Description Usage Arguments Value
Bootstrap (default) Bootstrap function for the non-parametric and the nearest neighbor methods
1 2 | boot_default(func, Y, Y_pos, X, X_std, control, wgt, n.quant, lambda,
sigma, grp.size, n.boot, quick)
|
func |
a function for weights calculation (nn / non_parm). |
Y |
the original outcome. |
Y_pos |
outcome after exponential transformation (if needed). |
X |
the original X matrix. |
X_std |
X matrix after standardization. |
control |
numeric data frame or matrix of factors to control for. these are factors that we can't consider while looking for the optimal intervention (e.g. race). |
wgt |
an optional vector of weights. |
n.quant |
number of quantiles to use when calculating CDF distance. |
lambda |
the lagrange multiplier. also known as the shadow price of an intervention. |
sigma |
distance penalty for the nearest-neighbors method. |
grp.size |
for the nearest-neighbors method; if the number of examples in each
control group is smaller than grp.size, performs weight adjustment
using |
n.boot |
number of bootstrap replications to use for the standard errors / confidence intervals calculation. |
quick |
logical. if TRUE, returns only E(X | I=1) - E(X | I=0) as an estimate.
this estimate is used by |
a list - the output from the function 'boot()'.
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