We generated Gaussian data with N observations and p predictors, with each pair of predictors Xj, Xj′ having the same population correlation ρ. We tried a number of combinations of N and p, with ρ varying from zero to 0.95. The outcome values were generated by (31)Y=∑j=1pXjβj+k·Z where βj = (−1)j exp(−2(j − 1)/20), Z ~ N (0, 1) and k is chosen so that the signal-to-noise ratio is 3.0. The coefficients are constructed to have alternating signs and to be exponentially decreasing.
