Abstract
Bhattacharya modeling can be used for unmasking Gaussian curves in the data. It should with the help of log transformed frequency scores of data histograms enable to identify Gaussian subsets in the data. It can also be applied to produce a better Gaussian fit to a data file than the usual mean and standard deviation does. This chapter assesses how it can be used to identify Gaussian data subsets, and provide models better fitting the data, than the traditional methods do. Bhattacharya modeling with the help of log transformed frequency scores of data histograms enables to identify Gaussian subsets in the data. It can also be applied to produce a better Gaussian fit to a data file than the usual mean and standard deviation does.
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© 2016 Springer International Publishing Switzerland
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Cleophas, T.J., Zwinderman, A.H. (2016). Bhattacharya Modeling for Unmasking Hidden Gaussian Curves. In: Clinical Data Analysis on a Pocket Calculator. Springer, Cham. https://doi.org/10.1007/978-3-319-27104-0_30
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DOI: https://doi.org/10.1007/978-3-319-27104-0_30
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Publisher Name: Springer, Cham
Print ISBN: 978-3-319-27103-3
Online ISBN: 978-3-319-27104-0
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