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 protected]>, Brisa N. Sanchez <[email protected]>, Peter X.K. Song <[email protected]>, Raymond Luu <[email protected]>, Wen Wang <[email protected]>|
|Date of publication||2016-06-11 09:37:25|
|Maintainer||Brisa N. Sanchez <[email protected]>|
|Package repository||View on CRAN|
Install the latest version of this package by entering the following in R:
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.