Calculating Confidence Intervals for Dark Adaptation Data

Jeremiah Kelly (Other)

    Research output: Non-textual formExhibition

    42 Downloads (Pure)

    Abstract

    Dark adaptation can be modeled using a seven parameter composite function. I measured this function in 35 subjects. An algorithm was used that determined the parameters for each subject. There is no theoretical route to determine confidence intervals for these parameters. Therefore a bootstrap method using the high through-put computer cluster was used. This reduced the total calculation time from 14 days to 5 hours. MSE is not a useful substitute for bootstrapped confidence intervals.
    Original languageEnglish
    Publication statusPublished - 2011
    EventFaculty of Life Sciences Symposium - Armitage Centre, Manchester, United Kingdom
    Duration: 23 Sept 201123 Sept 2011

    Keywords

    • Dark adaptation, nonlinear, confidence intervals, Poster

    Fingerprint

    Dive into the research topics of 'Calculating Confidence Intervals for Dark Adaptation Data'. Together they form a unique fingerprint.

    Cite this