The regression problem Friedman 3 as described in Friedman (1991) and Breiman (1996). Inputs are 4 independent variables uniformly distributed over the ranges $$0 \le x1 \le 100$$ $$40 \pi \le x2 \le 560 \pi$$ $$0 \le x3 \le 1$$ $$1 \le x4 \le 11$$ The outputs are created according to the formula $$\mbox{atan}((x2 x3 - (1/(x2 x4)))/x1) + e$$ where e is \(N(0,sd^2)\).
Usage
sim.Friedman3(n, sd=0.1)
Value
Returns a list with components
- x
input values (independent variables)
- y
output values (dependent variable)
References
Breiman, Leo (1996) Bagging predictors. Machine Learning 24,
pages 123-140.
Friedman, Jerome H. (1991) Multivariate adaptive regression
splines. The Annals of Statistics 19 (1), pages 1-67.
See also
Other bark deprecated functions:
bark-deprecated
,
bark-package-deprecated
,
sim.Circle-deprecated
,
sim.Friedman1-deprecated
,
sim.Friedman2-deprecated
Examples
if (FALSE) { # \dontrun{
sim.Friedman3(n=100, sd=0.1)
} # }