TEST OF METHODS ON DATASETS GENERATED WITH SEED 1 N = 200 METHOD = nlm INITIALIZATION 1 user system elapsed 0.528 0.004 0.537 logl estimate.a estimate.b estimate.w se.a se.b se.w -421.0734 2.3404 0.0228 -18.5856 0.2524 0.0025 NaN N = 200 METHOD = nlm INITIALIZATION 2 user system elapsed 0.580 0.000 0.582 logl estimate.a estimate.b estimate.w se.a se.b se.w -421.0734 2.3404 0.0228 -19.9812 0.2524 0.0025 132.6356 N = 200 METHOD = optim INITIALIZATION 1 user system elapsed 0.664 0.000 0.666 logl estimate.a estimate.b estimate.w se.a se.b se.w -421.0734 2.3399 0.0228 -15.2588 0.2522 0.0025 524.2916 N = 200 METHOD = optim INITIALIZATION 2 user system elapsed 1.128 0.000 1.131 logl estimate.a estimate.b estimate.w se.a se.b se.w -421.0734 2.3404 0.0228 -15.0083 0.2523 0.0025 456.2840 N = 600 METHOD = nlm INITIALIZATION 1 user system elapsed 0.872 0.000 0.877 logl estimate.a estimate.b estimate.w se.a se.b se.w -1485.5336 2.3775 0.0191 -2.7053 0.1871 0.0009 0.5675 N = 600 METHOD = nlm INITIALIZATION 2 user system elapsed 0.404 0.000 0.406 logl estimate.a estimate.b estimate.w se.a se.b se.w -1486.9830 2.5235 0.0179 -2.1972 0.1928 0.0009 0.3705 N = 600 METHOD = optim INITIALIZATION 1 user system elapsed 1.940 0.000 1.947 logl estimate.a estimate.b estimate.w se.a se.b se.w -1487.3183 2.5239 0.0204 -14.9020 0.1750 0.0006 NaN N = 600 METHOD = optim INITIALIZATION 2 user system elapsed 2.468 0.000 2.477 logl estimate.a estimate.b estimate.w se.a se.b se.w -1485.5142 2.3975 0.0192 -2.8226 0.1879 0.0009 0.6301 There were 16 warnings (use warnings() to see them) RUNS OF METHODS ON 20 DATASETS seed 1 nlm a b w estimate 2.3775 0.0191 -2.7053 se 0.1871 0.0009 0.5675 seed 1 optim a b w estimate 2.5239 0.0204 -14.902 se 0.1750 0.0006 NaN seed 2 nlm a b w estimate 2.1901 0.020 -2.3139 se 0.1860 0.001 0.4708 seed 2 optim a b w estimate 2.1893 2e-02 -2.3141 se 0.1860 9e-04 0.4687 seed 3 nlm a b w estimate 2.1538 0.0221 -6.5421 se 0.1767 0.0009 18.3767 seed 3 optim a b w estimate 2.1536 0.0221 -6.5765 se 0.1771 0.0009 19.5312 seed 4 nlm a b w estimate 2.1984 0.0202 -2.5769 se 0.1831 0.0009 0.5614 seed 4 optim a b w estimate 2.1990 0.0202 -2.5787 se 0.1832 0.0009 0.5595 seed 5 nlm a b w estimate 2.1798 0.0197 -2.4233 se 0.1857 0.0010 0.5237 seed 5 optim a b w estimate 2.1789 0.0197 -2.4217 se 0.1857 0.0009 0.5209 seed 6 nlm a b w estimate 2.5556 0.0174 -2.0584 se 0.1996 0.0009 0.4083 seed 6 optim a b w estimate 2.5555 0.0174 -2.0559 se 0.1997 0.0009 0.4054 seed 7 nlm a b w estimate 2.6477 0.0205 -18.2657 se 0.1791 0.0007 44.7114 seed 7 optim a b w estimate 2.6477 0.0205 -11.2107 se 0.1790 0.0006 114.3651 seed 8 nlm a b w estimate 2.1196 0.0203 -2.7935 se 0.1816 0.0009 0.6449 seed 8 optim a b w estimate 2.1296 0.0204 -2.8679 se 0.1822 0.0009 0.6929 seed 9 nlm a b w estimate 2.3363 0.0207 -3.2821 se 0.1897 0.0009 0.9461 seed 9 optim a b w estimate 2.3362 0.0207 -3.2824 se 0.1896 0.0009 0.9419 seed 10 nlm a b w estimate 2.2084 0.0210 -3.1844 se 0.1848 0.0009 0.8292 seed 10 optim a b w estimate 2.2893 0.0219 -13.5782 se 0.1750 0.0006 NaN seed 11 nlm a b w estimate 1.9619 0.0220 -3.7862 se 0.1804 0.0009 1.4311 seed 11 optim a b w estimate 1.9620 0.0220 -3.7841 se 0.1804 0.0009 1.4272 seed 12 nlm a b w estimate 2.3218 0.0210 -17.3063 se 0.1733 0.0006 NaN seed 12 optim a b w estimate 2.3211 0.0210 -14.4530 se 0.1732 0.0006 494.3905 seed 13 nlm a b w estimate 2.3003 0.0195 -2.5829 se 0.1954 0.0010 0.6607 seed 13 optim a b w estimate 2.2214 0.0191 -2.2279 se 0.1899 0.0010 0.4767 seed 14 nlm a b w estimate 2.5603 0.0195 -4.2012 se 0.1891 0.0009 2.1350 seed 14 optim a b w estimate 2.5606 0.0195 -4.2031 se 0.1896 0.0009 2.1736 seed 15 nlm a b w estimate 2.7538 0.0202 -4.9726 se 0.1989 0.0009 4.6311 seed 15 optim a b w estimate 2.7535 0.0203 -4.9806 se 0.1983 0.0009 4.5879 seed 16 nlm a b w estimate 2.3786 0.0211 -5.2021 se 0.1853 0.0009 5.4047 seed 16 optim a b w estimate 2.3923 0.0212 -12.5232 se 0.1717 0.0006 NaN seed 17 nlm a b w estimate 2.4245 0.0205 -4.3547 se 0.1877 0.0009 2.4425 seed 17 optim a b w estimate 2.4236 0.0205 -4.3515 se 0.1880 0.0009 2.4590 seed 18 nlm a b w estimate 2.4104 0.0195 -2.9298 se 0.1932 0.0009 0.7349 seed 18 optim a b w estimate 2.4101 0.0195 -2.9267 se 0.1933 0.0009 0.7328 seed 19 nlm a b w estimate 2.6188 0.0198 -3.6862 se 0.1928 0.0009 1.2889 seed 19 optim a b w estimate 2.6183 0.0198 -3.6864 se 0.1927 0.0009 1.2859 seed 20 nlm a b w estimate 2.4210 0.0194 -2.6241 se 0.2032 0.0010 0.6766 seed 20 optim a b w estimate 2.3227 0.0190 -2.212 se 0.1965 0.0009 0.462 There were 50 or more warnings (use warnings() to see the first 50) TEST OF METHODS ON DATASETS GENERATED WITH NONLINEAR TREND N = 600 METHOD = nlm INITIALIZATION 1 logl estimate.a estimate.b estimate.w se.a se.b se.w -1522.9325 2.7855 0.0160 -1.9139 0.2053 0.0009 0.3898 N = 600 METHOD = nlm INITIALIZATION 2 logl estimate.a estimate.b estimate.w se.a se.b se.w -1523.3483 2.9624 0.0161 -2.1972 0.2095 0.0009 0.4555 N = 600 METHOD = optim INITIALIZATION 1 logl estimate.a estimate.b estimate.w se.a se.b se.w -1522.9325 2.7838 0.0160 -1.9150 0.2054 0.0009 0.3877 N = 600 METHOD = optim INITIALIZATION 2 logl estimate.a estimate.b estimate.w se.a se.b se.w -1522.9325 2.7854 0.0160 -1.9155 0.2054 0.0009 0.3874 N = 2500 METHOD = nlm INITIALIZATION 1 logl estimate.a estimate.b estimate.w se.a se.b se.w -7674.6697 2.5639 0.0209 -25.8843 0.1161 0.0001 46.8937 N = 2500 METHOD = nlm INITIALIZATION 2 logl estimate.a estimate.b estimate.w se.a se.b se.w -7659.8584 2.2837 0.0190 -2.1972 0.1206 0.0004 0.2240 N = 2500 METHOD = optim INITIALIZATION 1 logl estimate.a estimate.b estimate.w se.a se.b se.w -7659.6062 2.3570 0.0192 -2.3327 0.1219 0.0004 0.2366 N = 2500 METHOD = optim INITIALIZATION 2 logl estimate.a estimate.b estimate.w se.a se.b se.w -7659.6374 2.3590 0.0191 -2.2731 0.1220 0.0004 0.2265 There were 17 warnings (use warnings() to see them)