Regression beta coefficients are use for building a weighted distance measure between the learning and verum data set. The learning data set is used for learning the Cox model and use the obtained weights for calculating a (n x m)-distance matrix, where n is the number of cases in the learning data set and m is the number of cases of the query data. This distance matrix can then be used for cluster analysis or for getting for each case in the query data k (=1,...,l) smilar cases from the learning data. The rms-package is used for model fitting, variable selection, and checking the assumptions. If query data is ommitted, a n x n- distance matrix is returned.
CoxBetaModelAn R6Class generator object
For usage details see Methods, Arguments, and Examples sections.
new(formula, ...)This method is used to create an
object of this class RFModel. Formula for analysis has to be
provided. Further parameters for the ranger call can be provided here.
fit(dtData)Fits the RandomForest model.
See CBRBase class.