Result for 03E4E1DB5CFD6EE198EA73E60C804FB40CEB0011

Query result

Key Value
FileName./usr/lib64/R/library/msm/libs/msm.so
FileSize128768
MD5314896EA01CA78C42EAB251DD87C9CD1
SHA-103E4E1DB5CFD6EE198EA73E60C804FB40CEB0011
SHA-25632F14B1E8C61F6FF74997931590886AD1658958F1F0EA469CB2BE6E5E0A5E984
SSDEEP1536:PmYWSvggUB9zHX1M5OwWSChQEEDmxhfo9FHlS3pcJJaj3G0ZozzGErl9sb25zE+:XYh2Eimxhw9FM0djsb25zE
TLSHT147C30989B8525CBCE4A175703A767816E32926C8532C06391FEB5E2C1B7DF0B2DC7762
hashlookup:parent-total1
hashlookup:trust55

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Parents (Total: 1)

The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD57556CB025FC19F20C01C6B9B7F9B6B43
PackageArchx86_64
PackageDescriptionFunctions for fitting general continuous-time Markov and hidden Markov multi-state models to longitudinal data. A variety of observation schemes are supported, including processes observed at arbitrary times (panel data), continuously-observed processes, and censored states. Both Markov transition rates and the hidden Markov output process can be modelled in terms of covariates, which may be constant or piecewise-constant in time.
PackageNameR-msm
PackageRelease2.16
PackageVersion1.4
SHA-11B40916FDBCD510DAFC008DE933C6E6D1F4AE2E6
SHA-256AEA85EC2DB22DD4D2A0B526D8E9C8443B1B7720B3A2650E506D00893E46CAC0E