Result for 398ADEAFEC65541A996B2429241109812D0AA8B4

Query result

Key Value
FileName./usr/lib64/R/library/msm/Meta/package.rds
FileSize1096
MD53378807672D9CDC8B83C054DB606BB9F
SHA-1398ADEAFEC65541A996B2429241109812D0AA8B4
SHA-25633E23FF89A7D0E1762A517F7558A5F637E716D97C1752F113F0AC45465BE89A8
SSDEEP24:XIreRL6vLrLvyQAjg2iIdnEMrUV/A/ovcVRTP/9ZobvbcUwmEmh71n4L0El:XBRL6kjhr9KVYQINZo3cfNmh71n4L0M
TLSHT1B011B688CB264723C1D87F7935294916E420D35D2299A2A8B674F1E527CE84FEC038F8
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
MD5610BE6930C0310A4E2C482E5537E406C
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
PackageReleaselp153.2.12
PackageVersion1.4
SHA-1CFB4013CEDDF349A883F11AF6F458EB83DE86F48
SHA-256F0CB01AC0C4784468FCAB4604F0E59A89F77B2706DE551588A37DF57ED8F15FA