- using R version 2.15.0 (2012-03-30)
- using platform: i386-apple-darwin9.8.0 (32-bit)
- using session charset: ASCII
- checking for file 'censReg/DESCRIPTION' ... OK
- this is package 'censReg' version '0.5-10'
- checking package namespace information ... OK
- checking package dependencies ... OK
- checking if this is a source package ... OK
- checking if there is a namespace ... OK
- checking for executable files ... OK
- checking whether package 'censReg' can be installed ... OK
- checking installed package size ... OK
- checking package directory ... OK
- checking for portable file names ... OK
- checking for sufficient/correct file permissions ... OK
- checking DESCRIPTION meta-information ... OK
- checking top-level files ... OK
- checking index information ... OK
- checking package subdirectories ... OK
- checking R files for non-ASCII characters ... OK
- checking R files for syntax errors ... OK
- checking whether the package can be loaded ... OK
- checking whether the package can be loaded with stated dependencies ... OK
- checking whether the package can be unloaded cleanly ... OK
- checking whether the namespace can be loaded with stated dependencies ... OK
- checking whether the namespace can be unloaded cleanly ... OK
- checking for unstated dependencies in R code ... OK
- checking S3 generic/method consistency ... OK
- checking replacement functions ... OK
- checking foreign function calls ... OK
- checking R code for possible problems ... NOTE
censReg: no visible binding for global variable 'validObs2'
- checking Rd files ... OK
- checking Rd metadata ... OK
- checking Rd cross-references ... OK
- checking for missing documentation entries ... OK
- checking for code/documentation mismatches ... OK
- checking Rd \usage sections ... OK
- checking Rd contents ... OK
- checking for unstated dependencies in examples ... OK
- checking sizes of PDF files under 'inst/doc' ... OK
- checking installed files from 'inst/doc' ... OK
- checking examples ... OK
- checking for unstated dependencies in tests ... OK
- checking tests ... OK
Running 'censRegPanelLargerTest.R'
Comparing 'censRegPanelLargerTest.Rout' to 'censRegPanelLargerTest.Rout.save' ... OK
Running 'censRegPanelTest.R'
Comparing 'censRegPanelTest.Rout' to 'censRegPanelTest.Rout.save' ...127,128c127,128
< (Intercept) 0.225109672 -0.020570167 -0.254602886 -0.023824162 -0.002973952
< x1 -0.020570167 0.043773972 0.008562225 0.013404079 0.002969957
---
> (Intercept) 0.225109671 -0.020570168 -0.254602886 -0.023824162 -0.002973952
> x1 -0.020570168 0.043773972 0.008562225 0.013404079 0.002969957
134,135c134,135
< (Intercept) 0.225109672 -0.020570167 -0.254602886 -0.020929366 -0.002937279
< x1 -0.020570167 0.043773972 0.008562225 0.011775393 0.002933333
---
> (Intercept) 0.225109671 -0.020570168 -0.254602886 -0.020929366 -0.002937279
> x1 -0.020570168 0.043773972 0.008562225 0.011775394 0.002933333
137c137
< sigmaMu -0.020929366 0.011775393 0.015092113 0.051398826 -0.002289643
---
> sigmaMu -0.020929366 0.011775394 0.015092113 0.051398826 -0.002289643
170c170
< 1.712911e-11 4.534229e-11 1.345810e-11 8.216872e-12 6.208670e-11
---
> 1.711386e-11 4.533762e-11 1.344722e-11 8.216400e-12 6.207498e-11
604c604
< -0.37057 1.67999 2.24862 -0.12934 -0.01238
---
> -0.36750 1.67993 2.24379 -0.12947 -0.01241
609c609
< BFGSR maximization, 79 iterations
---
> BFGSR maximization, 78 iterations
611c611
< Log-Likelihood: -73.1989
---
> Log-Likelihood: -73.19883
615,619c615,619
< (Intercept) -0.370568 0.474897 -0.7803 0.4352071
< x1 1.679988 0.209259 8.0283 9.884e-16 ***
< x2 2.248615 0.674122 3.3356 0.0008511 ***
< logSigmaMu -0.129340 0.258029 -0.5013 0.6161867
< logSigmaNu -0.012385 0.129699 -0.0955 0.9239267
---
> (Intercept) -0.367502 0.474613 -0.7743 0.4387426
> x1 1.679929 0.209229 8.0291 9.816e-16 ***
> x2 2.243794 0.673969 3.3292 0.0008709 ***
> logSigmaMu -0.129473 0.258047 -0.5017 0.6158482
> logSigmaNu -0.012409 0.129690 -0.0957 0.9237740
634,638c634,638
< (Intercept) -0.37057 0.47490 -0.780 0.435207
< x1 1.67999 0.20926 8.028 9.88e-16 ***
< x2 2.24862 0.67412 3.336 0.000851 ***
< logSigmaMu -0.12934 0.25803 -0.501 0.616187
< logSigmaNu -0.01238 0.12970 -0.095 0.923927
---
> (Intercept) -0.36750 0.47461 -0.774 0.438743
> x1 1.67993 0.20923 8.029 9.82e-16 ***
> x2 2.24379 0.67397 3.329 0.000871 ***
> logSigmaMu -0.12947 0.25805 -0.502 0.615848
> logSigmaNu -0.01241 0.12969 -0.096 0.923774
642c642
< BFGSR maximization, 79 iterations
---
> BFGSR maximization, 78 iterations
644c644
< Log-likelihood: -73.1989 on 5 Df
---
> Log-likelihood: -73.19883 on 5 Df
648c648
< [1] -73.1989
---
> [1] -73.19883
652c652
< -0.37056805 1.67998816 2.24861521 -0.12934020 -0.01238474
---
> -0.36750163 1.67992931 2.24379444 -0.12947348 -0.01240886
656c656
< 0.0064789587 0.0056467255 -0.0143113590 0.0018124278 0.0004333105
---
> 0.0014212306 0.0034992596 -0.0064419525 0.0003782988 0.0003341343
660,664c660,664
< (Intercept) -13.311082 -4.095630 -7.3035010 -2.1329464 -1.2898286
< x1 -4.095630 -26.071343 -1.9887963 4.4818572 4.7507112
< x2 -7.303501 -1.988796 -6.2342610 -0.6319032 -0.4416634
< logSigmaMu -2.132946 4.481857 -0.6319032 -16.6765687 -3.7224144
< logSigmaNu -1.289829 4.750711 -0.4416634 -3.7224144 -61.0558439
---
> (Intercept) -13.317517 -4.096146 -7.3057987 -2.1155739 -1.300861
> x1 -4.096146 -26.075639 -1.9898094 4.4840349 4.755412
> x2 -7.305799 -1.989809 -6.2353998 -0.6259168 -0.464233
> logSigmaMu -2.115574 4.484035 -0.6259168 -16.6651955 -3.721179
> logSigmaNu -1.300861 4.755412 -0.4642330 -3.7211788 -61.065093
680c680
< [1] 79
---
> [1] 78
687,701c687,701
< [1,] -0.85216812 0.22352995 -0.07364572 -0.1446205 -0.9678051
< [2,] -1.70367158 0.04641517 -1.19140478 1.6832892 -1.0119822
< [3,] 1.75043100 0.33422765 1.72491799 1.8353355 1.7940935
< [4,] 0.15545147 -0.20322043 -0.43383789 -0.6893163 -1.4265922
< [5,] 0.12980373 0.98298202 0.68709567 -0.6768620 -0.5627093
< [6,] 0.33023562 -0.30414724 0.38358657 -0.4920260 -1.5826042
< [7,] -0.07973055 -3.18587601 -0.23676741 -0.6770972 6.0311261
< [8,] -0.26574402 0.37788872 0.05562230 -0.5388916 -1.1087669
< [9,] 1.14898817 0.59426578 0.30326960 0.1350017 -1.6149675
< [10,] -0.43384915 -0.40461913 -0.15224001 -0.4697202 -1.9371473
< [11,] -0.02775353 1.45089439 -0.64495620 -0.9182210 2.7438221
< [12,] 1.21017306 0.53891602 0.61090902 0.2050698 -1.7330381
< [13,] 0.53639774 -0.22509628 0.33101470 -0.3686114 -1.4086668
< [14,] -1.81481424 -1.30814108 -0.92026357 1.9588710 2.5772738
< [15,] -0.07727065 1.08762720 -0.45761164 -0.8403885 0.2083974
---
> [1,] -0.85278081 0.2247850 -0.07302970 -0.1442070 -0.9634923
> [2,] -1.70342425 0.0476419 -1.19055345 1.6820162 -1.0127268
> [3,] 1.75059965 0.3340379 1.72645582 1.8351650 1.8000202
> [4,] 0.15552297 -0.2026892 -0.43296702 -0.6893599 -1.4315786
> [5,] 0.12953233 0.9838683 0.68846571 -0.6770129 -0.5576955
> [6,] 0.33020957 -0.3070305 0.38415893 -0.4921914 -1.5806796
> [7,] -0.08124385 -3.1854369 -0.23706941 -0.6768114 6.0284476
> [8,] -0.26650783 0.3785437 0.05560267 -0.5386742 -1.1090288
> [9,] 1.14849813 0.5942606 0.30325840 0.1336487 -1.6163416
> [10,] -0.43466534 -0.4056715 -0.15242875 -0.4690608 -1.9368240
> [11,] -0.02815366 1.4492071 -0.64446998 -0.9176305 2.7387662
> [12,] 1.21036511 0.5376472 0.61231215 0.2052291 -1.7342086
> [13,] 0.53592238 -0.2250517 0.33100094 -0.3690601 -1.4085335
> [14,] -1.81473915 -1.3068211 -0.91982779 1.9580283 2.5799493
> [15,] -0.07771403 1.0862084 -0.45735047 -0.8397008 0.2042601
804c804
< 4.63179 1.68021 2.24438 -0.12914 -0.01233
---
> 4.62970 1.67974 2.24826 -0.12967 -0.01247
809c809
< BFGSR maximization, 78 iterations
---
> BFGSR maximization, 75 iterations
811c811
< Log-Likelihood: -73.19884
---
> Log-Likelihood: -73.19889
815,819c815,819
< (Intercept) 4.631789 0.474787 9.7555 < 2.2e-16 ***
< x1 1.680211 0.209268 8.0290 9.827e-16 ***
< x2 2.244378 0.674075 3.3296 0.0008698 ***
< logSigmaMu -0.129143 0.257998 -0.5006 0.6166816
< logSigmaNu -0.012332 0.129702 -0.0951 0.9242517
---
> (Intercept) 4.629702 0.474777 9.7513 < 2.2e-16 ***
> x1 1.679738 0.209226 8.0284 9.878e-16 ***
> x2 2.248262 0.674033 3.3355 0.0008513 ***
> logSigmaMu -0.129673 0.258097 -0.5024 0.6153734
> logSigmaNu -0.012466 0.129691 -0.0961 0.9234264
834,838c834,838
< (Intercept) 4.63179 0.47479 9.756 < 2e-16 ***
< x1 1.68021 0.20927 8.029 9.83e-16 ***
< x2 2.24438 0.67408 3.330 0.00087 ***
< logSigmaMu -0.12914 0.25800 -0.501 0.61668
< logSigmaNu -0.01233 0.12970 -0.095 0.92425
---
> (Intercept) 4.62970 0.47478 9.751 < 2e-16 ***
> x1 1.67974 0.20923 8.028 9.88e-16 ***
> x2 2.24826 0.67403 3.336 0.000851 ***
> logSigmaMu -0.12967 0.25810 -0.502 0.615373
> logSigmaNu -0.01247 0.12969 -0.096 0.923426
842c842
< BFGSR maximization, 78 iterations
---
> BFGSR maximization, 75 iterations
844c844
< Log-likelihood: -73.19884 on 5 Df
---
> Log-likelihood: -73.19889 on 5 Df
848c848
< 4.63178938 1.68021077 2.24437755 -0.12914317 -0.01233196
---
> 4.62970160 1.67973837 2.24826176 -0.12967269 -0.01246575
851c851
< 4.6317894 1.6802108 2.2443776 0.8788481 0.9877438
---
> 4.6297016 1.6797384 2.2482618 0.8783829 0.9876116
854,858c854,858
< (Intercept) 0.225422449 -0.020634257 -0.254853434 -0.023955407 -0.003015766
< x1 -0.020634257 0.043792977 0.008624400 0.013412037 0.002973112
< x2 -0.254853434 0.008624400 0.454377608 0.017255443 0.001604193
< logSigmaMu -0.023955407 0.013412037 0.017255443 0.066562955 -0.002626309
< logSigmaNu -0.003015766 0.002973112 0.001604193 -0.002626309 0.016822520
---
> (Intercept) 0.225413235 -0.020660460 -0.254872111 -0.024058747 -0.003055367
> x1 -0.020660460 0.043775353 0.008670292 0.013424948 0.002954403
> x2 -0.254872111 0.008670292 0.454320177 0.017344565 0.001704899
> logSigmaMu -0.024058747 0.013424948 0.017344565 0.066614118 -0.002644224
> logSigmaNu -0.003055367 0.002954403 0.001704899 -0.002644224 0.016819840
861,865c861,865
< (Intercept) 0.225422449 -0.020634257 -0.254853434 -0.021053165 -0.002978804
< x1 -0.020634257 0.043792977 0.008624400 0.011787143 0.002936673
< x2 -0.254853434 0.008624400 0.454377608 0.015164914 0.001584531
< sigmaMu -0.021053165 0.011787143 0.015164914 0.051411498 -0.002279838
< sigmaNu -0.002978804 0.002936673 0.001584531 -0.002279838 0.016412686
---
> (Intercept) 0.225413235 -0.020660460 -0.254872111 -0.021132792 -0.003017516
> x1 -0.020660460 0.043775353 0.008670292 0.011792244 0.002917803
> x2 -0.254872111 0.008670292 0.454320177 0.015235169 0.001683778
> sigmaMu -0.021132792 0.011792244 0.015235169 0.051396556 -0.002293867
> sigmaNu -0.003017516 0.002917803 0.001683778 -0.002293867 0.016405681
867c867
< 'log Lik.' -73.19884 (df=5)
---
> 'log Lik.' -73.19889 (df=5)
869c869
< [1] -40.0000 156.3977
---
> [1] -40.0000 156.3978
872c872
< [1] -73.19884
---
> [1] -73.19889
876c876
< 4.63178938 1.68021077 2.24437755 -0.12914317 -0.01233196
---
> 4.62970160 1.67973837 2.24826176 -0.12967269 -0.01246575
880c880
< 0.0046485580 -0.0002485124 -0.0057017491 -0.0030154623 -0.0035992940
---
> 0.007307875 0.009883823 -0.013334396 0.006186400 0.005241257
884,888c884,888
< (Intercept) -13.309328 -4.094718 -7.3020705 -2.1230848 -1.2974103
< x1 -4.094718 -26.068508 -1.9889081 4.4825039 4.7625990
< x2 -7.302071 -1.988908 -6.2331443 -0.6295535 -0.4614247
< logSigmaMu -2.123085 4.482504 -0.6295535 -16.6740611 -3.7159129
< logSigmaNu -1.297410 4.762599 -0.4614247 -3.7159129 -61.0545462
---
> (Intercept) -13.320457 -4.097602 -7.3082204 -2.1336126 -1.2945958
> x1 -4.097602 -26.078345 -1.9899709 4.4821291 4.7426563
> x2 -7.308220 -1.989971 -6.2371991 -0.6321033 -0.4451737
> logSigmaMu -2.133613 4.482129 -0.6321033 -16.6692492 -3.7313402
> logSigmaNu -1.294596 4.742656 -0.4451737 -3.7313402 -61.0632866
904c904
< [1] 78
---
> [1] 75
911,925c911,925
< [1,] -0.85230633 0.22458843 -0.07304728 -0.1444141 -0.9650018
< [2,] -1.70246830 0.04759869 -1.18995433 1.6809976 -1.0130521
< [3,] 1.74974401 0.33303785 1.72570975 1.8347312 1.7986028
< [4,] 0.15550920 -0.20287632 -0.43302639 -0.6890484 -1.4313931
< [5,] 0.12968588 0.98344340 0.68824520 -0.6770050 -0.5584949
< [6,] 0.33002983 -0.30775933 0.38412685 -0.4920320 -1.5810607
< [7,] -0.08078956 -3.18544132 -0.23696891 -0.6770491 6.0297346
< [8,] -0.26603171 0.37824869 0.05575580 -0.5389443 -1.1086688
< [9,] 1.14834217 0.59365930 0.30320618 0.1337981 -1.6162881
< [10,] -0.43402788 -0.40549326 -0.15210183 -0.4694328 -1.9367171
< [11,] -0.02797603 1.44910704 -0.64432126 -0.9180796 2.7385099
< [12,] 1.20989300 0.53746891 0.61196604 0.2047991 -1.7341828
< [13,] 0.53628861 -0.22529766 0.33118065 -0.3685549 -1.4085268
< [14,] -1.81396848 -1.30658448 -0.91942370 1.9575483 2.5784985
< [15,] -0.07727586 1.08605156 -0.45704852 -0.8403296 0.2044413
---
> [1,] -0.85234478 0.22391255 -0.07352168 -0.1446474 -0.9667939
> [2,] -1.70440691 0.04648408 -1.19187418 1.6836901 -1.0116930
> [3,] 1.75174657 0.33535241 1.72587454 1.8367494 1.7958201
> [4,] 0.15579094 -0.20309642 -0.43362554 -0.6891859 -1.4267967
> [5,] 0.12991963 0.98333538 0.68739315 -0.6767124 -0.5620972
> [6,] 0.33086011 -0.30311404 0.38387759 -0.4917565 -1.5823937
> [7,] -0.07989148 -3.18597288 -0.23681005 -0.6769023 6.0302925
> [8,] -0.26596451 0.37804584 0.05556194 -0.5387087 -1.1089943
> [9,] 1.14932504 0.59476363 0.30337878 0.1352853 -1.6147885
> [10,] -0.43413381 -0.40461336 -0.15239416 -0.4696682 -1.9371976
> [11,] -0.02782997 1.45111717 -0.64509342 -0.9178916 2.7444007
> [12,] 1.21065533 0.53914179 0.61120668 0.2059469 -1.7330972
> [13,] 0.53650159 -0.22510291 0.33108334 -0.3687683 -1.4084656
> [14,] -1.81538737 -1.30822940 -0.92054812 1.9588064 2.5784263
> [15,] -0.07753252 1.08785999 -0.45784326 -0.8400504 0.2086192
991c991
< 0.37057 -1.67999 -2.24862 -0.12934 -0.01238
---
> 0.36750 -1.67993 -2.24379 -0.12947 -0.01241
996c996
< BFGSR maximization, 79 iterations
---
> BFGSR maximization, 78 iterations
998c998
< Log-Likelihood: -73.1989
---
> Log-Likelihood: -73.19883
1002,1006c1002,1006
< (Intercept) 0.370568 0.474897 0.7803 0.4352069
< x1 -1.679988 0.209259 -8.0283 9.884e-16 ***
< x2 -2.248616 0.674122 -3.3356 0.0008511 ***
< logSigmaMu -0.129341 0.258029 -0.5013 0.6161856
< logSigmaNu -0.012385 0.129699 -0.0955 0.9239267
---
> (Intercept) 0.367502 0.474613 0.7743 0.4387426
> x1 -1.679929 0.209229 -8.0291 9.816e-16 ***
> x2 -2.243794 0.673969 -3.3292 0.0008709 ***
> logSigmaMu -0.129473 0.258047 -0.5017 0.6158482
> logSigmaNu -0.012409 0.129690 -0.0957 0.9237740
1022,1026c1022,1026
< (Intercept) 0.37057 0.47490 0.780 0.435207
< x1 -1.67999 0.20926 -8.028 9.88e-16 ***
< x2 -2.24862 0.67412 -3.336 0.000851 ***
< logSigmaMu -0.12934 0.25803 -0.501 0.616186
< logSigmaNu -0.01238 0.12970 -0.095 0.923927
---
> (Intercept) 0.36750 0.47461 0.774 0.438743
> x1 -1.67993 0.20923 -8.029 9.82e-16 ***
> x2 -2.24379 0.67397 -3.329 0.000871 ***
> logSigmaMu -0.12947 0.25805 -0.502 0.615848
> logSigmaNu -0.01241 0.12969 -0.096 0.923774
1030c1030
< BFGSR maximization, 79 iterations
---
> BFGSR maximization, 78 iterations
1032c1032
< Log-likelihood: -73.1989 on 5 Df
---
> Log-likelihood: -73.19883 on 5 Df
1036c1036
< 0.37056813 -1.67998792 -2.24861616 -0.12934066 -0.01238475
---
> 0.36750163 -1.67992931 -2.24379444 -0.12947348 -0.01240886
1039c1039
< 0.3705681 -1.6799879 -2.2486162 0.8786746 0.9876916
---
> 0.3675016 -1.6799293 -2.2437944 0.8785579 0.9876678
1042,1046c1042,1046
< (Intercept) 0.225527161 -0.020673437 -0.254957099 0.024056898 0.003061966
< x1 -0.020673437 0.043789121 0.008679578 -0.013422338 -0.002962818
< x2 -0.254957099 0.008679578 0.454440827 -0.017339109 -0.001717016
< logSigmaMu 0.024056898 -0.013422338 -0.017339109 0.066579079 -0.002631994
< logSigmaNu 0.003061966 -0.002962818 -0.001717016 -0.002631994 0.016821713
---
> (Intercept) 0.22525765 -0.020606031 -0.254727485 0.023900534 0.003010360
> x1 -0.02060603 0.043776857 0.008606687 -0.013409282 -0.002965503
> x2 -0.25472748 0.008606687 0.454234549 -0.017236296 -0.001593108
> logSigmaMu 0.02390053 -0.013409282 -0.017236296 0.066588439 -0.002635405
> logSigmaNu 0.00301036 -0.002965503 -0.001593108 -0.002635405 0.016819519
1049,1053c1049,1053
< (Intercept) 0.225527161 -0.020673437 -0.254957099 0.021138185 0.003024278
< x1 -0.020673437 0.043789121 0.008679578 -0.011793867 -0.002926350
< x2 -0.254957099 0.008679578 0.454440827 -0.015235435 -0.001695883
< sigmaMu 0.021138185 -0.011793867 -0.015235435 0.051403645 -0.002284201
< sigmaNu 0.003024278 -0.002926350 -0.001695883 -0.002284201 0.016410166
---
> (Intercept) 0.225257647 -0.020606031 -0.254727485 0.020998003 0.002973236
> x1 -0.020606031 0.043776857 0.008606687 -0.011780830 -0.002928932
> x2 -0.254727485 0.008606687 0.454234549 -0.015143084 -0.001573462
> sigmaMu 0.020998003 -0.011780830 -0.015143084 0.051397216 -0.002286802
> sigmaNu 0.002973236 -0.002928932 -0.001573462 -0.002286802 0.016407234
1055c1055
< 'log Lik.' -73.1989 (df=5)
---
> 'log Lik.' -73.19883 (df=5)
1057c1057
< [1] -40.0000 156.3978
---
> [1] -40.0000 156.3977
1060c1060
< [1] -73.1989
---
> [1] -73.19883
1064c1064
< 0.37056813 -1.67998792 -2.24861616 -0.12934066 -0.01238475
---
> 0.36750163 -1.67992931 -2.24379444 -0.12947348 -0.01240886
1068c1068
< -0.0064750983 -0.0056495347 0.0143159034 0.0018184934 0.0004339865
---
> -0.0014212306 -0.0034992596 0.0064419525 0.0003782988 0.0003341343
1072,1076c1072,1076
< (Intercept) -13.311091 -4.095631 -7.3035050 2.1329396 1.2898298
< x1 -4.095631 -26.071347 -1.9887969 -4.4818588 -4.7507046
< x2 -7.303505 -1.988797 -6.2342630 0.6318989 0.4416592
< logSigmaMu 2.132940 -4.481859 0.6318988 -16.6765564 -3.7224235
< logSigmaNu 1.289830 -4.750705 0.4416592 -3.7224235 -61.0558473
---
> (Intercept) -13.317517 -4.096146 -7.3057987 2.1155739 1.300861
> x1 -4.096146 -26.075639 -1.9898094 -4.4840349 -4.755412
> x2 -7.305799 -1.989809 -6.2353998 0.6259168 0.464233
> logSigmaMu 2.115574 -4.484035 0.6259168 -16.6651955 -3.721179
> logSigmaNu 1.300861 -4.755412 0.4642330 -3.7211788 -61.065093
1092c1092
< [1] 79
---
> [1] 78
1099,1113c1099,1113
< [1,] 0.85216869 -0.22352932 0.07364610 -0.1446203 -0.9678049
< [2,] 1.70367319 -0.04641448 1.19140609 1.6832914 -1.0119814
< [3,] -1.75043196 -0.33422889 -1.72491827 1.8353356 1.7940932
< [4,] -0.15545157 0.20322040 0.43383798 -0.6893167 -1.4265909
< [5,] -0.12980358 -0.98298210 -0.68709534 -0.6768620 -0.5627104
< [6,] -0.33023578 0.30414561 -0.38358639 -0.4920264 -1.5826044
< [7,] 0.07973069 3.18587576 0.23676742 -0.6770968 6.0311247
< [8,] 0.26574444 -0.37788889 -0.05562206 -0.5388912 -1.1087674
< [9,] -1.14898856 -0.59426624 -0.30326969 0.1350020 -1.6149674
< [10,] 0.43384994 0.40461915 0.15224049 -0.4697198 -1.9371475
< [11,] 0.02775371 -1.45089478 0.64495648 -0.9182204 2.7438230
< [12,] -1.21017374 -0.53891661 -0.61090910 0.2050704 -1.7330381
< [13,] -0.53639741 0.22509596 -0.33101446 -0.3686120 -1.4086669
< [14,] 1.81481557 1.30814253 0.92026453 1.9588724 2.5772746
< [15,] 0.07727125 -1.08762763 0.45761213 -0.8403877 0.2083978
---
> [1,] 0.85278081 -0.2247850 0.07302970 -0.1442070 -0.9634923
> [2,] 1.70342425 -0.0476419 1.19055345 1.6820162 -1.0127268
> [3,] -1.75059965 -0.3340379 -1.72645582 1.8351650 1.8000202
> [4,] -0.15552297 0.2026892 0.43296702 -0.6893599 -1.4315786
> [5,] -0.12953233 -0.9838683 -0.68846571 -0.6770129 -0.5576955
> [6,] -0.33020957 0.3070305 -0.38415893 -0.4921914 -1.5806796
> [7,] 0.08124385 3.1854369 0.23706941 -0.6768114 6.0284476
> [8,] 0.26650783 -0.3785437 -0.05560267 -0.5386742 -1.1090288
> [9,] -1.14849813 -0.5942606 -0.30325840 0.1336487 -1.6163416
> [10,] 0.43466534 0.4056715 0.15242875 -0.4690608 -1.9368240
> [11,] 0.02815366 -1.4492071 0.64446998 -0.9176305 2.7387662
> [12,] -1.21036511 -0.5376472 -0.61231215 0.2052291 -1.7342086
> [13,] -0.53592238 0.2250517 -0.33100094 -0.3690601 -1.4085335
> [14,] 1.81473915 1.3068211 0.91982779 1.9580283 2.5799493
> [15,] 0.07771403 -1.0862084 0.45735047 -0.8397008 0.2042601
1180c1180
< -4.6307 -1.6805 -2.2463 -0.1292 -0.0124
---
> -4.63391 -1.68002 -2.24127 -0.12953 -0.01241
1185c1185
< BFGSR maximization, 81 iterations
---
> BFGSR maximization, 73 iterations
1187c1187
< Log-Likelihood: -73.19886
---
> Log-Likelihood: -73.19882
1191,1195c1191,1195
< (Intercept) -4.630677 0.474848 -9.7519 < 2.2e-16 ***
< x1 -1.680483 0.209282 -8.0297 9.768e-16 ***
< x2 -2.246251 0.674084 -3.3323 0.0008613 ***
< logSigmaMu -0.129211 0.257995 -0.5008 0.6164919
< logSigmaNu -0.012402 0.129698 -0.0956 0.9238206
---
> (Intercept) -4.633912 0.474500 -9.7659 < 2.2e-16 ***
> x1 -1.680022 0.209226 -8.0297 9.772e-16 ***
> x2 -2.241274 0.673908 -3.3258 0.0008817 ***
> logSigmaMu -0.129526 0.258065 -0.5019 0.6157303
> logSigmaNu -0.012412 0.129690 -0.0957 0.9237579
1211,1215c1211,1215
< (Intercept) -4.6307 0.4748 -9.752 < 2e-16 ***
< x1 -1.6805 0.2093 -8.030 9.77e-16 ***
< x2 -2.2462 0.6741 -3.332 0.000861 ***
< logSigmaMu -0.1292 0.2580 -0.501 0.616492
< logSigmaNu -0.0124 0.1297 -0.096 0.923821
---
> (Intercept) -4.63391 0.47450 -9.766 < 2e-16 ***
> x1 -1.68002 0.20923 -8.030 9.77e-16 ***
> x2 -2.24127 0.67391 -3.326 0.000882 ***
> logSigmaMu -0.12953 0.25807 -0.502 0.615730
> logSigmaNu -0.01241 0.12969 -0.096 0.923758
1219c1219
< BFGSR maximization, 81 iterations
---
> BFGSR maximization, 73 iterations
1221c1221
< Log-likelihood: -73.19886 on 5 Df
---
> Log-likelihood: -73.19882 on 5 Df
1225c1225
< -4.63067746 -1.68048285 -2.24625120 -0.12921113 -0.01240199
---
> -4.63391165 -1.68002232 -2.24127447 -0.12952582 -0.01241152
1228c1228
< -4.6306775 -1.6804828 -2.2462512 0.8787884 0.9876746
---
> -4.6339117 -1.6800223 -2.2412745 0.8785119 0.9876652
1231,1235c1231,1235
< (Intercept) 0.225480373 -0.020660876 -0.254900177 0.024005554 0.003035301
< x1 -0.020660876 0.043799096 0.008656191 -0.013418190 -0.002979254
< x2 -0.254900177 0.008656191 0.454389820 -0.017295177 -0.001652372
< logSigmaMu 0.024005554 -0.013418190 -0.017295177 0.066561325 -0.002626804
< logSigmaNu 0.003035301 -0.002979254 -0.001652372 -0.002626804 0.016821503
---
> (Intercept) 0.225149823 -0.020580559 -0.254635601 0.023847765 0.002981648
> x1 -0.020580559 0.043775600 0.008573460 -0.013405916 -0.002969797
> x2 -0.254635601 0.008573460 0.454151985 -0.017194816 -0.001524188
> logSigmaMu 0.023847765 -0.013405916 -0.017194816 0.066597765 -0.002638193
> logSigmaNu 0.002981648 -0.002969797 -0.001524188 -0.002638193 0.016819556
1238,1242c1238,1242
< (Intercept) 0.22548037 -0.020660876 -0.254900177 0.021095802 0.002997890
< x1 -0.02066088 0.043799096 0.008656191 -0.011791750 -0.002942533
< x2 -0.25490018 0.008656191 0.454389820 -0.015198801 -0.001632006
< sigmaMu 0.02109580 -0.011791750 -0.015198801 0.051403252 -0.002279953
< sigmaNu 0.00299789 -0.002942533 -0.001632006 -0.002279953 0.016409395
---
> (Intercept) 0.22514982 -0.020580559 -0.254635601 0.020950545 0.002944870
> x1 -0.02058056 0.043775600 0.008573460 -0.011777256 -0.002933165
> x2 -0.25463560 0.008573460 0.454151985 -0.015105851 -0.001505387
> sigmaMu 0.02095055 -0.011777256 -0.015105851 0.051399034 -0.002289095
> sigmaNu 0.00294487 -0.002933165 -0.001505387 -0.002289095 0.016407183
1244c1244
< 'log Lik.' -73.19886 (df=5)
---
> 'log Lik.' -73.19882 (df=5)
1246c1246
< [1] -40.0000 156.3977
---
> [1] -40.0000 156.3976
1249c1249
< [1] -73.19886
---
> [1] -73.19882
1253c1253
< -4.63067746 -1.68048285 -2.24625120 -0.12921113 -0.01240199
---
> -4.63391165 -1.68002232 -2.24127447 -0.12952582 -0.01241152
1257c1257
< -0.0048866096 0.0071527882 0.0097277101 0.0007806535 0.0028105458
---
> -7.425390e-04 -5.237316e-05 1.205358e-03 2.666987e-04 4.763349e-04
1261,1265c1261,1265
< (Intercept) -13.309605 -4.095386 -7.3026112 2.1280176 1.2912472
< x1 -4.095386 -26.068538 -1.9887942 -4.4833261 -4.7734798
< x2 -7.302611 -1.988794 -6.2337770 0.6308358 0.4516281
< logSigmaMu 2.128018 -4.483326 0.6308358 -16.6779255 -3.7204412
< logSigmaNu 1.291247 -4.773480 0.4516281 -3.7204412 -61.0627565
---
> (Intercept) -13.321012 -4.096571 -7.3072433 2.1105735 1.306995
> x1 -4.096571 -26.076360 -1.9903898 -4.4846924 -4.761848
> x2 -7.307243 -1.990390 -6.2361292 0.6247544 0.476812
> logSigmaMu 2.110574 -4.484692 0.6247544 -16.6602022 -3.722583
> logSigmaNu 1.306995 -4.761848 0.4768120 -3.7225828 -61.067774
1281c1281
< [1] 81
---
> [1] 73
1288,1302c1288,1302
< [1,] 0.85258829 -0.22348676 0.07359303 -0.1442407 -0.9666015
< [2,] 1.70307507 -0.04656243 1.19073732 1.6823134 -1.0127467
< [3,] -1.74990831 -0.33229784 -1.72536269 1.8347922 1.7975289
< [4,] -0.15551064 0.20325315 0.43345733 -0.6890586 -1.4290419
< [5,] -0.12980082 -0.98288716 -0.68775814 -0.6769147 -0.5604661
< [6,] -0.32980975 0.30780970 -0.38395431 -0.4922636 -1.5811577
< [7,] 0.08026704 3.18659689 0.23693165 -0.6771100 6.0336671
< [8,] 0.26571038 -0.37792463 -0.05575911 -0.5390071 -1.1085588
< [9,] -1.14871753 -0.59312853 -0.30328203 0.1345353 -1.6159462
< [10,] 0.43407764 0.40564778 0.15217448 -0.4694234 -1.9364891
< [11,] 0.02790629 -1.44967200 0.64454222 -0.9181711 2.7404867
< [12,] -1.20997476 -0.53786403 -0.61156680 0.2048039 -1.7337482
< [13,] -0.53672078 0.22557309 -0.33133814 -0.3682659 -1.4082097
< [14,] 1.81472398 1.30863304 0.92012489 1.9592404 2.5783685
< [15,] 0.07720730 -1.08653748 0.45718801 -0.8404493 0.2057251
---
> [1,] 0.85300597 -0.22538442 0.07270967 -0.1440551 -0.9615875
> [2,] 1.70313415 -0.04819704 1.19001008 1.6809910 -1.0132088
> [3,] -1.75081925 -0.33365931 -1.72733510 1.8354213 1.8035220
> [4,] -0.15575929 0.20248810 0.43239154 -0.6891027 -1.4343552
> [5,] -0.12954290 -0.98419670 -0.68923518 -0.6769998 -0.5551304
> [6,] -0.33034949 0.30889860 -0.38462520 -0.4921179 -1.5796319
> [7,] 0.08189456 3.18535013 0.23720553 -0.6766812 6.0277787
> [8,] 0.26673068 -0.37878111 -0.05566019 -0.5386220 -1.1090629
> [9,] -1.14832130 -0.59395010 -0.30328878 0.1331873 -1.6170652
> [10,] 0.43493369 0.40626633 0.15243113 -0.4688524 -1.9365296
> [11,] 0.02832945 -1.44822208 0.64415440 -0.9173654 2.7358109
> [12,] -1.21044619 -0.53688713 -0.61307141 0.2055182 -1.7349351
> [13,] -0.53600998 0.22524959 -0.33118372 -0.3690370 -1.4082862
> [14,] 1.81463246 1.30632858 0.91958449 1.9574877 2.5811938
> [15,] 0.07784490 -1.08535582 0.45711810 -0.8395052 0.2019637
1369c1369
< -0.233107 1.893398 1.967816 0.002073 0.052993
---
> -0.233782 1.893280 1.969602 0.001543 0.052867
1374,1376c1374,1378
< BFGSR maximization, 91 iterations
< Return code 2: successive function values within tolerance limit
< Log-Likelihood: -64.31274
---
> BFGSR maximization, 96 iterations
> Return code 3: Last step could not find a value above the current.
> Boundary of parameter space?
> Consider switching to a more robust optimisation method temporarily.
> Log-Likelihood: -64.31273
1380,1384c1382,1386
< (Intercept) -0.2331074 0.5484498 -0.4250 0.67082
< x1 1.8933978 0.3011537 6.2871 3.234e-10 ***
< x2 1.9678158 0.8188410 2.4032 0.01625 *
< logSigmaMu 0.0020726 0.2778031 0.0075 0.99405
< logSigmaNu 0.0529934 0.1630181 0.3251 0.74512
---
> (Intercept) -0.2337822 0.5483289 -0.4264 0.66985
> x1 1.8932801 0.3011173 6.2875 3.226e-10 ***
> x2 1.9696025 0.8188341 2.4054 0.01616 *
> logSigmaMu 0.0015433 0.2778758 0.0056 0.99557
> logSigmaNu 0.0528675 0.1630158 0.3243 0.74570
1400,1404c1402,1406
< (Intercept) -0.233107 0.548450 -0.425 0.6708
< x1 1.893398 0.301154 6.287 3.23e-10 ***
< x2 1.967816 0.818841 2.403 0.0163 *
< logSigmaMu 0.002073 0.277803 0.007 0.9940
< logSigmaNu 0.052993 0.163018 0.325 0.7451
---
> (Intercept) -0.233782 0.548329 -0.426 0.6698
> x1 1.893280 0.301117 6.288 3.23e-10 ***
> x2 1.969602 0.818834 2.405 0.0162 *
> logSigmaMu 0.001543 0.277876 0.006 0.9956
> logSigmaNu 0.052867 0.163016 0.324 0.7457
1408,1410c1410,1414
< BFGSR maximization, 91 iterations
< Return code 2: successive function values within tolerance limit
< Log-likelihood: -64.31274 on 5 Df
---
> BFGSR maximization, 96 iterations
> Return code 3: Last step could not find a value above the current.
> Boundary of parameter space?
> Consider switching to a more robust optimisation method temporarily.
> Log-likelihood: -64.31273 on 5 Df
1424,1428c1428,1432
< (Intercept) -0.2331 0.5484 -0.425 0.670815
< x1 1.8934 0.3012 6.287 3.23e-10 ***
< x2 1.9678 0.8188 2.403 0.016254 *
< sigmaMu 1.0021 0.2784 3.600 0.000319 ***
< sigmaNu 1.0544 0.1719 6.134 8.55e-10 ***
---
> (Intercept) -0.2338 0.5483 -0.426 0.66985
> x1 1.8933 0.3011 6.288 3.23e-10 ***
> x2 1.9696 0.8188 2.405 0.01616 *
> sigmaMu 1.0015 0.2783 3.599 0.00032 ***
> sigmaNu 1.0543 0.1719 6.134 8.55e-10 ***
1432,1434c1436,1440
< BFGSR maximization, 91 iterations
< Return code 2: successive function values within tolerance limit
< Log-likelihood: -64.31274 on 5 Df
---
> BFGSR maximization, 96 iterations
> Return code 3: Last step could not find a value above the current.
> Boundary of parameter space?
> Consider switching to a more robust optimisation method temporarily.
> Log-likelihood: -64.31273 on 5 Df
1438c1444
< -0.233107402 1.893397791 1.967815751 0.002072576 0.052993359
---
> -0.23378216 1.89328013 1.96960246 0.00154326 0.05286747
1441c1447
< -0.2331074 1.8933978 1.9678158 1.0020747 1.0544226
---
> -0.2337822 1.8932801 1.9696025 1.0015445 1.0542899
1444,1448c1450,1454
< (Intercept) 0.30079722 -0.03136868 -0.36410059 -0.015938979 -0.016354698
< x1 -0.03136868 0.09069353 0.03173538 0.035194203 0.015936650
< x2 -0.36410059 0.03173538 0.67050050 0.018587202 0.024421208
< logSigmaMu -0.01593898 0.03519420 0.01858720 0.077174550 0.004360657
< logSigmaNu -0.01635470 0.01593665 0.02442121 0.004360657 0.026574890
---
> (Intercept) 0.30066457 -0.03140943 -0.36406867 -0.015974524 -0.016384019
> x1 -0.03140943 0.09067161 0.03182344 0.035194978 0.015930682
> x2 -0.36406867 0.03182344 0.67048933 0.018652238 0.024503878
> logSigmaMu -0.01597452 0.03519498 0.01865224 0.077214979 0.004337456
> logSigmaNu -0.01638402 0.01593068 0.02450388 0.004337456 0.026574149
1451,1455c1457,1461
< (Intercept) 0.30079722 -0.03136868 -0.36410059 -0.015972048 -0.017244763
< x1 -0.03136868 0.09069353 0.03173538 0.035267221 0.016803964
< x2 -0.36410059 0.03173538 0.67050050 0.018625765 0.025750275
< sigmaMu -0.01597205 0.03526722 0.01862576 0.077495114 0.004607515
< sigmaNu -0.01724476 0.01680396 0.02575027 0.004607515 0.029546152
---
> (Intercept) 0.30066457 -0.03140943 -0.36406867 -0.015999196 -0.017273506
> x1 -0.03140943 0.09067161 0.03182344 0.035249335 0.016795557
> x2 -0.36406867 0.03182344 0.67048933 0.018681045 0.025834191
> sigmaMu -0.01599920 0.03524934 0.01868105 0.077453673 0.004579999
> sigmaNu -0.01727351 0.01679556 0.02583419 0.004579999 0.029537890
1458,1462c1464,1468
< (Intercept) -0.233107402 0.5484498 -0.425029578 6.708151e-01
< x1 1.893397791 0.3011537 6.287148362 3.233503e-10
< x2 1.967815751 0.8188410 2.403172127 1.625353e-02
< logSigmaMu 0.002072576 0.2778031 0.007460594 9.940474e-01
< logSigmaNu 0.052993359 0.1630181 0.325076601 7.451231e-01
---
> (Intercept) -0.23378216 0.5483289 -0.426353903 6.698500e-01
> x1 1.89328013 0.3011173 6.287517678 3.225823e-10
> x2 1.96960246 0.8188341 2.405374171 1.615591e-02
> logSigmaMu 0.00154326 0.2778758 0.005553777 9.955687e-01
> logSigmaNu 0.05286747 0.1630158 0.324308863 7.457042e-01
1465,1469c1471,1475
< (Intercept) -0.2331074 0.5484498 -0.4250296 6.708151e-01
< x1 1.8933978 0.3011537 6.2871484 3.233503e-10
< x2 1.9678158 0.8188410 2.4031721 1.625353e-02
< sigmaMu 1.0020747 0.2783794 3.5996722 3.186186e-04
< sigmaNu 1.0544226 0.1718899 6.1342894 8.554069e-10
---
> (Intercept) -0.2337822 0.5483289 -0.4263539 6.698500e-01
> x1 1.8932801 0.3011173 6.2875177 3.225823e-10
> x2 1.9696025 0.8188341 2.4053742 1.615591e-02
> sigmaMu 1.0015445 0.2783050 3.5987296 3.197754e-04
> sigmaNu 1.0542899 0.1718659 6.1343749 8.549467e-10
1471c1477
< 'log Lik.' -64.31274 (df=5)
---
> 'log Lik.' -64.31273 (df=5)
1476c1482
< [1] -64.31274
---
> [1] -64.31273
1480c1486
< -0.233107402 1.893397791 1.967815751 0.002072576 0.052993359
---
> -0.23378216 1.89328013 1.96960246 0.00154326 0.05286747
1484c1490
< -0.0003693622 0.0001095599 0.0070240317 -0.0050962592 -0.0099472269
---
> -0.002894857 -0.002369745 0.002610000 0.003016516 -0.002543448
1488,1492c1494,1498
< (Intercept) -9.91942006 -1.4894416 -5.3020702 -0.07398358 -0.3268811
< x1 -1.48944161 -15.1331831 -0.5447905 6.29391420 7.6264365
< x2 -5.30207023 -0.5447905 -4.3879876 0.14968338 1.0715235
< logSigmaMu -0.07398357 6.2939142 0.1496834 -15.80210764 -1.3645124
< logSigmaNu -0.32688108 7.6264365 1.0715235 -1.36451242 -43.1649425
---
> (Intercept) -9.92921213 -1.4915778 -5.3068262 -0.07430279 -0.3220588
> x1 -1.49157779 -15.1380768 -0.5453987 6.29452164 7.6308755
> x2 -5.30682618 -0.5453987 -4.3907451 0.15071751 1.0791686
> logSigmaMu -0.07430279 6.2945216 0.1507175 -15.79417345 -1.3802899
> logSigmaNu -0.32205878 7.6308755 1.0791686 -1.38028985 -43.1734818
1495c1501
< [1] 2
---
> [1] 3
1498c1504
< [1] "successive function values within tolerance limit"
---
> [1] "Last step could not find a value above the current.\nBoundary of parameter space? \nConsider switching to a more robust optimisation method temporarily."
1501c1507,1533
< NULL
---
> $last.step$theta0
> (Intercept) x1 x2 logSigmaMu logSigmaNu
> -0.233805135 1.893310605 1.969641022 0.001551443 0.052675686
>
> $last.step$f0
> [1] -64.31273
> attr(,"gradient")
> [,1] [,2] [,3] [,4] [,5]
> [1,] -0.85417510 -0.10609337 -0.18146777 -0.0235494 -0.8369719
> [2,] -1.41680128 -0.02702422 -0.97196805 1.4567554 -1.1645981
> [3,] 1.29745993 1.02088535 0.92544703 1.0920903 0.1540724
> [4,] 0.07075595 -0.25207707 -0.39840982 -0.7015966 -1.8261020
> [5,] 0.08922410 0.80745931 0.64769792 -0.6906630 -0.2847701
> [6,] 0.55923778 0.49468626 0.42897976 -0.2914444 -0.3603540
> [7,] -0.12034788 -3.06219247 -0.23674144 -0.7063845 6.3455056
> [8,] -0.20961505 0.33550846 0.08326478 -0.5906480 -1.0295346
> [9,] 1.03436546 0.66021829 0.28832659 0.1971790 -1.2970105
> [10,] -0.42828980 -0.58564682 -0.11733332 -0.3957152 -1.8006439
> [11,] -0.04064163 1.09509187 -0.50821521 -0.8668820 2.0017961
> [12,] 1.14034027 0.50533928 0.83221911 0.5852838 -0.7450190
> [13,] 0.53486256 -0.28181457 0.34791505 -0.2865027 -1.4336469
> [14,] -1.63819150 -1.34761986 -0.83803596 2.1201245 2.7646850
> [15,] -0.02103951 0.73904950 -0.29933851 -0.8946959 -0.4814000
>
> $last.step$climb
> [1] -394657.2 523581.9 662476.4 140569.0 -3294770.3
>
1508c1540
< [1] 91
---
> [1] 96
1515,1529c1547,1561
< [1,] -0.85343389 -0.10543621 -0.1810232 -0.02415723 -0.8373100
< [2,] -1.41520029 -0.02593378 -0.9705126 1.45402225 -1.1649354
< [3,] 1.29668712 1.02098251 0.9251493 1.09170119 0.1536952
< [4,] 0.07070341 -0.25178865 -0.3978885 -0.70124078 -1.8289343
< [5,] 0.08917641 0.80755474 0.6478335 -0.69082429 -0.2836389
< [6,] 0.55927319 0.49427180 0.4290449 -0.29109259 -0.3606708
< [7,] -0.12043475 -3.06004892 -0.2366143 -0.70647597 6.3402899
< [8,] -0.20955203 0.33559074 0.0833811 -0.59082951 -1.0292834
< [9,] 1.03365080 0.66018497 0.2881534 0.19632574 -1.2973028
< [10,] -0.42754254 -0.58515711 -0.1169174 -0.39609045 -1.8009283
< [11,] -0.04044580 1.09424230 -0.5077064 -0.86712703 1.9991531
< [12,] 1.13954442 0.50460058 0.8321523 0.58454371 -0.7450017
< [13,] 0.53457664 -0.28161720 0.3478140 -0.28637989 -1.4342658
< [14,] -1.63662115 -1.34546074 -0.8370071 2.11772328 2.7619772
< [15,] -0.02075091 0.73812451 -0.2988351 -0.89519469 -0.4827913
---
> [1,] -0.85399301 -0.10602099 -0.18140766 -0.02364687 -0.8371385
> [2,] -1.41680831 -0.02700922 -0.97193915 1.45664700 -1.1645431
> [3,] 1.29738032 1.02095947 0.92539297 1.09190281 0.1539769
> [4,] 0.07100562 -0.25197861 -0.39807733 -0.70154825 -1.8266607
> [5,] 0.08922699 0.80745668 0.64756678 -0.69055935 -0.2850413
> [6,] 0.55925418 0.49480489 0.42892323 -0.29147726 -0.3608594
> [7,] -0.12039508 -3.06089075 -0.23666324 -0.70622873 6.3420715
> [8,] -0.20969533 0.33555238 0.08322106 -0.59050851 -1.0297117
> [9,] 1.03428932 0.66016070 0.28831450 0.19721031 -1.2971304
> [10,] -0.42828624 -0.58538485 -0.11736408 -0.39582567 -1.8009247
> [11,] -0.04081588 1.09472020 -0.50816401 -0.86667778 2.0006839
> [12,] 1.14045635 0.50528295 0.83226925 0.58550194 -0.7452782
> [13,] 0.53470207 -0.28162570 0.34780933 -0.28674186 -1.4339655
> [14,] -1.63795687 -1.34717561 -0.83791582 2.11940059 2.7641334
> [15,] -0.02125898 0.73877872 -0.29935581 -0.89443186 -0.4821556
1596,1600c1628,1632
< [1] "Component 1: Mean relative difference: 8.724597e-07"
< [2] "Component 2: Mean relative difference: 0.001379892"
< [3] "Component 3: Mean relative difference: 0.6679543"
< [4] "Component 4: Mean relative difference: 0.001175551"
< [5] "Component 9: Mean relative difference: 0.234375"
---
> [1] "Component 1: Mean relative difference: 1.585932e-07"
> [2] "Component 2: Mean relative difference: 0.0009942645"
> [3] "Component 3: Mean relative difference: 5.267562"
> [4] "Component 4: Mean relative difference: 0.000453646"
> [5] "Component 9: Mean relative difference: 0.2352941"
1602c1634
< [1] "Mean relative difference: 0.00105602"
---
> [1] "Mean relative difference: 0.0006692936"
1636c1668
< [1] -6.386315e-05
---
> [1] 1.160884e-05
1638c1670
< [1] 6.386315e-05
---
> [1] -1.160884e-05
1662c1694
< -0.220974 1.640458 2.105688 -0.167737 -0.001252
---
> -0.223438 1.640494 2.109440 -0.167351 -0.001139
1667,1671c1699,1701
< BFGSR maximization, 80 iterations
< Return code 3: Last step could not find a value above the current.
< Boundary of parameter space?
< Consider switching to a more robust optimisation method temporarily.
< Log-Likelihood: -71.1926
---
> BFGSR maximization, 91 iterations
> Return code 2: successive function values within tolerance limit
> Log-Likelihood: -71.19256
1675,1679c1705,1709
< (Intercept) -0.2209735 0.4723040 -0.4679 0.639883
< x1 1.6404576 0.2110125 7.7742 7.591e-15 ***
< x2 2.1056881 0.6847093 3.0753 0.002103 **
< logSigmaMu -0.1677375 0.2716019 -0.6176 0.536848
< logSigmaNu -0.0012523 0.1322670 -0.0095 0.992446
---
> (Intercept) -0.2234379 0.4725748 -0.4728 0.63635
> x1 1.6404941 0.2110522 7.7729 7.669e-15 ***
> x2 2.1094395 0.6848755 3.0800 0.00207 **
> logSigmaMu -0.1673511 0.2714906 -0.6164 0.53762
> logSigmaNu -0.0011386 0.1322729 -0.0086 0.99313
1694,1698c1724,1728
< (Intercept) -0.220974 0.472304 -0.468 0.6399
< x1 1.640458 0.211013 7.774 7.59e-15 ***
< x2 2.105688 0.684709 3.075 0.0021 **
< logSigmaMu -0.167737 0.271602 -0.618 0.5368
< logSigmaNu -0.001252 0.132267 -0.009 0.9924
---
> (Intercept) -0.223438 0.472575 -0.473 0.63635
> x1 1.640494 0.211052 7.773 7.67e-15 ***
> x2 2.109440 0.684875 3.080 0.00207 **
> logSigmaMu -0.167351 0.271491 -0.616 0.53762
> logSigmaNu -0.001139 0.132273 -0.009 0.99313
1702,1706c1732,1734
< BFGSR maximization, 80 iterations
< Return code 3: Last step could not find a value above the current.
< Boundary of parameter space?
< Consider switching to a more robust optimisation method temporarily.
< Log-likelihood: -71.1926 on 5 Df
---
> BFGSR maximization, 91 iterations
> Return code 2: successive function values within tolerance limit
> Log-likelihood: -71.19256 on 5 Df
1709c1737
< 'log Lik.' -71.1926 (df=5)
---
> 'log Lik.' -71.19256 (df=5)
1711c1739
< [1] -36.0000 152.3852
---
> [1] -36.0000 152.3851
1714c1742
< [1] -71.1926
---
> [1] -71.19256
1718c1746
< -0.220973530 1.640457585 2.105688092 -0.167737454 -0.001252266
---
> -0.223437886 1.640494086 2.109439512 -0.167351143 -0.001138553
1722c1750
< -0.007303906 -0.004094840 0.009557131 0.002603713 0.006875225
---
> -0.0023645994 0.0002134735 0.0043525355 -0.0012274752 -0.0003310896
1726,1730c1754,1758
< (Intercept) -13.801744 -4.348961 -7.533467 -1.100998 -1.945761
< x1 -4.348961 -25.821004 -2.059257 4.652784 4.060753
< x2 -7.533467 -2.059257 -6.269100 -0.139852 -1.072475
< logSigmaMu -1.100998 4.652784 -0.139852 -14.917158 -3.782947
< logSigmaNu -1.945761 4.060753 -1.072475 -3.782947 -58.846702
---
> (Intercept) -13.788369 -4.345893 -7.5273217 -1.1108512 -1.941872
> x1 -4.345893 -25.811539 -2.0571716 4.6503075 4.052490
> x2 -7.527322 -2.057172 -6.2654750 -0.1435365 -1.057070
> logSigmaMu -1.110851 4.650307 -0.1435365 -14.9303962 -3.772496
> logSigmaNu -1.941872 4.052490 -1.0570698 -3.7724962 -58.832591
1733c1761
< [1] 3
---
> [1] 2
1736c1764
< [1] "Last step could not find a value above the current.\nBoundary of parameter space? \nConsider switching to a more robust optimisation method temporarily."
---
> [1] "successive function values within tolerance limit"
1739,1765c1767
< $last.step$theta0
< (Intercept) x1 x2 logSigmaMu logSigmaNu
< -0.2210935585 1.6403254656 2.1058489222 -0.1676614571 -0.0008586637
<
< $last.step$f0
< [1] -71.1926
< attr(,"gradient")
< [,1] [,2] [,3] [,4] [,5]
< [1,] -0.50876527 0.08928477 0.10368717 -0.39396798 -0.52981976
< [2,] -1.81731073 0.06735318 -1.24704946 1.79795113 -0.96133745
< [3,] 1.78468487 0.48565044 1.77007797 1.73236978 1.89749434
< [4,] 0.15222438 -0.16234004 -0.39515529 -0.73670389 -1.58907751
< [5,] 0.08144697 1.03920276 0.69831136 -0.67791800 -0.44484280
< [6,] 0.33280505 -0.23283619 0.37410012 -0.53977261 -1.57372590
< [7,] -0.18146435 -3.02744843 -0.24859841 -0.62168118 5.47502863
< [8,] 0.01859333 -0.00405288 0.01063418 -0.41746718 -0.58194012
< [9,] 1.11537081 0.66647030 0.29563717 0.06289465 -1.68664493
< [10,] -0.53841264 -0.42044278 -0.20447414 -0.40615819 -1.97453276
< [11,] -0.08367427 1.37709735 -0.64734574 -0.82238229 2.49067695
< [12,] 1.25923652 0.53118395 0.67034459 0.23126477 -1.79492519
< [13,] 0.44641340 -0.16319537 0.28632375 -0.46864577 -1.45077852
< [14,] -1.89287049 -1.28622512 -0.96213676 1.98263580 2.68180132
< [15,] -0.17541214 1.04175440 -0.49506420 -0.72294168 0.02558265
<
< $last.step$climb
< [1] -2062077 -2269801 2763043 1305624 6762039
<
---
> NULL
1772c1774
< [1] 80
---
> [1] 91
1779,1793c1781,1795
< [1,] -0.50912045 0.089247505 0.10377274 -0.39383839 -0.5289532
< [2,] -1.81772069 0.067227915 -1.24741076 1.79869148 -0.9615202
< [3,] 1.78541738 0.484722898 1.77105090 1.73386429 1.9001980
< [4,] 0.15200493 -0.162502300 -0.39566214 -0.73687426 -1.5877964
< [5,] 0.08155816 1.039388174 0.69883647 -0.67805464 -0.4436553
< [6,] 0.33258959 -0.233911067 0.37421054 -0.53980684 -1.5722671
< [7,] -0.18149189 -3.030250682 -0.24879224 -0.62184645 5.4816890
< [8,] 0.01860344 -0.004055083 0.01063996 -0.41762271 -0.5817843
< [9,] 1.11581756 0.666511293 0.29576493 0.06306042 -1.6863225
< [10,] -0.53865309 -0.421148026 -0.20454111 -0.40595432 -1.9738204
< [11,] -0.08358821 1.377840216 -0.64762729 -0.82266516 2.4939436
< [12,] 1.25939156 0.531283741 0.67044480 0.23116432 -1.7940987
< [13,] 0.44667456 -0.163547654 0.28650766 -0.46839191 -1.4500244
< [14,] -1.89355453 -1.287295609 -0.96242724 1.98400492 2.6843489
< [15,] -0.17523221 1.042393841 -0.49521009 -0.72312704 0.0269383
---
> [1,] -0.50851468 0.088549089 0.10332418 -0.39424112 -0.5321531
> [2,] -1.81705349 0.066630144 -1.24744468 1.79880183 -0.9613088
> [3,] 1.78438158 0.484622552 1.76921902 1.73324126 1.8938711
> [4,] 0.15178686 -0.162863846 -0.39633296 -0.73697159 -1.5844197
> [5,] 0.08174549 1.038619943 0.69766179 -0.67810229 -0.4478988
> [6,] 0.33238733 -0.231741427 0.37360317 -0.53970858 -1.5740604
> [7,] -0.18005740 -3.029939879 -0.24845697 -0.62247948 5.4823898
> [8,] 0.01878553 -0.004094775 0.01074411 -0.41775131 -0.5816437
> [9,] 1.11613611 0.666458518 0.29576147 0.06379078 -1.6850635
> [10,] -0.53761405 -0.420066528 -0.20419807 -0.40660173 -1.9743628
> [11,] -0.08280126 1.379236916 -0.64772340 -0.82356321 2.4973552
> [12,] 1.25885598 0.532122184 0.66915527 0.23058826 -1.7934726
> [13,] 0.44678737 -0.163413157 0.28637417 -0.46810019 -1.4504984
> [14,] -1.89274932 -1.287262705 -0.96222366 1.98378247 2.6810702
> [15,] -0.17444065 1.043356443 -0.49511091 -0.72391258 0.0298645
Running 'censRegTest.R'
Comparing 'censRegTest.Rout' to 'censRegTest.Rout.save' ...32c32
< -3.932479e-12 -1.208372e-10 -2.727575e-11 -1.302044e-11 -1.581076e-11
---
> -3.932352e-12 -1.208755e-10 -2.731102e-11 -1.302267e-11 -1.581067e-11
34c34
< -1.680000e-11 -3.830020e-12
---
> -1.679983e-11 -3.828576e-12
1443,1458c1443,1458
< (Intercept) age yearsmarried religiousness occupation
< (Intercept) 7.51552372 -0.1196798499 0.089357154 -3.970038e-01 -0.176564351
< age -0.11967985 0.0062557405 -0.008052616 5.380018e-04 -0.003932012
< yearsmarried 0.08935715 -0.0080526163 0.018095076 -1.006372e-02 0.003581751
< religiousness -0.39700379 0.0005380018 -0.010063723 1.630153e-01 0.005214883
< occupation -0.17656435 -0.0039320120 0.003581751 5.214883e-03 0.064731952
< rating -0.61644229 0.0011114966 0.004771647 -2.571295e-05 -0.006192755
< logSigma 0.00696809 -0.0005561255 0.001594861 -4.944751e-03 0.000892592
< rating logSigma
< (Intercept) -6.164423e-01 0.0069680896
< age 1.111497e-03 -0.0005561255
< yearsmarried 4.771647e-03 0.0015948607
< religiousness -2.571295e-05 -0.0049447513
< occupation -6.192755e-03 0.0008925920
< rating 1.663236e-01 -0.0068779111
< logSigma -6.877911e-03 0.0045021647
---
> (Intercept) age yearsmarried religiousness
> (Intercept) 7.515523717 -0.1196798498 0.089357154 -0.3970037876
> age -0.119679850 0.0062557405 -0.008052616 0.0005380018
> yearsmarried 0.089357154 -0.0080526163 0.018095076 -0.0100637228
> religiousness -0.397003788 0.0005380018 -0.010063723 0.1630153148
> occupation -0.176564351 -0.0039320120 0.003581751 0.0052148835
> rating -0.616442290 0.0011114966 0.004771647 -0.0000257130
> logSigma 0.006968089 -0.0005561255 0.001594861 -0.0049447512
> occupation rating logSigma
> (Intercept) -0.176564351 -0.616442290 0.0069680894
> age -0.003932012 0.001111497 -0.0005561255
> yearsmarried 0.003581751 0.004771647 0.0015948607
> religiousness 0.005214883 -0.000025713 -0.0049447512
> occupation 0.064731952 -0.006192755 0.0008925920
> rating -0.006192755 0.166323611 -0.0068779111
> logSigma 0.000892592 -0.006877911 0.0045021647
1461,1467c1461,1467
< (Intercept) 7.51552372 -0.1196798499 0.089357154 -3.970038e-01 -0.176564351
< age -0.11967985 0.0062557405 -0.008052616 5.380018e-04 -0.003932012
< yearsmarried 0.08935715 -0.0080526163 0.018095076 -1.006372e-02 0.003581751
< religiousness -0.39700379 0.0005380018 -0.010063723 1.630153e-01 0.005214883
< occupation -0.17656435 -0.0039320120 0.003581751 5.214883e-03 0.064731952
< rating -0.61644229 0.0011114966 0.004771647 -2.571295e-05 -0.006192755
< sigma 0.05746639 -0.0045864114 0.013152944 -4.077976e-02 0.007361278
---
> (Intercept) 7.51552372 -0.1196798498 0.089357154 -0.3970037876 -0.176564351
> age -0.11967985 0.0062557405 -0.008052616 0.0005380018 -0.003932012
> yearsmarried 0.08935715 -0.0080526163 0.018095076 -0.0100637228 0.003581751
> religiousness -0.39700379 0.0005380018 -0.010063723 0.1630153148 0.005214883
> occupation -0.17656435 -0.0039320120 0.003581751 0.0052148835 0.064731952
> rating -0.61644229 0.0011114966 0.004771647 -0.0000257130 -0.006192755
> sigma 0.05746639 -0.0045864114 0.013152944 -0.0407797607 0.007361278
1469,1475c1469,1475
< (Intercept) -6.164423e-01 0.057466394
< age 1.111497e-03 -0.004586411
< yearsmarried 4.771647e-03 0.013152944
< religiousness -2.571295e-05 -0.040779761
< occupation -6.192755e-03 0.007361278
< rating 1.663236e-01 -0.056722685
< sigma -5.672269e-02 0.306211731
---
> (Intercept) -0.616442290 0.057466393
> age 0.001111497 -0.004586411
> yearsmarried 0.004771647 0.013152944
> religiousness -0.000025713 -0.040779761
> occupation -0.006192755 0.007361278
> rating 0.166323611 -0.056722685
> sigma -0.056722685 0.306211731
1501c1501
< religiousness 0.24868749 -0.19433695 0.24013928 -0.05180838 0.39683239
---
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17871,17872c17871,17872
< religiousness3 -5.3653370
< religiousness4 -13.0149352
---
> religiousness3 -5.3653371
> religiousness4 -13.0149353
17878,17885c17878,17885
< (Intercept) 10.31538095 -0.200651746 0.1686842101 -1.1319277007
< age -0.20065175 0.009401332 -0.0116862348 -0.0126882104
< yearsmarried 0.16868421 -0.011686235 0.0222169680 0.0020910174
< religiousness2 -1.13192770 -0.012688210 0.0020910174 2.3677473929
< religiousness3 -1.67391450 0.009680115 -0.0335847975 1.5816089430
< religiousness4 -1.63520649 0.020356049 -0.0571329529 1.5834255166
< occupation -0.21663046 -0.004766186 0.0071748020 -0.0149992594
< rating -0.70525290 0.001990725 0.0047558306 0.0059794240
---
> (Intercept) 10.31538093 -0.200651745 0.1686842095 -1.1319277037
> age -0.20065175 0.009401332 -0.0116862348 -0.0126882102
> yearsmarried 0.16868421 -0.011686235 0.0222169680 0.0020910171
> religiousness2 -1.13192770 -0.012688210 0.0020910171 2.3677473930
> religiousness3 -1.67391450 0.009680115 -0.0335847979 1.5816089425
> religiousness4 -1.63520649 0.020356049 -0.0571329533 1.5834255179
> occupation -0.21663046 -0.004766186 0.0071748020 -0.0149992598
> rating -0.70525290 0.001990725 0.0047558307 0.0059794244
17888c17888
< (Intercept) -1.673914502 -1.635206490 -0.2166304578 -0.7052528967
---
> (Intercept) -1.673914504 -1.635206495 -0.2166304561 -0.7052528970
17890,17895c17890,17895
< yearsmarried -0.033584798 -0.057132953 0.0071748020 0.0047558306
< religiousness2 1.581608943 1.583425517 -0.0149992594 0.0059794240
< religiousness3 2.344052055 1.676859201 0.0085145599 0.0042720441
< religiousness4 1.676859201 2.490749122 -0.0079195863 -0.0274176775
< occupation 0.008514560 -0.007919586 0.0698641100 0.0025917526
< rating 0.004272044 -0.027417678 0.0025917526 0.1682841971
---
> yearsmarried -0.033584798 -0.057132953 0.0071748020 0.0047558307
> religiousness2 1.581608943 1.583425518 -0.0149992598 0.0059794244
> religiousness3 2.344052053 1.676859201 0.0085145595 0.0042720444
> religiousness4 1.676859201 2.490749125 -0.0079195867 -0.0274176772
> occupation 0.008514559 -0.007919587 0.0698641100 0.0025917525
> rating 0.004272044 -0.027417677 0.0025917525 0.1682841972
17898c17898
< (Intercept) -0.0520571911
---
> (Intercept) -0.0520571909
17902c17902
< religiousness3 -0.0020934236
---
> religiousness3 -0.0020934237
- checking for unstated dependencies in vignettes ... OK
- checking package vignettes in 'inst/doc' ... OK
- checking running R code from vignettes ... OK
- checking re-building of vignette PDFs ... NOTE
Error in re-building vignettes:
...
backsolve
Loading required package: nlme
Loading required package: Formula
Loading required package: MASS
Loading required package: sandwich
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from 'package:base':
as.Date, as.Date.numeric
Error in texi2dvi(file = file, pdf = TRUE, clean = clean, quiet = quiet, :
Running 'texi2dvi' on 'censReg.tex' failed.
LaTeX errors:
/censReg.Rcheck/vign_test/censReg/inst/doc/censReg.tex:7: LaTeX Error: Missing
\begin{document}.
See the LaTeX manual or LaTeX Companion for explanation.
Type H <return> for immediate help.
Calls: buildVignettes -> texi2pdf -> texi2dvi
Execution halted
- checking PDF version of manual ... OK
NOTE: There were 2 notes.
See
'/Volumes/Tiger/Builds/Rdev-web/QA/Simon/packages/leopard-universal/results/2.15/censReg.Rcheck/00check.log'
for details.
- elapsed time (check, wall clock): 2:06