simdata {NeuralSens}

Simulated data to test the package functionalities

Description

data.frame with 2000 rows of 4 columns with 3 input variables X1, X2, X3 and one output variable Y. The data is already scaled, and has been generated using the following code:

set.seed(150)

simdata <- data.frame( "X1" = rnorm(2000, 0, 1), "X2" = rnorm(2000, 0, 1), "X3" = rnorm(2000, 0, 1) )

simdata$Y <- simdata$X1^2 + 0.5*simdata$X2 + 0.1*rnorm(2000, 0, 1)

Format

A data frame with 2000 rows and 4 variables:

X1

Random input 1

X2

Random input 2

X3

Random input 3

Y

Output

Author(s)

Jaime Pizarroso Gonzalo

References

Pizarroso J, Portela J, Muñoz A (2022). NeuralSens: Sensitivity Analysis of Neural Networks. Journal of Statistical Software, 102(7), 1-36.