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Update MBNMA to obtain deviance contributions or fitted values

Usage

mb.update(
  mbnma,
  param = "theta",
  n.iter = mbnma$BUGSoutput$n.iter,
  n.thin = mbnma$BUGSoutput$n.thin
)

Arguments

mbnma

An S3 object of class "mbnma" generated by running a time-course MBNMA model

param

A character object that represents the parameter within the model to monitor when updating. Can currently only be used for monitoring fitted values and deviance contributions and so can take either "dev" (for deviance contributions), "resdev" (for residual deviance contributions) or "theta" (for fitted values).

n.iter

The number of iterations to update the model whilst monitoring additional parameters (if necessary). Must be a positive integer. Default is the value used in mbnma.

n.thin

The thinning rate. Must be a positive integer. Default is the value used in mbnma.

Value

A data frame containing posterior means for the specified param at each observation, arm and study.

Examples

# \donttest{
# Using the alogliptin dataset
network <- mb.network(alog_pcfb)
#> Reference treatment is `placebo`
#> Studies reporting change from baseline automatically identified from the data

# Run Emax model
emax <- mb.run(network, fun=temax())
#> 'et50' parameters must take positive values.
#>  Default half-normal prior restricts posterior to positive values.
#> Compiling model graph
#>    Resolving undeclared variables
#>    Allocating nodes
#> Graph information:
#>    Observed stochastic nodes: 233
#>    Unobserved stochastic nodes: 38
#>    Total graph size: 4166
#> 
#> Initializing model
#> 

# Update model for 500 iterations to monitor fitted values
mb.update(emax, param="theta", n.iter=500)
#>     study arm fup         mean
#> 1       1   1   1 -0.014948348
#> 2       2   1   1 -0.036385500
#> 3       3   1   1 -0.471122124
#> 4       4   1   1 -0.005961700
#> 5       5   1   1 -0.087472839
#> 6       6   1   1 -0.032419703
#> 7       7   1   1 -0.102720954
#> 8       8   1   1 -0.009877440
#> 9       9   1   1 -0.098446060
#> 10     10   1   1  0.055079540
#> 11     11   1   1 -0.045635786
#> 12     12   1   1  0.038037062
#> 13     13   1   1 -0.767154599
#> 14     14   1   1 -0.721324218
#> 15      1   2   1 -0.225191820
#> 16      2   2   1 -0.155898459
#> 17      3   2   1 -0.672814547
#> 18      4   2   1 -0.363020316
#> 19      5   2   1 -0.415659783
#> 20      6   2   1 -0.352128176
#> 21      7   2   1 -0.507599034
#> 22      8   2   1 -0.385253138
#> 23      9   2   1 -0.259431165
#> 24     10   2   1 -0.188015413
#> 25     11   2   1 -0.250874631
#> 26     12   2   1 -0.167789238
#> 27     13   2   1 -0.828190344
#> 28     14   2   1 -0.786362332
#> 29      1   3   1 -0.274263365
#> 30      2   3   1 -0.212202048
#> 31      3   3   1 -0.758131963
#> 32      4   3   1 -0.392852325
#> 33      5   3   1 -0.443655550
#> 34      6   3   1 -0.378908643
#> 35      7   3   1 -0.542808000
#> 36      8   3   1 -0.416782499
#> 37      9   3   1 -0.273637950
#> 38     10   3   1 -0.208044359
#> 39     11   3   1 -0.268721016
#> 40     12   3   1 -0.184723028
#> 43      1   4   1 -0.295282819
#> 44      2   4   1 -0.227202482
#> 45      3   4   1 -0.850969882
#> 57      1   5   1 -0.328547967
#> 58      2   5   1 -0.224009443
#> 71      1   6   1 -0.281564984
#> 85      1   1   2 -0.029016768
#> 86      2   1   2 -0.059554642
#> 87      3   1   2 -0.474679136
#> 88      4   1   2 -0.008545790
#> 89      5   1   2 -0.123328200
#> 90      6   1   2 -0.046357787
#> 91      7   1   2 -0.134761822
#> 92      8   1   2 -0.013677249
#> 93      9   1   2 -0.162848336
#> 94     10   1   2  0.083897304
#> 95     11   1   2 -0.072225829
#> 96     12   1   2  0.060180492
#> 97     13   1   2 -0.800956499
#> 98     14   1   2 -0.738304126
#> 99      1   2   2 -0.354851325
#> 100     2   2   2 -0.267371955
#> 101     3   2   2 -0.632613036
#> 102     4   2   2 -0.507986912
#> 103     5   2   2 -0.594092473
#> 104     6   2   2 -0.508168468
#> 105     7   2   2 -0.679490034
#> 106     8   2   2 -0.530870509
#> 107     9   2   2 -0.432727412
#> 108    10   2   2 -0.292127716
#> 109    11   2   2 -0.401508191
#> 110    12   2   2 -0.269705852
#> 111    13   2   2 -0.863345357
#> 112    14   2   2 -0.803353459
#> 113     1   3   2 -0.417989374
#> 114     2   3   2 -0.349752868
#> 115     3   3   2 -0.711684826
#> 116     4   3   2 -0.548933328
#> 117     5   3   2 -0.633299222
#> 118     6   3   2 -0.546110155
#> 119     7   3   2 -0.725253332
#> 120     8   3   2 -0.573385201
#> 121     9   3   2 -0.456076802
#> 122    10   3   2 -0.322782641
#> 123    11   3   2 -0.429523075
#> 124    12   3   2 -0.296577501
#> 127     1   4   2 -0.449292558
#> 128     2   4   2 -0.374138826
#> 129     3   4   2 -0.845617241
#> 141     1   5   2 -0.512209995
#> 142     2   5   2 -0.381587558
#> 155     1   6   2 -0.525897571
#> 170     2   1   3 -0.087433030
#> 171     3   1   3 -0.476866070
#> 172     4   1   3 -0.009983396
#> 173     5   1   3 -0.142902725
#> 174     6   1   3 -0.054139107
#> 175     7   1   3 -0.150505066
#> 176     8   1   3 -0.015692190
#> 177     9   1   3 -0.242131310
#> 178    10   1   3  0.113725432
#> 179    11   1   3 -0.101995906
#> 180    12   1   3  0.084949468
#> 181    13   1   3 -0.819208278
#> 182    14   1   3 -0.747202922
#> 184     2   2   3 -0.416407994
#> 185     3   2   3 -0.611107778
#> 186     4   2   3 -0.586274027
#> 187     5   2   3 -0.693523786
#> 188     6   2   3 -0.596472726
#> 189     7   2   3 -0.766323642
#> 190     8   2   3 -0.607667418
#> 191     9   2   3 -0.649946103
#> 192    10   2   3 -0.404240350
#> 193    11   2   3 -0.574026170
#> 194    12   2   3 -0.387532036
#> 195    13   2   3 -0.882283207
#> 196    14   2   3 -0.812266831
#> 198     2   3   3 -0.517751055
#> 199     3   3   3 -0.686893515
#> 200     4   3   3 -0.633018357
#> 201     5   3   3 -0.738754746
#> 202     6   3   3 -0.640542487
#> 203     7   3   3 -0.817148743
#> 204     8   3   3 -0.655762344
#> 205     9   3   3 -0.684357136
#> 206    10   3   3 -0.445950723
#> 207    11   3   3 -0.613204494
#> 208    12   3   3 -0.425571077
#> 212     2   4   3 -0.553242087
#> 213     3   4   3 -0.842844416
#> 226     2   5   3 -0.588903405
#> 254     2   1   4 -0.103633793
#> 255     3   1   4 -0.478347105
#> 256     4   1   4 -0.010898541
#> 257     5   1   4 -0.155243199
#> 258     6   1   4 -0.059109817
#> 259     7   1   4 -0.159876282
#> 260     8   1   4 -0.016941294
#> 261     9   1   4 -0.289112841
#> 262    10   1   4  0.129061254
#> 263    11   1   4 -0.118281315
#> 264    12   1   4  0.098487338
#> 265    13   1   4 -0.830638609
#> 266    14   1   4 -0.752682267
#> 268     2   2   4 -0.511616146
#> 269     3   2   4 -0.597702282
#> 270     4   2   4 -0.635332417
#> 271     5   2   4 -0.756952191
#> 272     6   2   4 -0.653325293
#> 273     7   2   4 -0.818760698
#> 274     8   2   4 -0.655148487
#> 275     9   2   4 -0.780688411
#> 276    10   2   4 -0.463664947
#> 277    11   2   4 -0.670127664
#> 278    12   2   4 -0.453687553
#> 279    13   2   4 -0.894126952
#> 280    14   2   4 -0.817757626
#> 282     2   3   4 -0.616625665
#> 283     3   3   4 -0.671458179
#> 284     4   3   4 -0.685634787
#> 285     5   3   4 -0.805940104
#> 286     6   3   4 -0.701268994
#> 287     7   3   4 -0.872553785
#> 288     8   3   4 -0.706618037
#> 289     9   3   4 -0.821541114
#> 290    10   3   4 -0.511067568
#> 291    11   3   4 -0.715307931
#> 292    12   3   4 -0.497847176
#> 296     2   4   4 -0.658468295
#> 297     3   4   4 -0.841172643
#> 310     2   5   4 -0.719340800
#> 339     3   1   5 -0.479416670
#> 340     4   1   5 -0.011532170
#> 341     5   1   5 -0.163736909
#> 342     6   1   5 -0.062561077
#> 343     7   1   5 -0.166095659
#> 344     8   1   5 -0.018656551
#> 349    13   1   5 -0.838470850
#> 350    14   1   5 -0.756395861
#> 353     3   2   5 -0.588541907
#> 354     4   2   5 -0.668968640
#> 355     5   2   5 -0.800945915
#> 356     6   2   5 -0.693002118
#> 357     7   2   5 -0.853871885
#> 358     8   2   5 -0.720206204
#> 363    13   2   5 -0.902235156
#> 364    14   2   5 -0.821479928
#> 367     3   3   5 -0.660918755
#> 368     4   3   5 -0.721676472
#> 369     5   3   5 -0.852499570
#> 370     6   3   5 -0.743616329
#> 371     7   3   5 -0.909614691
#> 372     8   3   5 -0.776204075
#> 381     3   4   5 -0.840063629
#> 423     3   1   6 -0.480225386
#> 424     4   1   6 -0.012185629
#> 425     5   1   6 -0.172455392
#> 426     6   1   6 -0.066129631
#> 427     7   1   6 -0.172294205
#> 433    13   1   6 -0.844173335
#> 434    14   1   6 -0.759078932
#> 437     3   2   6 -0.581884556
#> 438     4   2   6 -0.703387154
#> 439     5   2   6 -0.846391930
#> 440     6   2   6 -0.734202126
#> 441     7   2   6 -0.889112984
#> 447    13   2   6 -0.908134791
#> 448    14   2   6 -0.824169726
#> 451     3   3   6 -0.653263187
#> 452     4   3   6 -0.758527351
#> 453     5   3   6 -0.900561081
#> 454     6   3   6 -0.787560632
#> 455     7   3   6 -0.946782234
#> 465     3   4   6 -0.839277948
#> 507     3   1   7 -0.480858333
#> 517    13   1   7 -0.848510961
#> 518    14   1   7 -0.761108224
#> 521     3   2   7 -0.576827124
#> 531    13   2   7 -0.912620236
#> 532    14   2   7 -0.826204332
#> 535     3   3   7 -0.647449669
#> 549     3   4   7 -0.838693998
#> 591     3   1   8 -0.481367212
#> 601    13   1   8 -0.851921442
#> 602    14   1   8 -0.762696769
#> 605     3   2   8 -0.572854500
#> 615    13   2   8 -0.916145636
#> 616    14   2   8 -0.827797165
#> 619     3   3   8 -0.642884480
#> 633     3   4   8 -0.838243860
#> 685    13   1   9 -0.854673377
#> 699    13   2   9 -0.918989457

# Update model for 500 iterations to monitor residual deviance contributions
mb.update(emax, param="resdev", n.iter=500)
#>     study arm fup        mean
#> 1       1   1   1  0.50554476
#> 2       2   1   1  2.99137825
#> 3       3   1   1  1.27988319
#> 4       4   1   1  4.12908910
#> 5       5   1   1  1.64239372
#> 6       6   1   1  2.40451936
#> 7       7   1   1 12.15127712
#> 8       8   1   1 16.57718243
#> 9       9   1   1 11.79641001
#> 10     10   1   1  0.80937250
#> 11     11   1   1  3.11049052
#> 12     12   1   1  1.47443743
#> 13     13   1   1  2.91038777
#> 14     14   1   1  2.50645038
#> 15      1   2   1  1.32039121
#> 16      2   2   1  0.26398613
#> 17      3   2   1  0.48200224
#> 18      4   2   1  0.34308065
#> 19      5   2   1  0.58236409
#> 20      6   2   1  0.33740357
#> 21      7   2   1  0.97062320
#> 22      8   2   1  0.64780124
#> 23      9   2   1  7.72904826
#> 24     10   2   1  8.32052859
#> 25     11   2   1 13.14300812
#> 26     12   2   1  3.66263746
#> 27     13   2   1  1.17451069
#> 28     14   2   1  3.57756642
#> 29      1   3   1  0.78311721
#> 30      2   3   1  4.21824080
#> 31      3   3   1  0.53310469
#> 32      4   3   1  2.89257819
#> 33      5   3   1  0.39686535
#> 34      6   3   1  0.81587716
#> 35      7   3   1  1.08469256
#> 36      8   3   1  2.65861372
#> 37      9   3   1 13.60593638
#> 38     10   3   1 15.31997782
#> 39     11   3   1  9.34807411
#> 40     12   3   1 13.31478440
#> 43      1   4   1  0.69574310
#> 44      2   4   1 10.54433353
#> 45      3   4   1  0.53114101
#> 57      1   5   1  0.20165100
#> 58      2   5   1 13.44663563
#> 71      1   6   1  0.38187180
#> 85      1   1   2  0.47262867
#> 86      2   1   2  1.75899549
#> 87      3   1   2  1.46685849
#> 88      4   1   2  2.96365345
#> 89      5   1   2  0.96344272
#> 90      6   1   2  8.00718998
#> 91      7   1   2  4.97826922
#> 92      8   1   2  8.68212045
#> 93      9   1   2  5.31753199
#> 94     10   1   2  0.28011569
#> 95     11   1   2  2.39837784
#> 96     12   1   2  1.21872763
#> 97     13   1   2  2.52775203
#> 98     14   1   2  3.95436306
#> 99      1   2   2  2.04600166
#> 100     2   2   2  7.28538601
#> 101     3   2   2  3.68296173
#> 102     4   2   2  0.31521727
#> 103     5   2   2  0.13542312
#> 104     6   2   2  4.13830671
#> 105     7   2   2  1.92435261
#> 106     8   2   2  1.08068813
#> 107     9   2   2  3.03620597
#> 108    10   2   2  0.72768569
#> 109    11   2   2  2.16607927
#> 110    12   2   2  0.57337428
#> 111    13   2   2  4.04185379
#> 112    14   2   2  3.57948333
#> 113     1   3   2  1.12992460
#> 114     2   3   2  0.90110266
#> 115     3   3   2  0.89186373
#> 116     4   3   2  3.44700008
#> 117     5   3   2  5.46163789
#> 118     6   3   2  1.25977324
#> 119     7   3   2  3.56188355
#> 120     8   3   2  3.80786256
#> 121     9   3   2  0.21003777
#> 122    10   3   2  1.35513145
#> 123    11   3   2  0.16617151
#> 124    12   3   2  0.36939557
#> 127     1   4   2  1.06949946
#> 128     2   4   2  0.75635875
#> 129     3   4   2  1.00114021
#> 141     1   5   2  0.49513392
#> 142     2   5   2  0.56752185
#> 155     1   6   2  0.69165476
#> 170     2   1   3  2.68833732
#> 171     3   1   3  1.32464220
#> 172     4   1   3  2.40972002
#> 173     5   1   3  1.73521428
#> 174     6   1   3  2.57189117
#> 175     7   1   3  2.76541507
#> 176     8   1   3  5.29411339
#> 177     9   1   3  3.45890304
#> 178    10   1   3  1.73646442
#> 179    11   1   3  4.11593230
#> 180    12   1   3  1.13247091
#> 181    13   1   3  1.76790555
#> 182    14   1   3  6.67683185
#> 184     2   2   3  3.05450899
#> 185     3   2   3  1.50129663
#> 186     4   2   3  0.17470519
#> 187     5   2   3  0.09816631
#> 188     6   2   3  1.90438934
#> 189     7   2   3  1.11049596
#> 190     8   2   3  0.45466295
#> 191     9   2   3 11.06550958
#> 192    10   2   3  5.84549846
#> 193    11   2   3 11.49763748
#> 194    12   2   3  4.00855888
#> 195    13   2   3  1.52606284
#> 196    14   2   3  5.73728234
#> 198     2   3   3  3.14214987
#> 199     3   3   3  0.11077675
#> 200     4   3   3  0.31827396
#> 201     5   3   3  2.96804786
#> 202     6   3   3  0.25862317
#> 203     7   3   3  0.07920964
#> 204     8   3   3  0.61673429
#> 205     9   3   3 11.49648795
#> 206    10   3   3  8.47423117
#> 207    11   3   3  9.63846557
#> 208    12   3   3 10.51471949
#> 212     2   4   3  4.87957305
#> 213     3   4   3  0.48075940
#> 226     2   5   3  5.75366816
#> 254     2   1   4  9.60471589
#> 255     3   1   4  0.12565415
#> 256     4   1   4  1.76915550
#> 257     5   1   4  2.04138802
#> 258     6   1   4  1.05991110
#> 259     7   1   4  0.73648827
#> 260     8   1   4  4.09835008
#> 261     9   1   4  3.96147275
#> 262    10   1   4 12.27576176
#> 263    11   1   4  8.86032267
#> 264    12   1   4  3.15644931
#> 265    13   1   4  0.80447355
#> 266    14   1   4  3.16833623
#> 268     2   2   4  0.06716543
#> 269     3   2   4  0.11492071
#> 270     4   2   4  0.71518788
#> 271     5   2   4  1.22369039
#> 272     6   2   4  0.09384517
#> 273     7   2   4  0.13275799
#> 274     8   2   4  6.45559086
#> 275     9   2   4  9.85505760
#> 276    10   2   4  6.15039704
#> 277    11   2   4 21.13896711
#> 278    12   2   4  2.16936766
#> 279    13   2   4  0.07124148
#> 280    14   2   4  3.28565311
#> 282     2   3   4  1.87018909
#> 283     3   3   4  0.09177290
#> 284     4   3   4  0.45867070
#> 285     5   3   4  0.49147638
#> 286     6   3   4  1.54227651
#> 287     7   3   4  2.26785684
#> 288     8   3   4  0.95556041
#> 289     9   3   4  9.42095355
#> 290    10   3   4  7.34257013
#> 291    11   3   4 13.04754757
#> 292    12   3   4  7.98618289
#> 296     2   4   4  2.76060247
#> 297     3   4   4  0.17515768
#> 310     2   5   4  3.77432368
#> 339     3   1   5  1.16885337
#> 340     4   1   5  1.57102065
#> 341     5   1   5  2.01318002
#> 342     6   1   5  0.72344940
#> 343     7   1   5  0.11964173
#> 344     8   1   5  0.21202942
#> 349    13   1   5  0.07554708
#> 350    14   1   5  0.31028712
#> 353     3   2   5  0.19571472
#> 354     4   2   5  2.19379991
#> 355     5   2   5  4.91690225
#> 356     6   2   5  1.66330834
#> 357     7   2   5  1.61787669
#> 358     8   2   5 34.78215507
#> 363    13   2   5  0.18646018
#> 364    14   2   5  0.10002781
#> 367     3   3   5  0.09992300
#> 368     4   3   5  3.37316238
#> 369     5   3   5  0.42557837
#> 370     6   3   5  4.92043247
#> 371     7   3   5  4.82000081
#> 372     8   3   5 19.77320469
#> 381     3   4   5  0.77260581
#> 423     3   1   6  2.43350991
#> 424     4   1   6  0.11212759
#> 425     5   1   6  0.17309275
#> 426     6   1   6  0.31277437
#> 427     7   1   6  0.42917893
#> 433    13   1   6  0.30887976
#> 434    14   1   6  0.12045924
#> 437     3   2   6  0.12278725
#> 438     4   2   6  5.05611810
#> 439     5   2   6 11.19315466
#> 440     6   2   6  5.72221212
#> 441     7   2   6 11.78825536
#> 447    13   2   6  0.16810889
#> 448    14   2   6  1.89836624
#> 451     3   3   6  0.32246153
#> 452     4   3   6  6.69045016
#> 453     5   3   6  3.31710568
#> 454     6   3   6 13.63037620
#> 455     7   3   6  9.34355205
#> 465     3   4   6  1.08382228
#> 507     3   1   7  3.72204318
#> 517    13   1   7  0.53674671
#> 518    14   1   7  0.79243180
#> 521     3   2   7  0.39824037
#> 531    13   2   7  0.81879447
#> 532    14   2   7  4.37234034
#> 535     3   3   7  0.14047266
#> 549     3   4   7  0.86209222
#> 591     3   1   8  4.12329950
#> 601    13   1   8  0.28248133
#> 602    14   1   8  3.93179774
#> 605     3   2   8  0.89672237
#> 615    13   2   8  0.15558031
#> 616    14   2   8  8.07340115
#> 619     3   3   8  0.18347134
#> 633     3   4   8  0.86114839
#> 685    13   1   9  0.97755549
#> 699    13   2   9  0.09699883

# Update model for 500 iterations to monitor deviance contributions
mb.update(emax, param="dev", n.iter=500)
#>     study arm fup        mean
#> 1       1   1   1 -2.07044558
#> 2       2   1   1 -2.87325441
#> 3       3   1   1 -2.13477414
#> 4       4   1   1  0.15917417
#> 5       5   1   1 -2.78995067
#> 6       6   1   1 -1.98196395
#> 7       7   1   1  7.84842800
#> 8       8   1   1 12.17324523
#> 9       9   1   1  5.35787122
#> 10     10   1   1 -4.26545885
#> 11     11   1   1 -2.75358363
#> 12     12   1   1 -4.59914404
#> 13     13   1   1 -1.46535114
#> 14     14   1   1 -2.77744490
#> 15      1   2   1 -1.59567963
#> 16      2   2   1 -6.06515212
#> 17      3   2   1 -3.39997296
#> 18      4   2   1 -4.54877247
#> 19      5   2   1 -4.63231225
#> 20      6   2   1 -4.78649694
#> 21      7   2   1 -3.35739915
#> 22      8   2   1 -4.70751835
#> 23      9   2   1  1.08873828
#> 24     10   2   1  2.68217379
#> 25     11   2   1  6.69368500
#> 26     12   2   1 -2.25343334
#> 27     13   2   1 -3.44565173
#> 28     14   2   1 -1.61869466
#> 29      1   3   1 -1.94963055
#> 30      2   3   1 -1.66985873
#> 31      3   3   1 -3.61277360
#> 32      4   3   1 -2.14072159
#> 33      5   3   1 -4.78703367
#> 34      6   3   1 -4.35019271
#> 35      7   3   1 -3.22591755
#> 36      8   3   1 -2.68003663
#> 37      9   3   1  6.70287071
#> 38     10   3   1  9.20755375
#> 39     11   3   1  2.99894647
#> 40     12   3   1  6.84192788
#> 43      1   4   1 -2.06795060
#> 44      2   4   1  4.53828055
#> 45      3   4   1 -3.57907335
#> 57      1   5   1 -2.58803875
#> 58      2   5   1  7.59704120
#> 71      1   6   1 -2.49773160
#> 85      1   1   2 -1.42539006
#> 86      2   1   2 -2.90954757
#> 87      3   1   2 -1.71724762
#> 88      4   1   2 -0.37127528
#> 89      5   1   2 -2.76070600
#> 90      6   1   2  4.17593487
#> 91      7   1   2  1.15982839
#> 92      8   1   2  4.85663963
#> 93      9   1   2  0.02517629
#> 94     10   1   2 -4.57077254
#> 95     11   1   2 -2.39924772
#> 96     12   1   2 -4.00210168
#> 97     13   1   2 -1.35608151
#> 98     14   1   2 -0.81114035
#> 99      1   2   2 -0.29807532
#> 100     2   2   2  1.49083607
#> 101     3   2   2  0.03185448
#> 102     4   2   2 -3.89680504
#> 103     5   2   2 -4.37257165
#> 104     6   2   2 -0.50980148
#> 105     7   2   2 -1.85900980
#> 106     8   2   2 -3.52116651
#> 107     9   2   2 -2.79916604
#> 108    10   2   2 -4.12088111
#> 109    11   2   2 -3.20314980
#> 110    12   2   2 -4.61645513
#> 111    13   2   2 -0.09235737
#> 112    14   2   2 -0.93877306
#> 113     1   3   2 -1.22121344
#> 114     2   3   2 -4.04614299
#> 115     3   3   2 -2.67714735
#> 116     4   3   2 -0.79436163
#> 117     5   3   2  0.95491915
#> 118     6   3   2 -3.30362366
#> 119     7   3   2 -0.11284359
#> 120     8   3   2 -0.79181870
#> 121     9   3   2 -5.43218901
#> 122    10   3   2 -3.56830911
#> 123    11   3   2 -5.04898466
#> 124    12   3   2 -4.95044675
#> 127     1   4   2 -1.34014995
#> 128     2   4   2 -4.35031868
#> 129     3   4   2 -2.75572107
#> 141     1   5   2 -1.89315740
#> 142     2   5   2 -4.50237529
#> 155     1   6   2 -1.70793067
#> 170     2   1   3 -1.27204010
#> 171     3   1   3 -2.00294261
#> 172     4   1   3 -0.73602369
#> 173     5   1   3 -1.75119033
#> 174     6   1   3 -0.98353667
#> 175     7   1   3 -0.70486325
#> 176     8   1   3  1.80434259
#> 177     9   1   3 -0.97885295
#> 178    10   1   3 -2.18008710
#> 179    11   1   3 -0.02563904
#> 180    12   1   3 -3.23102138
#> 181    13   1   3 -1.76259807
#> 182    14   1   3  2.28857489
#> 184     2   2   3 -1.26189538
#> 185     3   2   3 -2.10115370
#> 186     4   2   3 -3.79716670
#> 187     5   2   3 -4.14181086
#> 188     6   2   3 -2.38599074
#> 189     7   2   3 -2.31355742
#> 190     8   2   3 -3.84721475
#> 191     9   2   3  5.86729161
#> 192    10   2   3  1.71229187
#> 193    11   2   3  7.34296871
#> 194    12   2   3  0.08816570
#> 195    13   2   3 -2.14678346
#> 196    14   2   3  1.37987391
#> 198     2   3   3 -0.88752555
#> 199     3   3   3 -3.33093587
#> 200     4   3   3 -3.62209576
#> 201     5   3   3 -1.23609163
#> 202     6   3   3 -4.00395196
#> 203     7   3   3 -3.31763746
#> 204     8   3   3 -3.64147427
#> 205     9   3   3  6.63887000
#> 206    10   3   3  4.41013310
#> 207    11   3   3  5.33313583
#> 208    12   3   3  6.30681484
#> 212     2   4   3  0.71682862
#> 213     3   4   3 -3.20580446
#> 226     2   5   3  1.23899680
#> 254     2   1   4  5.65176524
#> 255     3   1   4 -3.11988630
#> 256     4   1   4 -1.25158545
#> 257     5   1   4 -1.25136961
#> 258     6   1   4 -2.35482796
#> 259     7   1   4 -2.62242031
#> 260     8   1   4  0.71689030
#> 261     9   1   4  0.08540616
#> 262    10   1   4  8.86373534
#> 263    11   1   4  5.14584505
#> 264    12   1   4 -0.62574941
#> 265    13   1   4 -2.46695591
#> 266    14   1   4 -0.98814951
#> 268     2   2   4 -3.23948427
#> 269     3   2   4 -3.21586783
#> 270     4   2   4 -3.19544755
#> 271     5   2   4 -2.86259969
#> 272     6   2   4 -4.05653319
#> 273     7   2   4 -3.24209969
#> 274     8   2   4  2.10207627
#> 275     9   2   4  5.06328203
#> 276    10   2   4  2.32277167
#> 277    11   2   4 17.48047232
#> 278    12   2   4 -1.47983449
#> 279    13   2   4 -3.55561034
#> 280    14   2   4 -1.06234119
#> 282     2   3   4 -1.81637322
#> 283     3   3   4 -3.22372393
#> 284     4   3   4 -3.38908541
#> 285     5   3   4 -3.52461324
#> 286     6   3   4 -2.57525981
#> 287     7   3   4 -1.05466292
#> 288     8   3   4 -3.21239246
#> 289     9   3   4  5.02450123
#> 290    10   3   4  3.48734161
#> 291    11   3   4  9.08984599
#> 292    12   3   4  4.19215260
#> 296     2   4   4 -0.93520608
#> 297     3   4   4 -3.34311273
#> 310     2   5   4 -0.30194800
#> 339     3   1   5 -1.91692227
#> 340     4   1   5 -1.34023317
#> 341     5   1   5 -1.23369352
#> 342     6   1   5 -2.66385652
#> 343     7   1   5 -3.13974051
#> 344     8   1   5 -2.89512889
#> 349    13   1   5 -3.16509145
#> 350    14   1   5 -3.87460740
#> 353     3   2   5 -3.00298491
#> 354     4   2   5 -1.66134284
#> 355     5   2   5  0.81882195
#> 356     6   2   5 -2.50248630
#> 357     7   2   5 -1.71193796
#> 358     8   2   5 30.28391211
#> 363    13   2   5 -3.31341066
#> 364    14   2   5 -4.19821468
#> 367     3   3   5 -3.12046235
#> 368     4   3   5 -0.45863796
#> 369     5   3   5 -3.56039207
#> 370     6   3   5  0.81220477
#> 371     7   3   5  1.55887670
#> 372     8   3   5 15.58173047
#> 381     3   4   5 -2.48737262
#> 423     3   1   6 -0.70577982
#> 424     4   1   6 -2.77463557
#> 425     5   1   6 -3.01430265
#> 426     6   1   6 -2.99360270
#> 427     7   1   6 -2.80330160
#> 433    13   1   6 -3.02823307
#> 434    14   1   6 -4.02010322
#> 437     3   2   6 -2.83681678
#> 438     4   2   6  1.16670494
#> 439     5   2   6  6.99941243
#> 440     6   2   6  1.53414600
#> 441     7   2   6  8.43741330
#> 447    13   2   6 -3.35020649
#> 448    14   2   6 -2.30836636
#> 451     3   3   6 -2.75257841
#> 452     4   3   6  2.88390718
#> 453     5   3   6 -0.70204864
#> 454     6   3   6  9.52130036
#> 455     7   3   6  6.10255974
#> 465     3   4   6 -1.99567228
#> 507     3   1   7  0.41386114
#> 517    13   1   7 -2.78076719
#> 518    14   1   7 -3.39834439
#> 521     3   2   7 -2.41628757
#> 531    13   2   7 -2.48313270
#> 532    14   2   7  0.33334165
#> 535     3   3   7 -3.10533475
#> 549     3   4   7 -2.20331649
#> 591     3   1   8  0.70466893
#> 601    13   1   8 -2.97411659
#> 602    14   1   8 -0.35456611
#> 605     3   2   8 -1.79989873
#> 615    13   2   8 -3.22137418
#> 616    14   2   8  3.97432361
#> 619     3   3   8 -3.11641201
#> 633     3   4   8 -2.18263080
#> 685    13   1   9 -2.17032298
#> 699    13   2   9 -3.22551790
# }