qhat_rangerlogit {drpop} | R Documentation |
Estimate marginal and joint distribution of lists j and k using ensemble of ranger and logit.
qhat_rangerlogit(
List.train,
List.test,
K = 2,
j = 1,
k = 2,
margin = 0.005,
...
)
List.train |
The training data matrix used to estimate the distibution functions. |
List.test |
The data matrix on which the estimator function is applied. |
K |
The number of lists in the data. |
j |
The first list that is conditionally independent. |
k |
The second list that is conditionally independent. |
margin |
The minimum value the estimates can attain to bound them away from zero. |
... |
Any extra arguments passed into the function. |
A list of the marginal and joint distribution probabilities q1
, q2
and q12
.
Marvin N. Wright, Andreas Ziegler (2017). ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R. Journal of Statistical Software, 77(1), 1-17. doi:10.18637/jss.v077.i01
Polley, Eric C. and van der Laan, Mark J., (May 2010) Super Learner In Prediction. U.C. Berkeley Division of Biostatistics Working Paper Series. Working Paper 266. https://biostats.bepress.com/ucbbiostat/paper266
## Not run:
qhat = qhat_ranger(List.train = List.train, List.test = List.test, margin = 0.005)
q1 = qhat$q1
q2 = qhat$q2
q12 = qhat$q12
## End(Not run)