Parents (Total: 14)

The searched file hash is included in 14 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
FileSize	123868
MD5	062C60D0A9C269CFC62E48A72B2E572C
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 R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageName	r-cran-brglm
PackageSection	gnu-r
PackageVersion	0.7.2-1
SHA-1	6F8315D89C58CB4F5950F11390F62801959130AF
SHA-256	D5FC2C1059A187F9288787E73553E394AC86C969DA15ED73355347F331103AEC

Key	Value
FileSize	124100
MD5	9AB0D42EFDFC95E86B56C425F3D4A2F4
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 R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageName	r-cran-brglm
PackageSection	gnu-r
PackageVersion	0.7.2-1
SHA-1	B69DDD42492DA42982F1007BA340ACF039EFB0F5
SHA-256	5022D552FCF2F19AAB12282EB23E755248E20D028AD8D12F621F3306C81AE732

Key	Value
FileSize	124148
MD5	69CDF756603158644420AB8E50E5A045
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 R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageName	r-cran-brglm
PackageSection	gnu-r
PackageVersion	0.7.2-1
SHA-1	19A107F445D112054CAF52C6BB46E38F91863F70
SHA-256	5DCA2D11537EAEF3F672F07D5556674510FD50E05E590F79A3E870327E3E6D16

Key	Value
FileSize	125244
MD5	F6C18D2FCA3DB514813C06E6AD7B21A2
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 R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageName	r-cran-brglm
PackageSection	gnu-r
PackageVersion	0.7.2-1
SHA-1	EF61D8496674063966A4F60EF4E15AF1C7EA3814
SHA-256	DEC1E4D300EF89B18D1515493F4DAFAE0BC112362D7B07806D49919EEEC62E93

Key	Value
FileSize	124372
MD5	40656DBCF603F24A14B8FAA9B2016AFA
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 R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageName	r-cran-brglm
PackageSection	gnu-r
PackageVersion	0.7.2-1
SHA-1	14B270E7ECBEE8DC5CCE92DD75DD901C4584B6D2
SHA-256	980E5CE02D93A5640A0B52FAF3A8AB11AB72EE32FE6A0E6A329920230B968706

Key	Value
MD5	5724C63933B2F8DE45D59D5A1B734426
PackageArch	x86_64
PackageDescription	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.
PackageName	R-brglm
PackageRelease	lp153.1.3
PackageVersion	0.7.2
SHA-1	78F4A7164F96FDC7532CCA2BC3D71AEC35FD87FA
SHA-256	6B666F3A0709954FD394C74BACAE349E6C35A0AAA773F9BEF0088F2C7257760D

Key	Value
FileSize	124388
MD5	BA748F3E21448474FE111779159AFE85
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 R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageName	r-cran-brglm
PackageSection	gnu-r
PackageVersion	0.7.2-1
SHA-1	203C93730E87A67B7F00FE93D91FC32A81E1F211
SHA-256	DC69E5FADDCB6F5EC0EC79C3F73C4A3A168E24A18A2DD00ADB27FCE9FD670E9D

Key	Value
FileSize	123952
MD5	E21FF49D480D464E9B998131E02C9A74
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 R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageName	r-cran-brglm
PackageSection	gnu-r
PackageVersion	0.7.2-1
SHA-1	049487A17BBE796E8F2C58DF9DF8EBF6F9614774
SHA-256	EBE35DA45C2932371E0F9E925C4BF5A61716AF87796EA3974941D0EEB6EFE31F

Key	Value
FileSize	124104
MD5	B5D5FD5551AF34F3DC348FFD55F82C30
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 R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageName	r-cran-brglm
PackageSection	gnu-r
PackageVersion	0.7.2-1
SHA-1	7E602BF71E6546E82D5E8FE6861DB15195A9D65D
SHA-256	B91CAE63B58AE8C909ECA1C2AD6109CF987C382467A81BD0E4BF4C82F235B3F0

Key	Value
MD5	C5261CF61DC5F5DFC070A11AE84BC53E
PackageArch	x86_64
PackageDescription	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.
PackageName	R-brglm
PackageRelease	lp154.1.1
PackageVersion	0.7.2
SHA-1	EE999711DC4EA8E3C24BA525E5D2F7C7C91709AE
SHA-256	4A886644D8DB971EA4BD966618C998085C414B5CBE0FCFE5A460698CD1F9841D

Key	Value
MD5	0286855345E1B2A8E09FEFF96AB19FCB
PackageArch	x86_64
PackageDescription	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.
PackageName	R-brglm
PackageRelease	lp153.1.1
PackageVersion	0.7.2
SHA-1	27745A2702479F4C311FA2E69524E2536D950E53
SHA-256	D7F60F07C295DA20CC1A5D641CA14ACDFA8D623E998221CB22D2340921AC2C5C

Key	Value
MD5	6CBEE56EED656AAE8AFE7C01F82ED182
PackageArch	x86_64
PackageDescription	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.
PackageName	R-brglm
PackageRelease	1.20
PackageVersion	0.7.2
SHA-1	87507AB50873EB366A36D93741D108CAA18B3B0B
SHA-256	4D7E0A86977773F572160D66A06A72C6FE924D91CA3FB66C88D2CEBA12584AA5

Key	Value
FileSize	124056
MD5	4EB8CE5FB3B905311C60BBFDBDC15E67
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 R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageName	r-cran-brglm
PackageSection	gnu-r
PackageVersion	0.7.2-1
SHA-1	ACC29A4290ECA57B4997CEF50352D132349EA702
SHA-256	00967E0951EAB21ED06F2B9171D9156D073781E2CC0EAACB186CF5C1C09C55F5

Key	Value
MD5	7389C6FD4277CCE7A66A28074DE5A001
PackageArch	x86_64
PackageDescription	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.
PackageName	R-brglm
PackageRelease	lp152.1.4
PackageVersion	0.7.2
SHA-1	CC22F98B1C96CD6BB1024795C76184A812437EE8
SHA-256	69049302FA2907C172D28E3B7AFB09F6C6886EBFB3EDB40834B9BB2A40F68EA0