qestimate {quantoptr} | R Documentation |
The Quantile-Optimal Treatment Regime Wrapper Function
Description
The wrapper function for quantile-optimal treatment regime that calls a genetic algorithm.
This function supports the IPWE_Qopt
function.
Usage
qestimate(tau, x, y, a, prob, p_level, nvars, hard_limit, max = TRUE,
cl.setup = 1, s.tol = 1e-04, it.num = 8, pop.size = 3000)
Arguments
tau |
a numeric value between 0 and 1. The quantile level of interest. |
x |
a matrix of observed covariates from the sample. Notice that we assumed the class of treatment regimes is linear. |
y |
a vector, the observed responses from a sample |
a |
a vector of 0s and 1s, the observed treatments from a sample |
prob |
a vector, the propensity scores of getting treatment 1 in the samples |
p_level |
choose between 0,1,2,3 to indicate different levels of output from the genetic function. Specifically, 0 (minimal printing), 1 (normal), 2 (detailed), and 3 (debug.) |
nvars |
an integer. The number of parameters indexing a treatment regime. |
hard_limit |
logical. This logical variable determines if the max.generations
variable is a binding constraint for |
max |
logical. If |
cl.setup |
the number of nodes. >1 indicates choosing parallel computing option in
|
s.tol |
This is the tolerance level used by |
it.num |
integer > 1. This argument will be used in |
pop.size |
an integer with the default set to be 3000. This is the population number for the first generation
in the genetic algorithm ( |
References
Wang L, Zhou Y, Song R and Sherwood B (2017). “Quantile-Optimal Treatment Regimes.” Journal of the American Statistical Association.
See Also
The function IPWE_Qopt
is based on this function.