Result for 16CC25BB53B760F36824DE8401591D0A4077CD24

Query result

Key Value
FileName./usr/lib/R/library/msm/R/msm.rdb
FileSize513231
MD5EE981CE3F83257D50072A8BE9A12FB60
SHA-116CC25BB53B760F36824DE8401591D0A4077CD24
SHA-256AA4BA1D6E0EEC5AF25B53387984EAFC5202B1F93112D4578A68AB45E4574D857
SSDEEP12288:6xw0UpzE+fsgjfiG6BpMvE7+OIdF0Q3PLwryDREWAv50:6ijtE+fszBpMv3OIdKQTwrWk2
TLSHT1B1B4232A6A51640D19E5ED6C1048739CAA3FA946FF0747307205C3E0F2B4336EEDBDA9
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
MD5B8991BA42431BBAEF482F5E6864B0F74
PackageArcharmv7hl
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
PackageRelease2.138
PackageVersion1.4
SHA-17E441A3388A2FA3CCABC58CEE3F9B7F95D57C2ED
SHA-256569A1963907386B349B8E57A96354B011716532F6F141D966D6EC76673C37E98