Can't run with species=1
sdwfrost opened this issue · 0 comments
sdwfrost commented
Hi, I can fit the models with species=2, but I get an error when fitting with species=1:
> fit(data, 1) # change value of species accordingly
'giveCsparse' has been deprecated; setting 'repr = "T"' for you'giveCsparse' has been deprecated; setting 'repr = "T"' for you'giveCsparse' has been deprecated; setting 'repr = "T"' for youOptimizing tape... Done
iter: 1 value: 120738.4 mgc: 25933318 ustep: 6.32006e-08
iter: 2 value: 93791.77 mgc: 20407370 ustep: 0.0003513721
iter: 3 value: 83832.87 mgc: 12300571 ustep: 0.002374317
iter: 4 value: 78461.76 mgc: 1235087 ustep: 0.006235358
iter: 5 value: 74898.13 mgc: 506864.5 ustep: 0.02037451
iter: 6 value: 72392.62 mgc: 424459.5 ustep: 0.07415515
iter: 7 value: 71638.69 mgc: 315881.7 ustep: 0.0764032
iter: 8 value: 71199.04 mgc: 113220.6 ustep: 0.1493874
iter: 9 value: 70991.32 mgc: 119472.9 ustep: 0.386568
iter: 10 value: 70958.38 mgc: 2605.041 ustep: 0.6217838
iter: 11 value: 70944.15 mgc: 18856.29 ustep: 0.5401132
iter: 12 value: 70938.49 mgc: 42626.34 ustep: 0.2824217
iter: 13 value: 70936.19 mgc: 13399.06 ustep: 0.5314804
iter: 14 value: 70935.78 mgc: 2665.392 ustep: 0.7290542
iter: 15 value: 70935.7 mgc: 510.5333 ustep: 0.8538613
iter: 16 value: 70935.68 mgc: 255.2613 ustep: 0.9240537
iter: 17 value: 70935.67 mgc: 202.8756 ustep: 0.961281
iter: 18 value: 70935.66 mgc: 951.7742 ustep: 0.9804514
iter: 19 value: 70935.66 mgc: 23.39349 ustep: 0.9901784
iter: 20 value: 70935.66 mgc: 7.789797 ustep: 0.9950776
iter: 21 value: 70935.66 mgc: 0.0001428561 ustep: 0.997536
iter: 22 value: 70935.66 mgc: 1.465828e-06 ustep: 0.9987674
iter: 23 value: 70935.66 mgc: 1.023927e-08 ustep: 0.9993836
mgc: 1.102412e-08
iter: 1 value: 70935.66 mgc: 1.102412e-08 ustep: 1
mgc: 5.573604e-09
Matching hessian patterns... Done
outer mgc: 192466.2
iter: 1 value: 85528.9 mgc: 20614108 ustep: 0.04283358
iter: 2 value: 81923.05 mgc: 150525.4 ustep: 0.02857298
iter: 3 value: 80608.88 mgc: 208025.3 ustep: 0.1691185
iter: 4 value: 80385.07 mgc: 60254.55 ustep: 0.03255886
iter: 5 value: 79916.73 mgc: 67846.17 ustep: 0.1805227
iter: 6 value: 79690.1 mgc: 17361.79 ustep: 0.03397441
iter: 7 value: 79371.59 mgc: 39908.22 ustep: 0.1844031
iter: 8 value: 79243.68 mgc: 2998.374 ustep: 0.4294788
iter: 9 value: 79193.23 mgc: 788.8472 ustep: 0.6553808
iter: 10 value: 79186.6 mgc: 81.70586 ustep: 0.809575
iter: 11 value: 79186.34 mgc: 3.261441 ustep: 0.8997739
iter: 12 value: 79186.33 mgc: 0.3986815 ustep: 0.9485693
iter: 13 value: 79186.33 mgc: 0.007000661 ustep: 0.9739478
iter: 14 value: 79186.33 mgc: 5.344416e-05 ustep: 0.9868893
iter: 15 value: 79186.33 mgc: 7.679551e-07 ustep: 0.9934237
iter: 16 mgc: 5.544888e-09
iter: 1 value: 83261.93 mgc: 20665407 ustep: 0.009622219
iter: 2 value: 80446.42 mgc: 159881.8 ustep: 0.0981831
iter: 3 value: 79562.54 mgc: 287190.8 ustep: 0.3134105
iter: 4 value: 79393.71 mgc: 55859.92 ustep: 0.1837795
iter: 5 value: 79330.98 mgc: 6930.505 ustep: 0.06757699
iter: 6 value: 79258 mgc: 345.7816 ustep: 0.2600298
iter: 7 value: 79205.08 mgc: 407.701 ustep: 0.5099801
iter: 8 value: 79190.15 mgc: 151.6659 ustep: 0.7141575
iter: 9 value: 79188.66 mgc: 13.79713 ustep: 0.8450939
iter: 10 value: 79188.37 mgc: 33.76395 ustep: 0.32135
iter: 11 value: 79187.58 mgc: 23.50793 ustep: 0.1781719
iter: 12 value: 79183.91 mgc: 49.83973 ustep: 0.1204292
iter: 13 value: 79172.57 mgc: 245.4495 ustep: 0.1010767
iter: 14 value: 79158.48 mgc: 1105.496 ustep: 0.3179938
iter: 15 value: 79156.69 mgc: 361.2397 ustep: 0.563953
iter: 16 value: 79156.67 mgc: 69.51507 ustep: 0.750993
iter: 17 value: 79156.67 mgc: 0.8365497 ustep: 0.8666118
iter: 18 value: 79156.66 mgc: 0.2542306 ustep: 0.9309268
iter: 19 value: 79156.66 mgc: 0.1553624 ustep: 0.964849
iter: 20 value: 79156.66 mgc: 0.07624108 ustep: 0.982269
iter: 21 value: 79156.66 mgc: 0.03346308 ustep: 0.9910958
iter: 22 value: 79156.66 mgc: 0.01474646 ustep: 0.9955384
iter: 23 value: 79156.66 mgc: 0.008520357 ustep: 0.9977669
iter: 24 value: 79156.66 mgc: 0.02426632 ustep: 0.966481
iter: 25 value: 79156.66 mgc: 0.04175595 ustep: 0.8699104
iter: 26 value: 79156.66 mgc: 0.0148733 ustep: 0.740497
iter: 27 value: 79156.66 mgc: 0.005411242 ustep: 0.8605353
Not improving much - will try early exit...PD hess?: TRUE
mgc: 0.158946
iter: 1 value: 83261.93 mgc: 20665407 ustep: 0.009622219
iter: 2 value: 80446.42 mgc: 159881.8 ustep: 0.0981831
iter: 3 value: 79562.54 mgc: 287190.8 ustep: 0.3134105
iter: 4 value: 79393.71 mgc: 55859.92 ustep: 0.1837795
iter: 5 value: 79330.98 mgc: 6930.505 ustep: 0.06757699
iter: 6 value: 79258 mgc: 345.7816 ustep: 0.2600298
iter: 7 value: 79205.08 mgc: 407.701 ustep: 0.5099801
iter: 8 value: 79190.15 mgc: 151.6659 ustep: 0.7141575
iter: 9 value: 79188.66 mgc: 13.79713 ustep: 0.8450939
iter: 10 value: 79188.37 mgc: 33.76395 ustep: 0.32135
iter: 11 value: 79187.58 mgc: 23.50793 ustep: 0.1781719
iter: 12 value: 79183.91 mgc: 49.83973 ustep: 0.1204292
iter: 13 value: 79172.57 mgc: 245.4495 ustep: 0.1010767
iter: 14 value: 79158.48 mgc: 1105.496 ustep: 0.3179938
iter: 15 value: 79156.69 mgc: 361.2397 ustep: 0.563953
iter: 16 value: 79156.67 mgc: 69.51507 ustep: 0.750993
iter: 17 value: 79156.67 mgc: 0.8365497 ustep: 0.8666118
iter: 18 value: 79156.66 mgc: 0.2542306 ustep: 0.9309268
iter: 19 value: 79156.66 mgc: 0.1553624 ustep: 0.964849
iter: 20 value: 79156.66 mgc: 0.07624108 ustep: 0.982269
iter: 21 value: 79156.66 mgc: 0.03346308 ustep: 0.9910958
iter: 22 value: 79156.66 mgc: 0.01474646 ustep: 0.9955384
iter: 23 value: 79156.66 mgc: 0.008520357 ustep: 0.9977669
iter: 24 value: 79156.66 mgc: 0.02426632 ustep: 0.966481
iter: 25 value: 79156.66 mgc: 0.04175595 ustep: 0.8699104
iter: 26 value: 79156.66 mgc: 0.0148733 ustep: 0.740497
iter: 27 value: 79156.66 mgc: 0.005411242 ustep: 0.8605353
Not improving much - will try early exit...PD hess?: TRUE
mgc: 0.158946
outer mgc: NaN
Error in (function (start, objective, gradient = NULL, hessian = NULL, :
NA/NaN gradient evaluation
Timing stopped at: 352.6 7.226 360.1