Parents (Total: 10)

The searched file hash is included in 10 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
MD5	4665CA05D382FE9EE614C00A0F0259A5
PackageArch	ppc64
PackageDescription	Functions for fitting general continuous-time Markov and hidden Markov multi-state models to longitudinal data. Both Markov transition rates and the hidden Markov output process can be modeled in terms of covariates. A variety of observation schemes are supported, including processes observed at arbitrary times, completely-observed processes, and censored states.
PackageMaintainer	Fedora Project
PackageName	R-msm
PackageRelease	3.fc22
PackageVersion	1.3
SHA-1	C6E9BAEDEBAFE558E7D000AEF649771A7007EEE0
SHA-256	943C6EB4554113D151319D42DE9CAADE09D9706D48BDAE4AAED9D406D156FB39

Key	Value
MD5	06C13F782D4E808D137D6B18EF2C1E41
PackageArch	aarch64
PackageDescription	Functions for fitting general continuous-time Markov and hidden Markov multi-state models to longitudinal data. Both Markov transition rates and the hidden Markov output process can be modeled in terms of covariates. A variety of observation schemes are supported, including processes observed at arbitrary times, completely-observed processes, and censored states.
PackageMaintainer	Fedora Project
PackageName	R-msm
PackageRelease	3.fc22
PackageVersion	1.3
SHA-1	1E6FC12BC91EF6F0EC3579C2ECFE57FCF0DF5D82
SHA-256	55D77ADAC15683D499329F292707230EC6177FA0475691F0E48C202B7427E9C9

Key	Value
MD5	FC27FC790691B2E0DA8010D75822AF95
PackageArch	s390
PackageDescription	Functions for fitting general continuous-time Markov and hidden Markov multi-state models to longitudinal data. Both Markov transition rates and the hidden Markov output process can be modeled in terms of covariates. A variety of observation schemes are supported, including processes observed at arbitrary times, completely-observed processes, and censored states.
PackageMaintainer	Fedora Project
PackageName	R-msm
PackageRelease	3.fc22
PackageVersion	1.3
SHA-1	9C52B81EB65EAD587DF379206EA5683C6A78A101
SHA-256	3DED46483BF63D5318914B3ED61C9F6575AD86B874D036B9D2E4E40983511332

Key	Value
MD5	87695DF2E82AC0FD2F2318E244115075
PackageArch	s390x
PackageDescription	Functions for fitting general continuous-time Markov and hidden Markov multi-state models to longitudinal data. Both Markov transition rates and the hidden Markov output process can be modeled in terms of covariates. A variety of observation schemes are supported, including processes observed at arbitrary times, completely-observed processes, and censored states.
PackageMaintainer	Fedora Project
PackageName	R-msm
PackageRelease	3.fc22
PackageVersion	1.3
SHA-1	B8EBB5DE5847B7B277CCEB6D2AB4775260EBBF7F
SHA-256	0FD23E3C127893901777491DE7E6E1B8B07638EABF1E86D9DE2B74573ED33814

Key	Value
MD5	B61F996CA770CC9255C3295CC4F7E9A6
PackageArch	s390
PackageDescription	Functions for fitting general continuous-time Markov and hidden Markov multi-state models to longitudinal data. Both Markov transition rates and the hidden Markov output process can be modeled in terms of covariates. A variety of observation schemes are supported, including processes observed at arbitrary times, completely-observed processes, and censored states.
PackageMaintainer	Fedora Project
PackageName	R-msm
PackageRelease	3.fc21
PackageVersion	1.3
SHA-1	68B69AE67C523AC8F5CE0F27298BE2E61277DBCD
SHA-256	87819AD5D6E6FC56B775F8B40D9703A0A30DD432C082D58CA24AEC120B4F26B5

Key	Value
MD5	E25E082B237D69DBB38AE84E3B565B04
PackageArch	ppc64le
PackageDescription	Functions for fitting general continuous-time Markov and hidden Markov multi-state models to longitudinal data. Both Markov transition rates and the hidden Markov output process can be modeled in terms of covariates. A variety of observation schemes are supported, including processes observed at arbitrary times, completely-observed processes, and censored states.
PackageMaintainer	Fedora Project
PackageName	R-msm
PackageRelease	3.fc22
PackageVersion	1.3
SHA-1	D69833AE47F5825191FFF632BED9BA47CB2B8F23
SHA-256	08AF3A220327C25EE4B35C663AE82F0F3CD5629DFF8729E5CE37639015E0D6A2

Key	Value
MD5	6E363E86E6A7DB904D391C873D19D927
PackageArch	ppc64
PackageDescription	Functions for fitting general continuous-time Markov and hidden Markov multi-state models to longitudinal data. Both Markov transition rates and the hidden Markov output process can be modeled in terms of covariates. A variety of observation schemes are supported, including processes observed at arbitrary times, completely-observed processes, and censored states.
PackageMaintainer	Fedora Project
PackageName	R-msm
PackageRelease	3.fc21
PackageVersion	1.3
SHA-1	7466F554CD6D6555FFB0DD20962AF463D4C9C175
SHA-256	BC41438FB4E978F7E53C58531571DC5048693BB42BFDCB6B2DAA06C4413E1194

Key	Value
MD5	D74D0ABD497E725908C6E0F53A5A328D
PackageArch	aarch64
PackageDescription	Functions for fitting general continuous-time Markov and hidden Markov multi-state models to longitudinal data. Both Markov transition rates and the hidden Markov output process can be modeled in terms of covariates. A variety of observation schemes are supported, including processes observed at arbitrary times, completely-observed processes, and censored states.
PackageMaintainer	Fedora Project
PackageName	R-msm
PackageRelease	3.fc21
PackageVersion	1.3
SHA-1	CA018C608E01C371010B4BDBBEB1A3E40814BDA1
SHA-256	4C4E0344C257D703F07E95ED24B5FFCA2FF9731CFFCBB122342481A8FDF4259B

Key	Value
MD5	AB90EECEE1657F36833F14220EF05650
PackageArch	s390x
PackageDescription	Functions for fitting general continuous-time Markov and hidden Markov multi-state models to longitudinal data. Both Markov transition rates and the hidden Markov output process can be modeled in terms of covariates. A variety of observation schemes are supported, including processes observed at arbitrary times, completely-observed processes, and censored states.
PackageMaintainer	Fedora Project
PackageName	R-msm
PackageRelease	3.fc21
PackageVersion	1.3
SHA-1	69E7A75A5BD96EEAF391C6805CACAC765A337818
SHA-256	1C83779FD381C6DEB2316B37C518DDF8BD872EEB1B137DF28C9C66867134E2AA

Key	Value
MD5	4830442313E27167F7E75DC27BAC2DA9
PackageArch	ppc64le
PackageDescription	Functions for fitting general continuous-time Markov and hidden Markov multi-state models to longitudinal data. Both Markov transition rates and the hidden Markov output process can be modeled in terms of covariates. A variety of observation schemes are supported, including processes observed at arbitrary times, completely-observed processes, and censored states.
PackageMaintainer	Fedora Project
PackageName	R-msm
PackageRelease	3.fc21
PackageVersion	1.3
SHA-1	76FC6574D179F9335595181EC5BD7D72F8007352
SHA-256	302F94ED1FBE2E61A3FD829A0C42F7C4110DBA36CCE66AD23A333C0E1090DDFB