Result for 3E6636F9D3D3AF369904EA826919C8BC4F05C207

Query result

Key Value
FileName./usr/lib64/R/library/msm/libs/msm.so
FileSize129352
MD56098C8E4F5BA9C8A35006E6059885559
SHA-13E6636F9D3D3AF369904EA826919C8BC4F05C207
SHA-25628B696F26AF768C3A26DA5EC2CC220F0184E90BEB54F8E80C098B19D7D99FBC8
SSDEEP1536:BmUWvBOb3lJgUFazd6FMhYEDIiXIHMEAkQ17tFXQNiIBr9MVjfTnZV38lLl9sbWf:1RbtqNX2MFkQdtFLHWDsbW5zMm
TLSHT198C3F889B8525C7CE4A175303A76781AE32927C8532C06391FEB5E281B7DF1B2DC7762
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
MD59144E198D71718D63335CBEBAB05D857
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
PackageReleaselp151.2.59
PackageVersion1.4
SHA-10500501E30F2021928DC92EFDAC7813A3E18389C
SHA-25625297FE0EA198BA15C874A6049803B93F54EEA023A40D50238A6745730364A63