Result for 24BD5F8A3043C46A0A8C255AB9C1DBD54258BF9D

Query result

Key Value
FileName./usr/lib64/R/library/msm/R/msm.rdb
FileSize513235
MD59546E5B28EC0DEE9B2BB803261217AC2
SHA-124BD5F8A3043C46A0A8C255AB9C1DBD54258BF9D
SHA-2566A77F5A1DEA6E954C5BE4B2A99C70C4BE5ED4409294D5E096CEBB8943EAB50F9
SSDEEP12288:Txw0UpzE+fsgjfiG6BpMvE7+OIdF0Q3PLwryDREWAv50:TijtE+fszBpMv3OIdKQTwrWk2
TLSHT11FB4232A6A51640D19E5EDAC1048739CAA3FA946FF0747706205C3E0F2B4336DEDFDA9
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
MD55855B80163A3AAEBF786F12483D239E9
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
PackageRelease2.27
PackageVersion1.4
SHA-1F92A4AA28A6E774ABC7BFAFB2E760A72309D23CC
SHA-256118135D31BFBC1C69957E664A5EA627677F8094C4216559C95AF72C95E357BA5