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 <email@example.com>, Brisa N. Sanchez <firstname.lastname@example.org>, Peter X.K. Song <email@example.com>, Raymond Luu <firstname.lastname@example.org>, Wen Wang <email@example.com>|
|Date of publication||2016-06-11 09:37:25|
|Maintainer||Brisa N. Sanchez <firstname.lastname@example.org>|
|Package repository||View on CRAN|
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