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Determine the sample size requirement to achieve the target probability of correct classification (PCC) for studies employing high-dimensional features. The package implements functions to 1) determine the asymptotic feasibility of the classification problem; 2) compute the upper bounds of the PCC for any linear classifier; 3) estimate the PCC of three design methods given design assumptions; 4) determine the sample size requirement to achieve the target PCC for three design methods.
| Version: | 1.1 |
| Published: | 2016-06-11 |
| Author: | Meihua Wu, Brisa N. Sanchez, Peter X.K. Song, Raymond Luu, Wen Wang |
| Maintainer: | Brisa N. Sanchez <brisa at umich.edu> |
| License: | GPL-2 |
| NeedsCompilation: | yes |
| CRAN checks: | HDDesign results |
| Reference manual: | HDDesign.pdf |
| Package source: | HDDesign_1.1.tar.gz |
| Windows binaries: | r-devel: HDDesign_1.1.zip, r-release: HDDesign_1.1.zip, r-oldrel: HDDesign_1.1.zip |
| macOS binaries: | r-release (arm64): HDDesign_1.1.tgz, r-oldrel (arm64): HDDesign_1.1.tgz, r-release (x86_64): HDDesign_1.1.tgz, r-oldrel (x86_64): HDDesign_1.1.tgz |
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