importData: Import Data to create a 'TrtDataObj' object.
In SkadiEye/ITRlearn: Individualized Treatment Rule Learning

Description Usage Arguments Details Value See Also

A user-friendly function to create a TrtDataObj object.

1
2
3

importData(X, trtResp = NULL, trtLabl = NULL, trtLevl = levels(trtLabl),
  trtTrue = NULL, sample.weight = rep(1, dim(X)[1]),
  sample.inclsn = rep(TRUE, dim(X)[1]))

`X`	A `matrix` or `data.frame` containing all samples/variables. It has to be `numeric` and cannot be left blank. Any variable with missing value will be removed.
`trtResp`	A `numeric` vector, indicating the response under assigned treatment. If it's left blank, t his object could not be used to build models but could be used in `predict` function.
`trtLabl`	A `factor` vector, the sample treatment labels.
`trtLevl`	A `character` vector of length two, the unique treatment labels. The default is `levels(trtLabl)`.
`trtTrue`	A `factor` vector, true optimal treatment labels. Left missing if not provided.
`sample.weight`	A `numeric` vector, sample weight used to evaluate the performance.
`sample.inclsn`	A `logical` vector, indicating whether a sample is used to evaluate the performance.

This function takes data set and generate an TrtDataObj in a flexible way:

X can be either a matrix of a data.frame, of which each column is a numeric predictor of the data set and each row is all predictor values for a sample. X should contain all samples/variables.

An TrtDataObj object.

TrtDataObj-class

SkadiEye/ITRlearn documentation built on May 24, 2019, 1:31 a.m.