cvq2.sample.A_pred


  This data set can be used to determine the prediction power of the model <var>M</var> generated with <code><a rd-options="" href="/link/cvq2.sample.A?package=cvq2&version=1.2.0" data-mini-rdoc="cvq2::cvq2.sample.A">cvq2.sample.A</a></code>.
  The four observations <var>y</var> depend on two parameters ($x_1$, $x_2$).


The external prediction capability of quantitative structure-activity relationship (QSAR) models is often quantified using the predictive squared correlation coefficient. This value can be calculated with an external data set or by cross validation.

Torsten Thalheim

cvq2

Calculate the predictive squared correlation coefficient

cvq2.sample.A_pred function

A data frame with four observations. 
  Each row contains two parameters and the observed value.
  <dl>
    <dt><code>x1</code></dt><dd>parameter 1</dd> <dt><code>x2</code></dt><dd>parameter 2</dd> <dt><code>y</code></dt><dd>observation</dd> </dl> 

Format

Generic data set, created for this purpose only.

Source


  Prediction set for model set <code><a rd-options="" href="/link/cvq2.sample.A?package=cvq2&version=1.2.0" data-mini-rdoc="cvq2::cvq2.sample.A">cvq2.sample.A</a></code>.


cvq2.sample.A_pred: Prediction set for model set `cvq2.sample.A`.

Description

Usage

Arguments

Format

Source

Details

See Also