Warning message: In trellis.par.spostscript 2 postscript 2 Analysis of Variance Table Model 1: best ~ (comm.strat + miLoading required package: grid Loading required package: mvtnorm x.cpu)^2 Res.Df RSS Df Sum of Sq F Pr(>F) 1 464 0.59040 2 467 0.59245 -3 -0.00206 0.5388 0.6559 Call: aov(formula = best ~ (comm.strat + migr.freq + max.cpu)^2, data = BestDF) Residuals: Min 1Q Median 3Q Max -0.1073847 -0.0246167 -0.0007395 0.0233175 0.0912512 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.1813191 0.0016257 111.531 < 2e-16 *** comm.strat1 -0.0021385 0.0022991 -0.930 0.35278 comm.strat2 -0.0017794 0.0013274 -1.341 0.18073 comm.strat3 0.0036406 0.0009386 3.879 0.00012 *** migr.freq1 -0.0036231 0.0016257 -2.229 0.02632 * max.cpu1 -0.0106959 0.0016257 -6.579 1.27e-10 *** comm.strat1:migr.freq1 -0.0021522 0.0022991 -0.936 0.34971 comm.strat2:migr.freq1 0.0027197 0.0013274 2.049 0.04103 * comm.strat3:migr.freq1 0.0014603 0.0009386 1.556 0.12044 comm.strat1:max.cpu1 -0.0039369 0.0022991 -1.712 0.08749 . comm.strat2:max.cpu1 -0.0004831 0.0013274 -0.364 0.71607 comm.strat3:max.cpu1 0.0011370 0.0009386 1.211 0.22639 migr.freq1:max.cpu1 0.0006790 0.0016257 0.418 0.67640 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.03562 on 467 degrees of freedom Multiple R-Squared: 0.1434, Adjusted R-squared: 0.1214 F-statistic: 6.513 on 12 and 467 DF, p-value: 8.648e-11 Df Sum Sq Mean Sq F value Pr(>F) comm.strat 3 0.02246 0.00749 5.9022 0.0005854 *** migr.freq 1 0.00630 0.00630 4.9667 0.0263150 * max.cpu 1 0.05491 0.05491 43.2851 1.272e-10 *** comm.strat:migr.freq 3 0.00951 0.00317 2.4982 0.0590374 . comm.strat:max.cpu 3 0.00575 0.00192 1.5106 0.2109683 migr.freq:max.cpu 1 0.00022 0.00022 0.1744 0.6763985 Residuals 467 0.59245 0.00127 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Tables of means Grand mean 0.1813191 comm.strat comm.strat FC HC R RW 0.1816 0.1773 0.1741 0.1922 migr.freq migr.freq fixed increasing 0.1849 0.1777 max.cpu max.cpu 4 8 0.1920 0.1706 comm.strat:migr.freq migr.freq comm.strat fixed increasing FC 0.1872 0.1759 HC 0.1873 0.1674 R 0.1738 0.1745 RW 0.1915 0.1930 comm.strat:max.cpu max.cpu comm.strat 4 8 FC 0.1890 0.1742 HC 0.1926 0.1620 R 0.1869 0.1613 RW 0.1995 0.1850 migr.freq:max.cpu max.cpu migr.freq 4 8 fixed 0.1963 0.1736 increasing 0.1877 0.1677 Standard errors for differences of means comm.strat migr.freq max.cpu comm.strat:migr.freq comm.strat:max.cpu 0.00460 0.00325 0.00325 0.00650 0.00650 replic. 120 240 240 60 60 migr.freq:max.cpu 0.00460 replic. 120 Tables of effects comm.strat comm.strat FC HC R RW 0.00028 -0.00400 -0.00720 0.01092 migr.freq migr.freq fixed increasing 0.00362 -0.00362 max.cpu max.cpu 4 8 0.0107 -0.0107 comm.strat:migr.freq migr.freq comm.strat fixed increasing FC 0.00203 -0.00203 HC 0.00633 -0.00633 R -0.00398 0.00398 RW -0.00438 0.00438 comm.strat:max.cpu max.cpu comm.strat 4 8 FC -0.00328 0.00328 HC 0.00459 -0.00459 R 0.00210 -0.00210 RW -0.00341 0.00341 migr.freq:max.cpu max.cpu migr.freq 4 8 fixed 0.000679 -0.000679 increasing -0.000679 0.000679 Standard errors of effects comm.strat migr.freq max.cpu comm.strat:migr.freq comm.strat:max.cpu 0.00325 0.00230 0.00230 0.00460 0.00460 replic. 120 240 240 60 60 migr.freq:max.cpu 0.00325 replic. 120 postscript 2 postscript 2 Tukey multiple comparisons of means 95% family-wise confidence level Fit: aov(formula = best ~ (comm.strat + migr.freq + max.cpu)^2, data = BestDF) $comm.strat diff lwr upr p adj HC-FC -0.004276992 -0.016132703 0.007578719 0.7886941 R-FC -0.007476748 -0.019332459 0.004378963 0.3649452 RW-FC 0.010644552 -0.001211159 0.022500263 0.0960892 R-HC -0.003199756 -0.015055467 0.008655955 0.8986560 RW-HC 0.014921544 0.003065833 0.026777255 0.0068768 RW-R 0.018121300 0.006265589 0.029977011 0.0005410 $migr.freq diff lwr upr p adj increasing-fixed -0.007246238 -0.01363554 -0.0008569355 0.026315 $max.cpu diff lwr upr p adj 8-4 -0.02139181 -0.02778111 -0.01500250 0 $`comm.strat:migr.freq` diff lwr upr p adj HC:fixed-FC:fixed 2.738736e-05 -0.0197722093 1.982698e-02 1.0000000 R:fixed-FC:fixed -1.348371e-02 -0.0332833049 6.315889e-03 0.4337429 RW:fixed-FC:fixed 4.235911e-03 -0.0155636857 2.403551e-02 0.9980851 FC:increasing-FC:fixed -1.130185e-02 -0.0311014455 8.497748e-03 0.6622811 HC:increasing-FC:fixed -1.988322e-02 -0.0396828170 -8.362362e-05 0.0481755 R:increasing-FC:fixed -1.277164e-02 -0.0325712336 7.027960e-03 0.5075217 RW:increasing-FC:fixed 5.751345e-03 -0.0140482520 2.555094e-02 0.9873620 R:fixed-HC:fixed -1.351110e-02 -0.0333106922 6.288501e-03 0.4309720 RW:fixed-HC:fixed 4.208524e-03 -0.0155910730 2.400812e-02 0.9981629 FC:increasing-HC:fixed -1.132924e-02 -0.0311288329 8.470361e-03 0.6594723 HC:increasing-HC:fixed -1.991061e-02 -0.0397102044 -1.110110e-04 0.0475904 R:increasing-HC:fixed -1.279902e-02 -0.0325986210 7.000572e-03 0.5046364 RW:increasing-HC:fixed 5.723957e-03 -0.0140756393 2.552355e-02 0.9877135 RW:fixed-R:fixed 1.771962e-02 -0.0020799775 3.751922e-02 0.1177180 FC:increasing-R:fixed 2.181859e-03 -0.0176177373 2.198146e-02 0.9999769 HC:increasing-R:fixed -6.399512e-03 -0.0261991088 1.340008e-02 0.9765530 R:increasing-R:fixed 7.120713e-04 -0.0190875254 2.051167e-02 1.0000000 RW:increasing-R:fixed 1.923505e-02 -0.0005645438 3.903465e-02 0.0639131 FC:increasing-RW:fixed -1.553776e-02 -0.0353373566 4.261837e-03 0.2489654 HC:increasing-RW:fixed -2.411913e-02 -0.0439187280 -4.319535e-03 0.0056714 R:increasing-RW:fixed -1.700755e-02 -0.0368071446 2.792049e-03 0.1529511 RW:increasing-RW:fixed 1.515434e-03 -0.0182841630 2.131503e-02 0.9999981 HC:increasing-FC:increasing -8.581371e-03 -0.0283809682 1.121823e-02 0.8912039 R:increasing-FC:increasing -1.469788e-03 -0.0212693848 1.832981e-02 0.9999985 RW:increasing-FC:increasing 1.705319e-02 -0.0027464031 3.685279e-02 0.1504800 R:increasing-HC:increasing 7.111583e-03 -0.0126880133 2.691118e-02 0.9580091 RW:increasing-HC:increasing 2.563457e-02 0.0058349683 4.543416e-02 0.0023535 RW:increasing-R:increasing 1.852298e-02 -0.0012766151 3.832258e-02 0.0859196 $`comm.strat:max.cpu` diff lwr upr p adj HC:4-FC:4 0.0035968727 -0.016202724 0.023396469 0.9993362 R:4-FC:4 -0.0020905682 -0.021890165 0.017709029 0.9999828 RW:4-FC:4 0.0105167446 -0.009282852 0.030316341 0.7397796 FC:8-FC:4 -0.0148256886 -0.034625285 0.004973908 0.3069541 HC:8-FC:4 -0.0269765455 -0.046776142 -0.007176949 0.0010310 R:8-FC:4 -0.0276886167 -0.047488213 -0.007889020 0.0006540 RW:8-FC:4 -0.0040533287 -0.023852925 0.015746268 0.9985567 R:4-HC:4 -0.0056874409 -0.025487038 0.014112156 0.9881704 RW:4-HC:4 0.0069198719 -0.012879725 0.026719469 0.9637854 FC:8-HC:4 -0.0184225613 -0.038222158 0.001377035 0.0894681 HC:8-HC:4 -0.0305734182 -0.050373015 -0.010773822 0.0000921 R:8-HC:4 -0.0312854894 -0.051085086 -0.011485893 0.0000552 RW:8-HC:4 -0.0076502014 -0.027449798 0.012149395 0.9383367 RW:4-R:4 0.0126073128 -0.007192284 0.032406909 0.5248829 FC:8-R:4 -0.0127351204 -0.032534717 0.007064476 0.5113728 HC:8-R:4 -0.0248859773 -0.044685574 -0.005086381 0.0036600 R:8-R:4 -0.0255980486 -0.045397645 -0.005798452 0.0024055 RW:8-R:4 -0.0019627605 -0.021762357 0.017836836 0.9999888 FC:8-RW:4 -0.0253424332 -0.045142030 -0.005542837 0.0028006 HC:8-RW:4 -0.0374932901 -0.057292887 -0.017693693 0.0000004 R:8-RW:4 -0.0382053613 -0.058004958 -0.018405765 0.0000002 RW:8-RW:4 -0.0145700733 -0.034369670 0.005229523 0.3294798 HC:8-FC:8 -0.0121508569 -0.031950454 0.007648740 0.5733318 R:8-FC:8 -0.0128629281 -0.032662525 0.006936669 0.4979148 RW:8-FC:8 0.0107723600 -0.009027237 0.030571957 0.7152796 R:8-HC:8 -0.0007120713 -0.020511668 0.019087525 1.0000000 RW:8-HC:8 0.0229232168 0.003123620 0.042722814 0.0108974 RW:8-R:8 0.0236352881 0.003835691 0.043434885 0.0074195 $`migr.freq:max.cpu` diff lwr upr p adj increasing:4-fixed:4 -0.008604194 -0.02045991 0.003251517 0.2419129 fixed:8-fixed:4 -0.022749764 -0.03460547 -0.010894053 0.0000063 increasing:8-fixed:4 -0.028638045 -0.04049376 -0.016782334 0.0000000 fixed:8-increasing:4 -0.014145569 -0.02600128 -0.002289858 0.0118650 increasing:8-increasing:4 -0.020033851 -0.03188956 -0.008178140 0.0000954 increasing:8-fixed:8 -0.005888281 -0.01774399 0.005967430 0.5757970 postscript 2 Simultaneous Confidence Intervals for General Linear Hypotheses Multiple Comparisons of Means: Mean Contrasts Fit: aov(formula = best ~ (comm.strat + migr.freq + max.cpu)^2, data = BestDF) Estimated Quantile = 2.2435 Linear Hypotheses: Estimate lwr upr 4 == 0 0.1920 0.1869 0.1972 8 == 0 0.1706 0.1655 0.1758 95% family-wise confidence level Simultaneous Confidence Intervals for General Linear Hypotheses Multiple Comparisons of Means: Mean Contrasts Fit: aov(formula = best ~ (comm.strat + migr.freq + max.cpu)^2, data = BestDF) Estimated Quantile = 2.2435 Linear Hypotheses: Estimate lwr upr fixed == 0 0.1849 0.1798 0.1901 increasing == 0 0.1777 0.1725 0.1829 95% family-wise confidence level Simultaneous Confidence Intervals for General Linear Hypotheses Multiple Comparisons of Means: Mean Contrasts Fit: aov(formula = best ~ (comm.strat + migr.freq + max.cpu)^2, data = BestDF) Estimated Quantile = 2.5002 Linear Hypotheses: Estimate lwr upr FC == 0 0.1816 0.1735 0.1897 HC == 0 0.1773 0.1692 0.1854 R == 0 0.1741 0.1660 0.1822 RW == 0 0.1922 0.1841 0.2004 95% family-wise confidence level postscript 2 Test stat Pr(>|t|) comm.strat NA NA migr.freq NA NA max.cpu NA NA Tukey test -1.453756 0.1460139 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