dmlalg (version 1.0.2)

print.regsdml: Printing regsdml fits

Description

This is a method for the class regsdml. It prints objects of class regsdml, which typically result from a function call to regsdml.

Usage

# S3 method for regsdml
print(x, ...)

Arguments

x

An object of class regsdml. This object usually results from a function call to regsdml.

...

Further arguments passed to or from other methods.

Value

By default, summary(x) is called. Please see summary.regsdml for further details.

See Also

regsdml, summary.regsdml, confint.regsdml, coef.regsdml, vcov.regsdml

Examples

# NOT RUN {
## Generate some data:
set.seed(19)
# true linear parameter
beta0 <- 1
n <- 40
# observed confounder
w <- pi * runif(n, -1, 1)
# instrument
a <- 3 * tanh(2 * w) + rnorm(n, 0, 1)
# unobserved confounder
h <- 2 * sin(w) + rnorm(n, 0, 1)
# linear covariate
x <- -1 * abs(a) - h - 2 * tanh(w) + rnorm(n, 0, 1)
# response
y <- beta0 * x - 3 * cos(pi * 0.25 * h) + 0.5 * w ^ 2 + rnorm(n, 0, 1)

## Estimate the linear coefficient from x to y
## (The parameters are chosen small enough to make estimation fast):
## Caveat: A spline estimator is extrapolated, which raises a warning message.
## Extrapolation lies in the nature of our method. To omit the warning message
## resulting from the spline estimator, another estimator may be used.
fit <- regsdml(a, w, x, y,
               gamma = exp(seq(-4, 1, length.out = 4)),
               S = 3,
               do_regDML_all_gamma = TRUE,
               cond_method = c("forest",  # for E[A|W]
                               "spline",  # for E[X|W]
                               "spline"), # for E[Y|W]
               params = list(list(ntree = 1), NULL, NULL))
print(fit)
# }