where the maximum likelihood estimates are infinite (data separation). Fitting takes place by fitting generalized linear models on iteratively updated pseudo-data. The interface is essentially the same as 'glm'. More flexibility is provided by the fact that custom pseudo-data representations can be specified and used for model fitting. Functions are provided for the construction of confidence intervals for the reduced-bias estimates.
PackageMaintainer	Debian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
PackageName	r-cran-brglm
PackageSection	gnu-r
PackageVersion	0.5-9-1
SHA-1	02EB0194C9224AB83725A17C4622369881F403BA
SHA-256	D472F5F0D7A348AD0EB160291D6A3F8BCD202DA637FDEA86765C613331238027

Key	Value
FileSize	89264
MD5	C687EFE51317BE1C4CEEBEF64E299A22
PackageDescription	GNU R package for bias reduction in binomial-response GLMs Fit generalized linear models with binomial responses using either an adjusted-score approach to bias reduction or maximum penalized likelihood where penalization is by Jeffreys invariant prior. These procedures return estimates with improved frequentist properties (bias, mean squared error) that are always finite even in cases where the maximum likelihood estimates are infinite (data separation). Fitting takes place by fitting generalized linear models on iteratively updated pseudo-data. The interface is essentially the same as 'glm'. More flexibility is provided by the fact that custom pseudo-data representations can be specified and used for model fitting. Functions are provided for the construction of confidence intervals for the reduced-bias estimates.
PackageMaintainer	Debian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
PackageName	r-cran-brglm
PackageSection	gnu-r
PackageVersion	0.5-9-1
SHA-1	0164AD6A590499B88DF3A586EAE09C38BA988C23
SHA-256	FB8D499AD325D89763FF545941AE34E6656F36FA7E57AD75489A6F366C6B51A6

Key	Value
FileSize	89408
MD5	E3E7A77598DAE08B6B4FD8EC33A58D78
PackageDescription	GNU R package for bias reduction in binomial-response GLMs Fit generalized linear models with binomial responses using either an adjusted-score approach to bias reduction or maximum penalized likelihood where penalization is by Jeffreys invariant prior. These procedures return estimates with improved frequentist properties (bias, mean squared error) that are always finite even in cases where the maximum likelihood estimates are infinite (data separation). Fitting takes place by fitting generalized linear models on iteratively updated pseudo-data. The interface is essentially the same as 'glm'. More flexibility is provided by the fact that custom pseudo-data representations can be specified and used for model fitting. Functions are provided for the construction of confidence intervals for the reduced-bias estimates.
PackageMaintainer	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	r-cran-brglm
PackageSection	gnu-r
PackageVersion	0.5-9-1
SHA-1	C0972C5E076B8CA046E761CC3957390506A751F7
SHA-256	F325AA5C10E9696E49E27C4E14D8E2399F465E0A74C05DD13DEF642BF0F1AAC8

Key	Value
FileSize	89276
MD5	3B3A80021CAFB0312A1E425ACF2B29C9
PackageDescription	GNU R package for bias reduction in binomial-response GLMs Fit generalized linear models with binomial responses using either an adjusted-score approach to bias reduction or maximum penalized likelihood where penalization is by Jeffreys invariant prior. These procedures return estimates with improved frequentist properties (bias, mean squared error) that are always finite even in cases where the maximum likelihood estimates are infinite (data separation). Fitting takes place by fitting generalized linear models on iteratively updated pseudo-data. The interface is essentially the same as 'glm'. More flexibility is provided by the fact that custom pseudo-data representations can be specified and used for model fitting. Functions are provided for the construction of confidence intervals for the reduced-bias estimates.
PackageMaintainer	Debian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
PackageName	r-cran-brglm
PackageSection	gnu-r
PackageVersion	0.5-9-1
SHA-1	EF46EBDDF1DAD384AA3BDFB4361C777EE375293D
SHA-256	271D091DFA59C1F6D5541B70ED52CBC611419CD35EEA8C65011FECFB70A895C0