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.
|Author||Meihua Wu <firstname.lastname@example.org>, Brisa N. Sanchez <email@example.com>, Peter X.K. Song <firstname.lastname@example.org>, Raymond Luu <email@example.com>, Wen Wang <firstname.lastname@example.org>|
|Maintainer||Brisa N. Sanchez <email@example.com>|
|Package repository||View on CRAN|
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