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  "Type": "Package",
  "Title": "Markov Chains with Rewards",
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  "Date": "2021-03-08",
  "Authors@R": "c(person(\"Daniel\", \"Schneider\" , role = c(\"aut\", \"cre\"), email = \"schneider@demogr.mpg.de\"),\nperson(\"Mikko\" , \"Myrskyla\"  , role = \"ctb\"),\nperson(\"Alyson\", \"van Raalte\", role = \"ctb\"))",
  "Author": "Daniel Schneider [aut, cre], Mikko Myrskyla [ctb], Alyson van\nRaalte [ctb]",
  "Maintainer": "Daniel Schneider <schneider@demogr.mpg.de>",
  "Description": "In the context of multistate models, which are popular in\nsociology, demography, and epidemiology, Markov chain with\nrewards calculations can help to refine transition timings and\nso obtain more accurate estimates. The package code\naccommodates up to nine transient states and irregular age\n(time) intervals. Traditional demographic life tables result as\na special case. Formulas and methods involved are explained in\ndetail in the accompanying article: Schneider / Myrskyla / van\nRaalte (2021): Flexible Transition Timing in Discrete-Time\nMultistate Life Tables Using Markov Chains with Rewards, MPIDR\nWorking Paper WP-2021-002.",
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