summary.MSE_Test: Summarizes an MSE Test object.

In tim-coleman/RFtest: Scalable and Efficient Hypothesis Tests for Random Forests

Usage

summary.MSE_Test(obj)

Author(s)

Tim Coleman

Examples

N <- 1250
Nvar <- 10
N_test <- 150
name_vec <- paste("X", 1:(2*Nvar), sep = "")

# training data:
X <- data.frame(replicate(Nvar, runif(N)),
                replicate(Nvar, cut(runif(N), 3,
                                      labels = as.character(1:3)))) 
  mutate(Y = 5*(X3) + .5*X2^2 + ifelse(X6 > 10*X1*X8*X9, 1, 0) +  rnorm(N, sd = .05))
names(X) <- c(name_vec, "Y")

# some testing data:
X.t1 <- data.frame(replicate(Nvar, runif(N_test)),
                   replicate(Nvar, cut(runif(N_test), 3,
                                       labels = as.character(1:3)))) 
  mutate(Y = 5*(X3) + .5*X2^2 + ifelse(X6 > 10*X1*X8*X9, 1, 0) +  rnorm(N_test, sd = .05))
names(X.t1) <- c(name_vec, "Y")

M_no_test <- MSE_Test(X = X 
                      base.learner = "rtree", NTest = 100, NTree = 500, B = 1000, var = c( "X5"),
                      p = .85)

summary(M_no_test)

tim-coleman/RFtest documentation built on March 10, 2020, 12:28 p.m.