## Not run:
# ##regression example
#
# ##generate Friedman data i.e. a nonlinear response model
# set.seed(11)
# n = 200
# p = 5
# X = data.frame(matrix(runif(n * p), ncol = p))
# y = 10 * sin(pi* X[ ,1] * X[,2]) +20 * (X[,3] -.5)^2 + 10 * X[ ,4] + 5 * X[,5] + rnorm(n)
#
# ##now test if there is a nonlinear relationship between X1, ..., X5 and y.
# linearity_test(X = X, y = y)
# ## note the plot and the printed p-value.. should be approx 0
#
# #generate a linear response model
# y = 1 * X[ ,1] + 3 * X[,2] + 5 * X[,3] + 7 * X[ ,4] + 9 * X[,5] + rnorm(n)
# linearity_test(X = X, y = y)
# ## note the plot and the printed p-value.. should be > 0.05
#
# ## End(Not run)
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