num_data: Simulated Numerical Data

In causalDisco: Tools for Causal Discovery on Observational Data

Simulated Numerical Data

Description

Simulated Numerical Data

Usage

num_data

Format

A data.frame with 1000 rows and 5 variables.

X1

Structural equation: X_1 := \sqrt{Z} + \epsilon_1 with \epsilon_1 \sim \mathrm{Unif}[0, 2]

X2

Structural equation: X_2 := 2 \cdot X_3 - \epsilon_2 with \epsilon_2 \sim N(5, 1)

X3

Structural equation: X_3 := \epsilon_3 with \epsilon_3 \sim \mathrm{Unif}[5, 10]

Z

Structural equation: Z := |\epsilon_4| with \epsilon_4 \sim N(10, 1)

Y

Structural equation: Y := X_1^2 + X_2 - X_3 - Z + \epsilon_5 with \epsilon_5 \sim N(10, 1)

Details

The R code used to generate this dataset is as follows:

set.seed(1405)
n <- 1000
Z <- abs(rnorm(n, mean = 10))
X1 <- sqrt(Z) + runif(n, min = 0, max = 2)
X3 <- runif(n, min = 5, max = 10)
X2 <- 2 * X3 - rnorm(n, mean = 5)
Y  <- X1^2 + X2 - X3 - Z + rnorm(n, mean = 10)
num_data <- data.frame(X1, X2, X3, Z, Y)

Examples

data(num_data)
head(num_data)

causalDisco documentation built on April 13, 2026, 5:06 p.m.