Parents (Total: 8)

The searched file hash is included in 8 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
MD5	E68F6582DA27EDCA1E69F530A634B380
PackageArch	x86_64
PackageDescription	A 'shiny' application that allows non-expert 'R' users to easily model species distribution. It offers a reproducible work flow for species distribution modeling into a single and user friendly environment. 'sdmApp' takes 'raster' data (in format supported by the 'raster package') and species occurrence data (several format supported) as input argument. It provides an interactive graphical user interface (GUI).
PackageMaintainer	https://www.suse.com/
PackageName	R-sdmApp
PackageRelease	lp154.4.1
PackageVersion	0.0.2
SHA-1	B99B5922E3BFEA92FC5A752BC08622F7B54B85CA
SHA-256	283EBEDC43A1E39D2A6A6138553C5874BABB315C75F4FEF29EC15A96964BDD83

Key	Value
MD5	61A7E727ECD2232FD29200F6EF0BBC2E
PackageArch	x86_64
PackageDescription	Data from statistical agencies and other institutions are mostly confidential. This package (see also Templ, Kowarik and Meindl (2017) <doi:10.18637/jss.v067.i04>) can be used for the generation of anonymized (micro)data, i.e. for the creation of public- and scientific-use files. The theoretical basis for the methods implemented can be found in Templ (2017) <doi:10.1007/978-3-319-50272-4>. Various risk estimation and anonymisation methods are included. Note that the package includes a graphical user interface (Meindl and Templ, 2019 <doi:10.3390/a12090191>) that allows to use various methods of this package.
PackageName	R-sdcMicro
PackageRelease	lp152.5.1
PackageVersion	5.6.1
SHA-1	547A26A4286D512AD2BB6FF72D3F5E46BBB1C61E
SHA-256	B91E61B2E0CCCC87E0D6AA8D0127A0A3FB39DA47CA321558A8EC5FA608985003

Key	Value
MD5	18A6C825FC36E3F25885D4754DA9EC71
PackageArch	x86_64
PackageDescription	Data from statistical agencies and other institutions are mostly confidential. This package (see also Templ, Kowarik and Meindl (2017) <doi:10.18637/jss.v067.i04>) can be used for the generation of anonymized (micro)data, i.e. for the creation of public- and scientific-use files. The theoretical basis for the methods implemented can be found in Templ (2017) <doi:10.1007/978-3-319-50272-4>. Various risk estimation and anonymisation methods are included. Note that the package includes a graphical user interface (Meindl and Templ, 2019 <doi:10.3390/a12090191>) that allows to use various methods of this package.
PackageName	R-sdcMicro
PackageRelease	lp153.5.1
PackageVersion	5.6.1
SHA-1	CC06C36ED1144746D290B8A01CBB31502F3F8B8F
SHA-256	537F07D39F32D36117FE0BB29839B872000F62493EDEAEFD52E4F55A5236B2D7

Key	Value
MD5	BB4A342C9995BB9B7DE7C13E4EEE0570
PackageArch	x86_64
PackageDescription	Data from statistical agencies and other institutions are mostly confidential. This package (see also Templ, Kowarik and Meindl (2017) <doi:10.18637/jss.v067.i04>) can be used for the generation of anonymized (micro)data, i.e. for the creation of public- and scientific-use files. The theoretical basis for the methods implemented can be found in Templ (2017) <doi:10.1007/978-3-319-50272-4>. Various risk estimation and anonymisation methods are included. Note that the package includes a graphical user interface (Meindl and Templ, 2019 <doi:10.3390/a12090191>) that allows to use various methods of this package.
PackageName	R-sdcMicro
PackageRelease	lp154.5.1
PackageVersion	5.6.1
SHA-1	16BA466E3F88C4ECD0C365263B6330CE61DAA916
SHA-256	B419D73105077B9A02D94FC10479C3E13151EAE5D5E641FA5DAA5064D0F090C3

Key	Value
MD5	9BF6F547F2976F5E57B0E3B46356E13D
PackageArch	x86_64
PackageDescription	A 'shiny' application that allows non-expert 'R' users to easily model species distribution. It offers a reproducible work flow for species distribution modeling into a single and user friendly environment. 'sdmApp' takes 'raster' data (in format supported by the 'raster package') and species occurrence data (several format supported) as input argument. It provides an interactive graphical user interface (GUI).
PackageName	R-sdmApp
PackageRelease	4.6
PackageVersion	0.0.2
SHA-1	00D05FAF4FFEBE790906D1A59DCCD00552B32CFA
SHA-256	FADDB1D2D51D77B6944EBB478089821BCD38D23075934D3747E9EB36E2D4FAEE

Key	Value
MD5	F20F1B2052BB6A08B112DAB4D7E83E0C
PackageArch	x86_64
PackageDescription	A 'shiny' application that allows non-expert 'R' users to easily model species distribution. It offers a reproducible work flow for species distribution modeling into a single and user friendly environment. 'sdmApp' takes 'raster' data (in format supported by the 'raster package') and species occurrence data (several format supported) as input argument. It provides an interactive graphical user interface (GUI).
PackageName	R-sdmApp
PackageRelease	lp152.4.2
PackageVersion	0.0.2
SHA-1	392FE5E277E864D78673AA94B275A11C4254B17F
SHA-256	5664077975BCCB1FE3D3FF55CA8D5D9FB896F05555D3502B479174F969021521

Key	Value
MD5	417DEFF20750DEE1826D2D233BD97383
PackageArch	x86_64
PackageDescription	A 'shiny' application that allows non-expert 'R' users to easily model species distribution. It offers a reproducible work flow for species distribution modeling into a single and user friendly environment. 'sdmApp' takes 'raster' data (in format supported by the 'raster package') and species occurrence data (several format supported) as input argument. It provides an interactive graphical user interface (GUI).
PackageName	R-sdmApp
PackageRelease	lp153.4.2
PackageVersion	0.0.2
SHA-1	DF5C0390A35EBF549022DA67B78F3C06983BB508
SHA-256	C7ED0F3BFF3BF12D7648F37C83EBB9215158E8C5CA1E3555FE3963599D128019

Key	Value
MD5	097D91A0F63F819C1901EF3338499169
PackageArch	x86_64
PackageDescription	Data from statistical agencies and other institutions are mostly confidential. This package (see also Templ, Kowarik and Meindl (2017) <doi:10.18637/jss.v067.i04>) can be used for the generation of anonymized (micro)data, i.e. for the creation of public- and scientific-use files. The theoretical basis for the methods implemented can be found in Templ (2017) <doi:10.1007/978-3-319-50272-4>. Various risk estimation and anonymisation methods are included. Note that the package includes a graphical user interface (Meindl and Templ, 2019 <doi:10.3390/a12090191>) that allows to use various methods of this package.
PackageName	R-sdcMicro
PackageRelease	5.3
PackageVersion	5.6.1
SHA-1	A080EA19355BFC81C3EA9B6EA4A8DD06DCD5610D
SHA-256	94894E276C2EA091E78046934910048E929EF077A13AA47D2803188799239CB3