follic

<p>Competing risk data set involving follicular cell lymphoma.</p>

datasets

A unified treatment of Breiman's random forests for survival, regression and classification problems based on Ishwaran and Kogalur's random survival forests (RSF) package.  Now extended to include multivariate and unsupervised forests.  Also includes quantile regression forests for univariate and multivariate training/testing settings.  The package runs in both serial and parallel (OpenMP) modes.

Udaya Kogalur

randomForestSRC

Random Forests for Survival, Regression, and Classification
(RF-SRC)

follic function

<p>A data frame containing:</p><table><tr><td>
    age      </td>
<td> age</td>
</tr><tr><td>
	  hgb      </td>
<td> hemoglobin (g/l)</td>
</tr><tr><td>
    clinstg	 </td>
<td> clinical stage: 1=stage I, 2=stage II</td>
</tr><tr><td>
	  ch       </td>
<td> chemotherapy</td>
</tr><tr><td>
	  rt       </td>
<td> radiotherapy</td>
</tr><tr><td>
    time     </td>
<td> first failure time</td>
</tr></table>

follic: Follicular Cell Lymphoma

Description

Arguments

Format

References

Examples

age	age
hgb	hemoglobin (g/l)
clinstg	clinical stage: 1=stage I, 2=stage II
ch	chemotherapy
rt	radiotherapy
time	first failure time