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  "Title": "The Analysis of Dark Adaptation Data",
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  "Date": "2025-01-14",
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  "Description": "The recovery of visual sensitivity in a dark environment\nis known as dark adaptation. In a clinical or research setting\nthe recovery is typically measured after a dazzling flash of\nlight and can be described by the Mahroo, Lamb and Pugh (MLP)\nmodel of dark adaptation. The functions in this package take\ndark adaptation data and use nonlinear regression to find the\nparameters of the model that 'best' describe the data. They do\nthis by firstly, generating rapid initial objective estimates\nof data adaptation parameters, then a multi-start algorithm is\nused to reduce the possibility of a local minimum. There is\nalso a bootstrap method to calculate parameter confidence\nintervals. The functions rely upon a 'dark' list or object.\nThis object is created as the first step in the workflow and\nparts of the object are updated as it is processed.",
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  "URL": "https://github.com/emkayoh/Dark",
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  "Date/Publication": "2025-01-19 11:46:47 UTC",
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