- x.train
Explanatory variables for training (in sample)
data.
Must be a matrix with (as usual) rows corresponding to
observations and columns to variables.
surv.bart
will generate
draws of \(f(t, x)\) for each \(x\) which is a row of x.train.
- y.train
The continuous outcome.
- P
The number of permutations: typically 50 or 100.
- R
The number of replicates: typically 5 or 10.
- ntree
The number of trees. In variable selection,
the number of trees is smaller than what might
be used for the best fit.
- numcut
The number of possible values of c (see usequants).
If a single number if given, this is used for all variables.
Otherwise a vector with length equal to ncol(x.train) is required,
where the \(i^{th}\) element gives the number of c used for
the \(i^{th}\) variable in x.train.
If usequants is false, numcut equally spaced cutoffs
are used covering the range of values in the corresponding
column of x.train. If usequants is true, then min(numcut, the number of unique values in the
corresponding columns of x.train - 1) c values are used.
- C
The starting value for the multiple of SE. You should not need to
change this except in rare circumstances.
- alpha
The global SE method relies on simultaneous 1-alpha
coverage
across the permutations for all predictor variables.
- k
k is the number of prior standard deviations \(f(t, x)\) is away from +/-3.
The bigger k is, the more conservative the fitting will be.
- power
Power parameter for tree prior.
- base
Base parameter for tree prior.
- ndpost
The number of posterior draws after burn in. In the global SE
method, generally, the method is repeated several times to
establish the variable count probabilities. However, we take the
alternative approach of simply running the MCMC chain longer which
should result in the same stabilization of the estimates. Therefore,
the number of posterior draws in variable selection should be set to a larger value than
would be typically anticipated for fitting.
- nskip
Number of MCMC iterations to be treated as burn in.
- printevery
As the MCMC runs, a message is printed every printevery draws.
- keepevery
Every keepevery
draw is kept.
- keeptrainfits
If TRUE
the draws of \(f(t, x)\) for \(x\) = rows of
x.train are generated.
- seed
seed
required for reproducible MCMC.
- mc.cores
Number of cores to employ in parallel.
- nice
Set the job priority. The default
priority is 19: priorities go from 0 (highest) to 19 (lowest).