/* NIST StRD benchmark from http://www.nist.gov/itl/div898/strd/ ANOVA Difficulty=Lower n_i=21 k=9 Generated Dataset Name: Simon-Lesage1 (Simon-Lesage1.dat) Procedure: Analysis of Variance Reference: Simon, Stephen D. and Lesage, James P. (1989). "Assessing the Accuracy of ANOVA Calculations in Statistical Software". Computational Statistics & Data Analysis, 8, pp. 325-332. Data: 1 Factor 9 Treatments 21 Replicates/Cell 189 Observations 1 Constant Leading Digit Lower Level of Difficulty Generated Data Model: 10 Parameters (mu,tau_1, ... , tau_9) y_{ij} = mu + tau_i + epsilon_{ij} Certified Values: Source of Sums of Mean Variation df Squares Squares F Statistic Between Treatment 8 1.68000000000000E+00 2.10000000000000E-01 2.1000000000E+01 Within Treatment 180 1.80000000000000E+00 1.00000000000000E-02 Certified R-Squared 4.82758620689655E-01 Certified Residual Standard Deviation 1.00000000000000E-01 */ clear scalar N = 189 scalar df_r = 180 scalar df_m = 8 scalar mss = 1.68 scalar F = 21 scalar rss = 1.8 scalar r2 = 4.82758620689655E-01 scalar rmse = 0.1 qui input byte treat double resp 1 1.4 1 1.3 1 1.5 1 1.3 1 1.5 1 1.3 1 1.5 1 1.3 1 1.5 1 1.3 1 1.5 1 1.3 1 1.5 1 1.3 1 1.5 1 1.3 1 1.5 1 1.3 1 1.5 1 1.3 1 1.5 2 1.3 2 1.2 2 1.4 2 1.2 2 1.4 2 1.2 2 1.4 2 1.2 2 1.4 2 1.2 2 1.4 2 1.2 2 1.4 2 1.2 2 1.4 2 1.2 2 1.4 2 1.2 2 1.4 2 1.2 2 1.4 3 1.5 3 1.4 3 1.6 3 1.4 3 1.6 3 1.4 3 1.6 3 1.4 3 1.6 3 1.4 3 1.6 3 1.4 3 1.6 3 1.4 3 1.6 3 1.4 3 1.6 3 1.4 3 1.6 3 1.4 3 1.6 4 1.3 4 1.2 4 1.4 4 1.2 4 1.4 4 1.2 4 1.4 4 1.2 4 1.4 4 1.2 4 1.4 4 1.2 4 1.4 4 1.2 4 1.4 4 1.2 4 1.4 4 1.2 4 1.4 4 1.2 4 1.4 5 1.5 5 1.4 5 1.6 5 1.4 5 1.6 5 1.4 5 1.6 5 1.4 5 1.6 5 1.4 5 1.6 5 1.4 5 1.6 5 1.4 5 1.6 5 1.4 5 1.6 5 1.4 5 1.6 5 1.4 5 1.6 6 1.3 6 1.2 6 1.4 6 1.2 6 1.4 6 1.2 6 1.4 6 1.2 6 1.4 6 1.2 6 1.4 6 1.2 6 1.4 6 1.2 6 1.4 6 1.2 6 1.4 6 1.2 6 1.4 6 1.2 6 1.4 7 1.5 7 1.4 7 1.6 7 1.4 7 1.6 7 1.4 7 1.6 7 1.4 7 1.6 7 1.4 7 1.6 7 1.4 7 1.6 7 1.4 7 1.6 7 1.4 7 1.6 7 1.4 7 1.6 7 1.4 7 1.6 8 1.3 8 1.2 8 1.4 8 1.2 8 1.4 8 1.2 8 1.4 8 1.2 8 1.4 8 1.2 8 1.4 8 1.2 8 1.4 8 1.2 8 1.4 8 1.2 8 1.4 8 1.2 8 1.4 8 1.2 8 1.4 9 1.5 9 1.4 9 1.6 9 1.4 9 1.6 9 1.4 9 1.6 9 1.4 9 1.6 9 1.4 9 1.6 9 1.4 9 1.6 9 1.4 9 1.6 9 1.4 9 1.6 9 1.4 9 1.6 9 1.4 9 1.6 end anova resp treat assert N == e(N) assert df_r == e(df_r) assert df_m == e(df_m) lrecomp e(F) F e(rmse) rmse e(r2) r2 e(mss) mss e(rss) rss