{ "_id": "6a47953a2f27a93436c0e0ec", "Package": "extBatchMarking", "Type": "Package", "Title": "Extended Batch Marking Models", "Version": "1.1.0", "Date": "2024-10-04", "Maintainer": "Kehinde Olobatuyi ", "Authors@R": "c(person(given = \"Kehinde\",\nfamily = \"Olobatuyi\",\nrole = c(\"aut\", \"cre\"),\nemail = \"olobatuyikenny@uvic.ca\",\ncomment = c(ORCID = \"0000-0002-4635-7895\")),\nperson(given = \"Simon\",\nfamily = \"Johns\",\nrole = c(\"aut\"),\nemail = \"simon737@outlook.com\"),\nperson(given = \"Matthew RP\",\nfamily = \"Parker\",\nrole = c(\"aut\"),\nemail = \"mrparker909@gmail.com\",\ncomment = c(ORCID = \"0000-0003-3021-7959\")),\nperson(given = \"Steve\",\nfamily = \"Hof\",\nrole = c(\"aut\"),\nemail = \"steven.Hof@icloud.com\"),\nperson(given = \"Laura LE\",\nfamily = \"Cowen\",\nrole = c(\"aut\"),\nemail = \"lcowen@uvic.ca\",\ncomment = c(ORCID = \"0000-0002-0853-1450\")) )", "Description": "A system for batch-marking data analysis to estimate\nsurvival probabilities, capture probabilities, and enumerate\nthe population abundance for both marked and unmarked\nindividuals. The estimation of only marked individuals can be\nachieved through the batchMarkOptim() function. Similarly, the\ncombined marked and unmarked can be achieved through the\nbatchMarkUnmarkOptim() function. The algorithm was also\nimplemented for the hidden Markov model encapsulated in\nbatchMarkUnmarkOptim() to estimate the abundance of both marked\nand unmarked individuals in the population. The package is\nbased on the paper: \"Hidden Markov Models for Extended Batch\nData\" of Cowen et al. 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