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  "Title": "Estimation for the Power Series Cure Rate Model",
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  "Authors@R": "c(person(\"Diego\", \"Gallardo\", role = c(\"aut\",\"cre\"), email = \"diego.gallardo.mateluna@gmail.com\"),\nperson(\"Reza\", \"Azimi\", role = c(\"ctb\"), email = \"r.azimi@uma.ac.ir\"),\nperson(\"Daniel\",\"Jana\", role = c(\"ctb\"), email = \"daniel.jana2001@alumnos.ubiobio.cl\"),\nperson(\"Yolanda\",\"Gomez\", role = c(\"ctb\"), email = \"ygomez@ubiobio.cl\"))",
  "Author": "Diego Gallardo [aut, cre], Reza Azimi [ctb], Daniel Jana [ctb],\nYolanda Gomez [ctb]",
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  "Description": "Provides estimation and simulation tools for particular\ncases of the power series cure rate model\n<doi:10.1080/03610918.2011.639971>. For the distribution of the\nconcurrent causes the alternative models are the Poisson,\nlogarithmic, negative binomial and Bernoulli (which are\nincludes in the original work), the polylogarithm model\n<doi:10.1080/00949655.2018.1451850> and the Flory-Schulz\n<doi:10.3390/math10244643>. The estimation procedure is based\non the EM algorithm discussed in\n<doi:10.1080/03610918.2016.1202276>. For the distribution of\nthe time-to-event the alternative models are slash half-normal,\nWeibull, gamma and Birnbaum-Saunders distributions.",
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