partial.rfsrc: Acquire Partial Effect of a Variable

In ehrlinger/randomForestSRC: Random Forests for Survival, Regression and Classification (RF-SRC)

Description

Acquire the partial effect of a variable on the ensembles.

Usage

partial.rfsrc(object, outcome.target = NULL,
  partial.type = NULL, partial.xvar = NULL, partial.values = NULL,
  partial.time = NULL, oob = TRUE, seed = NULL, do.trace = FALSE, ...)

Arguments

object	An object of class (rfsrc, grow).
outcome.target	Character value for multivariate families specifying the target outcome to be used. The default is to use the first coordinate.
partial.type	Character value of the type of predicted value. See details below.
partial.xvar	Character value specifying the x-variable to be used.
partial.values	Values for x-variable on which the partial values are to be calculated.
partial.time	For survival families, the time at which the predicted survival value is evaluated at (depends on partial.type).
oob	OOB (TRUE) or in-bag (FALSE) predicted values.
seed	Negative integer specifying seed for the random number generator.
do.trace	Number of seconds between updates to the user on approximate time to completion.
...	Further arguments passed to or from other methods.

Details

1. For regression, the predicted response is used.

2. For survival, the choices are:

   • Relative frequency of mortality (rel.freq) or mortality (mort) is of dim [n] x [length(partial.values)].

   • The cumulative hazard function (chf) is of dim [n] x [length(partial.time)] x [length(partial.values)].

   • The survival function (surv) is of dim [n] x [length(partial.time)] x [length(partial.values)].

3. For competing risks, the choices are:

   • The expected number of life years lost (years.lost) is of dim [n] x [length(event.info$event.type)] x [length(partial.values)].

   • The cumulative incidence function (cif) is of dim [n] x [length(partial.time)] x [length(event.info$event.type)] x [length(partial.values)].

   • The cumulative hazard function (chf) is of dim [n] x [length(partial.time)] x [length(event.info$event.type)] x [length(partial.values)].

4. For regression, it is of dim [n] x [length(partial.values)].

5. For classification, it is of dim [n] x [1 + yvar.nlevels[.]] x [length(partial.values)].

Author(s)

Hemant Ishwaran and Udaya B. Kogalur

References

Ishwaran H., Kogalur U.B. (2007). Random survival forests for R, Rnews, 7(2):25-31.

Ishwaran H., Kogalur U.B., Blackstone E.H. and Lauer M.S. (2008). Random survival forests, Ann. App. Statist., 2:841-860.

Ishwaran H., Gerds T.A., Kogalur U.B., Moore R.D., Gange S.J. and Lau B.M. (2014). Random survival forests for competing risks. Biostatistics, 15(4):757-773.

See Also

plot.variable.rfsrc

Examples

## Not run: 
## ------------------------------------------------------------
## survival/competing risk
## ------------------------------------------------------------

## survival
data(veteran, package = "randomForestSRC")
v.obj <- rfsrc(Surv(time,status)~., veteran, nsplit = 10, ntree = 100)
partial.obj <- partial.rfsrc(v.obj,
  partial.type = "rel.freq",
  partial.xvar = "age",
  partial.values = v.obj$xvar[, "age"],
  partial.time = v.obj$time.interest)

## competing risks
data(follic, package = "randomForestSRC")
follic.obj <- rfsrc(Surv(time, status) ~ ., follic, nsplit = 3, ntree = 100)
partial.obj <- partial.rfsrc(follic.obj,
  partial.type = "cif",
  partial.xvar = "age",
  partial.values = follic.obj$xvar[, "age"],
  partial.time = follic.obj$time.interest,
  oob = TRUE)

## regression
airq.obj <- rfsrc(Ozone ~ ., data = airquality)
partial.obj <- partial.rfsrc(airq.obj,
  partial.xvar = "Wind",
  partial.values = airq.obj$xvar[, "Wind"],
  oob = FALSE)

## classification
iris.obj <- rfsrc(Species ~., data = iris)
partial.obj <- partial.rfsrc(iris.obj,
  partial.xvar = "Sepal.Length",
  partial.values = iris.obj$xvar[, "Sepal.Length"])

## multivariate mixed outcomes
mtcars2 <- mtcars
mtcars2$carb <- factor(mtcars2$carb)
mtcars2$cyl <- factor(mtcars2$cyl)
mtcars.mix <- rfsrc(Multivar(carb, mpg, cyl) ~ ., data = mtcars2)
partial.obj <- partial.rfsrc(mtcars.mix,
  partial.xvar = "disp",
  partial.values = mtcars.mix$xvar[, "disp"])

## End(Not run)

ehrlinger/randomForestSRC documentation built on May 16, 2019, 1:20 a.m.