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New Theory of Discriminant Analysis After R. Fisher

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  • 228 pages
  • 8 hours of reading

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The book uniquely compares eight linear discriminant functions (LDFs) across various datasets, including Fisher's iris data and medical data with collinearities. It introduces a 100-fold cross-validation method tailored for small samples and presents a straightforward model selection procedure to identify the optimal model based on minimum M2. The Revised IP-OLDF, evaluated using the MNM criterion, demonstrates superior performance compared to other M2s across the examined datasets, making it a significant contribution to statistical modeling and data analysis.

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New Theory of Discriminant Analysis After R. Fisher, Shuichi Shinmura

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Released
2018
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