• using R version 2.14.2 RC (2012-02-23 r58468)
• using platform: i686-pc-linux-gnu (32-bit)
• using session charset: UTF-8
• checking for file ‘censReg/DESCRIPTION’ ... OK
• this is package ‘censReg’ version ‘0.5-6’
• 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 examples ... OK
• checking for unstated dependencies in tests ... OK
• checking tests ... OK
  Running ‘censRegPanelLargerTest.R’
  Comparing ‘censRegPanelLargerTest.Rout’ to ‘censRegPanelLargerTest.Rout.save’ ...5,18d4
  <
  < Attaching package: 'bdsmatrix'
  <
  < The following object(s) are masked from 'package:base':
  <
  < backsolve
  <
  <
  < Attaching package: 'zoo'
  <
  < The following object(s) are masked from 'package:base':
  <
  < as.Date, as.Date.numeric
  <
  84c70
  < BFGSR maximization, 22 iterations
  ---
  > BFGSR maximization, 15 iterations
  90,94c76,80
  < (Intercept) -1.086421 0.226316 -4.8005 1.583e-06 ***
  < x1 2.069543 0.096852 21.3681 < 2.2e-16 ***
  < x2 3.114673 0.326638 9.5356 < 2.2e-16 ***
  < logSigmaMu -0.105526 0.130947 -0.8059 0.4203
  < logSigmaNu 0.025589 0.069591 0.3677 0.7131
  ---
  > (Intercept) -1.086695 0.226326 -4.8015 1.575e-06 ***
  > x1 2.069552 0.096853 21.3679 < 2.2e-16 ***
  > x2 3.115097 0.326649 9.5365 < 2.2e-16 ***
  > logSigmaMu -0.105561 0.130954 -0.8061 0.4202
  > logSigmaNu 0.025601 0.069593 0.3679 0.7130
  Running ‘censRegPanelTest.R’
  Comparing ‘censRegPanelTest.Rout’ to ‘censRegPanelTest.Rout.save’ ...5,18d4
  <
  < Attaching package: 'bdsmatrix'
  <
  < The following object(s) are masked from 'package:base':
  <
  < backsolve
  <
  <
  < Attaching package: 'zoo'
  <
  < The following object(s) are masked from 'package:base':
  <
  < as.Date, as.Date.numeric
  <
  559c545
  < -0.37148 1.68048 2.24941 -0.12906 -0.01243
  ---
  > -0.36562 1.68000 2.24054 -0.12955 -0.01241
  564c550
  < BFGSR maximization, 70 iterations
  ---
  > BFGSR maximization, 10 iterations
  566c552
  < Log-Likelihood: -73.19891
  ---
  > Log-Likelihood: -73.19882
  570,574c556,560
  < (Intercept) -0.371476 0.475064 -0.7819 0.4342440
  < x1 1.680478 0.209293 8.0293 9.803e-16 ***
  < x2 2.249408 0.674173 3.3365 0.0008483 ***
  < logSigmaMu -0.129063 0.257968 -0.5003 0.6168602
  < logSigmaNu -0.012426 0.129699 -0.0958 0.9236740
  ---
  > (Intercept) -0.365623 0.474457 -0.7706 0.4409359
  > x1 1.680004 0.209222 8.0298 9.767e-16 ***
  > x2 2.240544 0.673889 3.3248 0.0008848 ***
  > logSigmaMu -0.129547 0.258070 -0.5020 0.6156791
  > logSigmaNu -0.012408 0.129690 -0.0957 0.9237792
  589,593c575,579
  < (Intercept) -0.37148 0.47506 -0.782 0.434244
  < x1 1.68048 0.20929 8.029 9.8e-16 ***
  < x2 2.24941 0.67417 3.337 0.000848 ***
  < logSigmaMu -0.12906 0.25797 -0.500 0.616860
  < logSigmaNu -0.01243 0.12970 -0.096 0.923674
  ---
  > (Intercept) -0.36562 0.47446 -0.771 0.440936
  > x1 1.68000 0.20922 8.030 9.77e-16 ***
  > x2 2.24054 0.67389 3.325 0.000885 ***
  > logSigmaMu -0.12955 0.25807 -0.502 0.615679
  > logSigmaNu -0.01241 0.12969 -0.096 0.923779
  597c583
  < BFGSR maximization, 70 iterations
  ---
  > BFGSR maximization, 10 iterations
  599c585
  < Log-likelihood: -73.19891 on 5 Df
  ---
  > Log-likelihood: -73.19882 on 5 Df
  603c589
  < [1] -73.19891
  ---
  > [1] -73.19882
  607c593
  < -0.3714762 1.6804785 2.2494084 -0.1290626 -0.0124261
  ---
  > -0.36562324 1.68000398 2.24054396 -0.12954711 -0.01240798
  611c597
  < 0.0102242312 -0.0039464219 -0.0137571152 0.0009714823 0.0050792785
  ---
  > 1.752053e-07 6.964484e-07 -3.816903e-07 9.595136e-07 -6.239532e-06
  615,619c601,605
  < (Intercept) -13.304847 -4.095310 -7.3011509 -2.1434951 -1.2841240
  < x1 -4.095310 -26.067680 -1.9882837 4.4811980 4.7676575
  < x2 -7.301151 -1.988284 -6.2333379 -0.6368505 -0.4372755
  < logSigmaMu -2.143495 4.481198 -0.6368505 -16.6887635 -3.7206999
  < logSigmaNu -1.284124 4.767658 -0.4372755 -3.7206999 -61.0588264
  ---
  > (Intercept) -13.321986 -4.096607 -7.3075700 -2.1079020 -1.3088195
  > x1 -4.096607 -26.076783 -1.9905303 4.4849634 4.7620874
  > x2 -7.307570 -1.990530 -6.2362548 -0.6238247 -0.4803056
  > logSigmaMu -2.107902 4.484963 -0.6238247 -16.6581988 -3.7224013
  > logSigmaNu -1.308819 4.762087 -0.4803056 -3.7224012 -61.0683295
  635c621
  < [1] 70
  ---
  > [1] 10
  642,656c628,642
  < [1,] -0.85197513 0.22300109 -0.07383855 -0.1446581 -0.9694365
  < [2,] -1.70293911 0.04598652 -1.19106512 1.6826450 -1.0123496
  < [3,] 1.74991333 0.33249754 1.72446674 1.8354630 1.7937608
  < [4,] 0.15549091 -0.20359441 -0.43404868 -0.6888761 -1.4257673
  < [5,] 0.13008069 0.98238046 0.68696694 -0.6768022 -0.5635666
  < [6,] 0.32998714 -0.30569851 0.38366318 -0.4918905 -1.5824562
  < [7,] -0.07915292 -3.18707762 -0.23672001 -0.6773847 6.0358379
  < [8,] -0.26508915 0.37745140 0.05582964 -0.5392448 -1.1082645
  < [9,] 1.14905374 0.59327311 0.30328674 0.1354696 -1.6148698
  < [10,] -0.43327799 -0.40480577 -0.15191875 -0.4700398 -1.9366805
  < [11,] -0.02755838 1.45095916 -0.64488192 -0.9187595 2.7444617
  < [12,] 1.20974890 0.53872518 0.61056530 0.2047218 -1.7328470
  < [13,] 0.53716547 -0.22567488 0.33142078 -0.3678065 -1.4082285
  < [14,] -1.81447672 -1.30897736 -0.92016674 1.9592877 2.5765524
  < [15,] -0.07674655 1.08760767 -0.45731667 -0.8411536 0.2089329
  ---
  > [1,] -0.85308347 0.22558499 -0.07261018 -0.1440032 -0.9609406
  > [2,] -1.70309377 0.04839407 -1.18987568 1.6807832 -1.0133140
  > [3,] 1.75084257 0.33367521 1.72755756 1.8353810 1.8043722
  > [4,] 0.15577754 -0.20240005 -0.43224639 -0.6891080 -1.4351384
  > [5,] 0.12950028 0.98433611 0.68943609 -0.6770203 -0.5543808
  > [6,] 0.33035927 -0.30928374 0.38471150 -0.4921375 -1.5793720
  > [7,] -0.08212546 -3.18521797 -0.23724723 -0.6766314 6.0271914
  > [8,] -0.26685304 0.37888545 0.05565469 -0.5385827 -1.1091112
  > [9,] 1.14824187 0.59396378 0.30328558 0.1329804 -1.6172740
  > [10,] -0.43505399 -0.40640581 -0.15245987 -0.4687583 -1.9364985
  > [11,] -0.02839190 1.44795720 -0.64407725 -0.9172652 2.7349914
  > [12,] 1.21047895 0.53669838 0.61328533 0.2055545 -1.7351239
  > [13,] 0.53592708 -0.22523038 0.33117481 -0.3691167 -1.4082836
  > [14,] -1.81460685 -1.30608988 -0.91951004 1.9573173 2.5815575
  > [15,] -0.07791890 1.08513335 -0.45707930 -0.8393920 0.2013182
  745c731
  < 4.63332 1.68005 2.24212 -0.12940 -0.01231
  ---
  > 4.63438 1.68000 2.24054 -0.12955 -0.01241
  750c736
  < BFGSR maximization, 97 iterations
  ---
  > BFGSR maximization, 10 iterations
  752c738
  < Log-Likelihood: -73.19883
  ---
  > Log-Likelihood: -73.19882
  756,760c742,746
  < (Intercept) 4.63332 0.47460 9.7627 < 2.2e-16 ***
  < x1 1.68005 0.20925 8.0289 9.833e-16 ***
  < x2 2.24212 0.67400 3.3266 0.0008792 ***
  < logSigmaMu -0.12940 0.25806 -0.5014 0.6160643
  < logSigmaNu -0.01231 0.12970 -0.0949 0.9243848
  ---
  > (Intercept) 4.634377 0.474457 9.7677 < 2.2e-16 ***
  > x1 1.680004 0.209222 8.0298 9.767e-16 ***
  > x2 2.240544 0.673889 3.3248 0.0008848 ***
  > logSigmaMu -0.129547 0.258070 -0.5020 0.6156791
  > logSigmaNu -0.012408 0.129690 -0.0957 0.9237792
  775,779c761,765
  < (Intercept) 4.63332 0.47460 9.763 < 2e-16 ***
  < x1 1.68005 0.20925 8.029 9.83e-16 ***
  < x2 2.24212 0.67400 3.327 0.000879 ***
  < logSigmaMu -0.12940 0.25806 -0.501 0.616064
  < logSigmaNu -0.01231 0.12970 -0.095 0.924385
  ---
  > (Intercept) 4.63438 0.47446 9.768 < 2e-16 ***
  > x1 1.68000 0.20922 8.030 9.77e-16 ***
  > x2 2.24054 0.67389 3.325 0.000885 ***
  > logSigmaMu -0.12955 0.25807 -0.502 0.615679
  > logSigmaNu -0.01241 0.12969 -0.096 0.923779
  783c769
  < BFGSR maximization, 97 iterations
  ---
  > BFGSR maximization, 10 iterations
  785c771
  < Log-likelihood: -73.19883 on 5 Df
  ---
  > Log-likelihood: -73.19882 on 5 Df
  789c775
  < 4.63331991 1.68004659 2.24211633 -0.12940158 -0.01231032
  ---
  > 4.63437676 1.68000398 2.24054396 -0.12954711 -0.01240798
  792c778
  < 4.6333199 1.6800466 2.2421163 0.8786211 0.9877651
  ---
  > 4.6343768 1.6800040 2.2405440 0.8784932 0.9876687
  795,799c781,785
  < (Intercept) 0.225241290 -0.020595368 -0.254722939 -0.023877828 -0.002992472
  < x1 -0.020595368 0.043785267 0.008586665 0.013409020 0.002970325
  < x2 -0.254722939 0.008586665 0.454274550 0.017213666 0.001546121
  < logSigmaMu -0.023877828 0.013409020 0.017213666 0.066595994 -0.002635273
  < logSigmaNu -0.002992472 0.002970325 0.001546121 -0.002635273 0.016822765
  ---
  > (Intercept) 0.225109676 -0.020570169 -0.254602918 -0.023824169 -0.002973956
  > x1 -0.020570169 0.043773979 0.008562227 0.013404084 0.002969957
  > x2 -0.254602918 0.008562227 0.454125958 0.017179555 0.001505443
  > logSigmaMu -0.023824169 0.013404084 0.017179555 0.066600343 -0.002638875
  > logSigmaNu -0.002973956 0.002969957 0.001505443 -0.002638875 0.016819446
  802,806c788,792
  < (Intercept) 0.22524129 -0.020595368 -0.254722939 -0.020979562 -0.002955860
  < x1 -0.02059537 0.043785267 0.008586665 0.011781447 0.002933984
  < x2 -0.25472294 0.008586665 0.454274550 0.015124290 0.001527205
  < sigmaMu -0.02097956 0.011781447 0.015124290 0.051410440 -0.002287078
  < sigmaNu -0.00295586 0.002933984 0.001527205 -0.002287078 0.016413635
  ---
  > (Intercept) 0.225109676 -0.020570169 -0.254602918 -0.020929371 -0.002937284
  > x1 -0.020570169 0.043773979 0.008562227 0.011775397 0.002933333
  > x2 -0.254602918 0.008562227 0.454125958 0.015092122 0.001486879
  > sigmaMu -0.020929371 0.011775397 0.015092122 0.051398836 -0.002289647
  > sigmaNu -0.002937284 0.002933333 0.001486879 -0.002289647 0.016407191
  808c794
  < 'log Lik.' -73.19883 (df=5)
  ---
  > 'log Lik.' -73.19882 (df=5)
  810c796
  < [1] -40.0000 156.3977
  ---
  > [1] -40.0000 156.3976
  813c799
  < [1] -73.19883
  ---
  > [1] -73.19882
  817c803
  < 4.63331991 1.68004659 2.24211633 -0.12940158 -0.01231032
  ---
  > 4.63437676 1.68000398 2.24054396 -0.12954711 -0.01240798
  821c807
  < 0.001979108 0.001206912 -0.002305339 -0.001347563 -0.005676405
  ---
  > 1.752053e-07 6.964484e-07 -3.816903e-07 9.595136e-07 -6.239532e-06
  825,829c811,815
  < (Intercept) -13.316899 -4.095471 -7.3051705 -2.1135465 -1.3054136
  < x1 -4.095471 -26.070905 -1.9897364 4.4835839 4.7599380
  < x2 -7.305171 -1.989736 -6.2345661 -0.6258396 -0.4731815
  < logSigmaMu -2.113547 4.483584 -0.6258396 -16.6619336 -3.7201702
  < logSigmaNu -1.305414 4.759938 -0.4731815 -3.7201702 -61.0551857
  ---
  > (Intercept) -13.321986 -4.096607 -7.3075700 -2.1079020 -1.3088195
  > x1 -4.096607 -26.076783 -1.9905303 4.4849634 4.7620874
  > x2 -7.307570 -1.990530 -6.2362548 -0.6238247 -0.4803056
  > logSigmaMu -2.107902 4.484963 -0.6238247 -16.6581988 -3.7224013
  > logSigmaNu -1.308819 4.762087 -0.4803056 -3.7224013 -61.0683295
  845c831
  < [1] 97
  ---
  > [1] 10
  852,866c838,852
  < [1,] -0.85267878 0.22516944 -0.07277876 -0.1442327 -0.9627270
  < [2,] -1.70285621 0.04808584 -1.18990346 1.6808079 -1.0131479
  < [3,] 1.75037326 0.33369516 1.72670651 1.8349365 1.8016608
  < [4,] 0.15575366 -0.20255154 -0.43243835 -0.6890605 -1.4338580
  < [5,] 0.12956825 0.98396830 0.68888034 -0.6769825 -0.5562170
  < [6,] 0.33032106 -0.30836848 0.38447820 -0.4920851 -1.5803025
  < [7,] -0.08159305 -3.18478145 -0.23710091 -0.6767436 6.0268592
  < [8,] -0.26656434 0.37865529 0.05567476 -0.5386720 -1.1090099
  < [9,] 1.14825660 0.59386549 0.30324938 0.1333283 -1.6169107
  < [10,] -0.43464063 -0.40591957 -0.15232804 -0.4690608 -1.9367144
  < [11,] -0.02824570 1.44830058 -0.64413372 -0.9174848 2.7358146
  < [12,] 1.21028735 0.53701862 0.61277780 0.2053706 -1.7348946
  < [13,] 0.53601855 -0.22518290 0.33114019 -0.3689713 -1.4085074
  < [14,] -1.81429221 -1.30614926 -0.91946365 1.9571789 2.5799667
  < [15,] -0.07772869 1.08540139 -0.45706565 -0.8396765 0.2023117
  ---
  > [1,] -0.85308347 0.22558499 -0.07261018 -0.1440032 -0.9609406
  > [2,] -1.70309377 0.04839407 -1.18987568 1.6807832 -1.0133140
  > [3,] 1.75084257 0.33367521 1.72755756 1.8353810 1.8043722
  > [4,] 0.15577754 -0.20240005 -0.43224639 -0.6891080 -1.4351384
  > [5,] 0.12950028 0.98433611 0.68943609 -0.6770203 -0.5543808
  > [6,] 0.33035927 -0.30928374 0.38471150 -0.4921375 -1.5793720
  > [7,] -0.08212546 -3.18521797 -0.23724723 -0.6766314 6.0271914
  > [8,] -0.26685304 0.37888545 0.05565469 -0.5385827 -1.1091112
  > [9,] 1.14824187 0.59396378 0.30328558 0.1329804 -1.6172740
  > [10,] -0.43505399 -0.40640581 -0.15245987 -0.4687583 -1.9364985
  > [11,] -0.02839190 1.44795720 -0.64407725 -0.9172652 2.7349914
  > [12,] 1.21047895 0.53669838 0.61328533 0.2055545 -1.7351239
  > [13,] 0.53592708 -0.22523038 0.33117481 -0.3691167 -1.4082836
  > [14,] -1.81460685 -1.30608988 -0.91951004 1.9573173 2.5815575
  > [15,] -0.07791890 1.08513335 -0.45707930 -0.8393920 0.2013182
  918c904
  < 0.36883 -1.68008 -2.24540 -0.12919 -0.01232
  ---
  > 0.36562 -1.68000 -2.24054 -0.12955 -0.01241
  923,927c909,911
  < BFGSR maximization, 99 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: -73.19885
  ---
  > BFGSR maximization, 10 iterations
  > Return code 2: successive function values within tolerance limit
  > Log-Likelihood: -73.19882
  931,935c915,919
  < (Intercept) 0.368834 0.474824 0.7768 0.4372885
  < x1 -1.680084 0.209265 -8.0285 9.866e-16 ***
  < x2 -2.245402 0.674099 -3.3310 0.0008654 ***
  < logSigmaMu -0.129190 0.258015 -0.5007 0.6165774
  < logSigmaNu -0.012323 0.129704 -0.0950 0.9243075
  ---
  > (Intercept) 0.365623 0.474457 0.7706 0.4409359
  > x1 -1.680004 0.209222 -8.0298 9.767e-16 ***
  > x2 -2.240544 0.673889 -3.3248 0.0008848 ***
  > logSigmaMu -0.129547 0.258070 -0.5020 0.6156791
  > logSigmaNu -0.012408 0.129690 -0.0957 0.9237792
  951,955c935,939
  < (Intercept) 0.36883 0.47482 0.777 0.437288
  < x1 -1.68008 0.20926 -8.029 9.87e-16 ***
  < x2 -2.24540 0.67410 -3.331 0.000865 ***
  < logSigmaMu -0.12919 0.25801 -0.501 0.616577
  < logSigmaNu -0.01232 0.12970 -0.095 0.924307
  ---
  > (Intercept) 0.36562 0.47446 0.771 0.440936
  > x1 -1.68000 0.20922 -8.030 9.77e-16 ***
  > x2 -2.24054 0.67389 -3.325 0.000885 ***
  > logSigmaMu -0.12955 0.25807 -0.502 0.615679
  > logSigmaNu -0.01241 0.12969 -0.096 0.923779
  959,963c943,945
  < BFGSR maximization, 99 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: -73.19885 on 5 Df
  ---
  > BFGSR maximization, 10 iterations
  > Return code 2: successive function values within tolerance limit
  > Log-likelihood: -73.19882 on 5 Df
  967c949
  < 0.36883360 -1.68008373 -2.24540221 -0.12918979 -0.01232306
  ---
  > 0.36562324 -1.68000398 -2.24054396 -0.12954711 -0.01240798
  970c952
  < 0.3688336 -1.6800837 -2.2454022 0.8788072 0.9877526
  ---
  > 0.3656232 -1.6800040 -2.2405440 0.8784932 0.9876687
  973,977c955,959
  < (Intercept) 0.225457518 -0.020644572 -0.254889987 0.023989703 0.003026588
  < x1 -0.020644572 0.043791676 0.008637256 -0.013415404 -0.002968255
  < x2 -0.254889987 0.008637256 0.454409379 -0.017279672 -0.001630376
  < logSigmaMu 0.023989703 -0.013415404 -0.017279672 0.066571630 -0.002628736
  < logSigmaNu 0.003026588 -0.002968255 -0.001630376 -0.002628736 0.016823069
  ---
  > (Intercept) 0.225109676 -0.020570169 -0.254602918 0.023824169 0.002973956
  > x1 -0.020570169 0.043773979 0.008562227 -0.013404084 -0.002969957
  > x2 -0.254602918 0.008562227 0.454125958 -0.017179555 -0.001505443
  > logSigmaMu 0.023824169 -0.013404084 -0.017179554 0.066600343 -0.002638875
  > logSigmaNu 0.002973956 -0.002969957 -0.001505443 -0.002638875 0.016819446
  980,984c962,966
  < (Intercept) 0.22545752 -0.020644572 -0.254889987 0.021082322 0.002989520
  < x1 -0.02064457 0.043791676 0.008637256 -0.011789553 -0.002931901
  < x2 -0.25488999 0.008637256 0.454409379 -0.015185500 -0.001610409
  < sigmaMu 0.02108232 -0.011789553 -0.015185500 0.051413405 -0.002281859
  < sigmaNu 0.00298952 -0.002931901 -0.001610409 -0.002281859 0.016413513
  ---
  > (Intercept) 0.225109676 -0.020570169 -0.254602918 0.020929371 0.002937284
  > x1 -0.020570169 0.043773979 0.008562227 -0.011775397 -0.002933333
  > x2 -0.254602918 0.008562227 0.454125958 -0.015092122 -0.001486879
  > sigmaMu 0.020929371 -0.011775397 -0.015092122 0.051398836 -0.002289647
  > sigmaNu 0.002937284 -0.002933333 -0.001486879 -0.002289647 0.016407191
  986c968
  < 'log Lik.' -73.19885 (df=5)
  ---
  > 'log Lik.' -73.19882 (df=5)
  988c970
  < [1] -40.0000 156.3977
  ---
  > [1] -40.0000 156.3976
  991c973
  < [1] -73.19885
  ---
  > [1] -73.19882
  995c977
  < 0.36883360 -1.68008373 -2.24540221 -0.12918979 -0.01232306
  ---
  > 0.36562324 -1.68000398 -2.24054396 -0.12954711 -0.01240798
  999c981
  < -0.006065518 -0.003409733 0.007261602 -0.002162623 -0.004236442
  ---
  > -1.752053e-07 -6.964484e-07 3.816903e-07 9.595136e-07 -6.239532e-06
  1003,1007c985,989
  < (Intercept) -13.309936 -4.094894 -7.3025225 2.1268846 1.2966815
  < x1 -4.094894 -26.068888 -1.9889147 -4.4817784 -4.7559479
  < x2 -7.302522 -1.988915 -6.2333996 0.6308142 0.4573231
  < logSigmaMu 2.126885 -4.481778 0.6308142 -16.6740825 -3.7177259
  < logSigmaNu 1.296681 -4.755948 0.4573231 -3.7177259 -61.0512080
  ---
  > (Intercept) -13.321986 -4.096607 -7.3075700 2.1079020 1.3088195
  > x1 -4.096607 -26.076783 -1.9905303 -4.4849634 -4.7620874
  > x2 -7.307570 -1.990530 -6.2362548 0.6238247 0.4803056
  > logSigmaMu 2.107902 -4.484963 0.6238247 -16.6581988 -3.7224012
  > logSigmaNu 1.308819 -4.762087 0.4803056 -3.7224013 -61.0683295
  1010c992
  < [1] 3
  ---
  > [1] 2
  1013c995
  < [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"
  1016,1042c998
  < $last.step$theta0
  < (Intercept) x1 x2 logSigmaMu logSigmaNu
  < 0.36877736 -1.67996651 -2.24518308 -0.12918477 -0.01266367
  <
  < $last.step$f0
  < [1] -73.19885
  < attr(,"gradient")
  < [,1] [,2] [,3] [,4] [,5]
  < [1,] 0.85225068 -0.22528738 0.07282978 -0.1445497 -0.9645464
  < [2,] 1.70257774 -0.04784372 1.19014545 1.6811725 -1.0129395
  < [3,] -1.75073742 -0.33345056 -1.72643191 1.8369427 1.7992936
  < [4,] -0.15531041 0.20294327 0.43361572 -0.6890265 -1.4294992
  < [5,] -0.12987829 -0.98377704 -0.68849159 -0.6770351 -0.5583283
  < [6,] -0.33031326 0.30648555 -0.38416198 -0.4915117 -1.5807464
  < [7,] 0.08044119 3.18737453 0.23702420 -0.6773008 6.0338188
  < [8,] 0.26583269 -0.37814934 -0.05581875 -0.5391567 -1.1084091
  < [9,] -1.14870322 -0.59451145 -0.30325124 0.1340752 -1.6154047
  < [10,] 0.43369203 0.40525771 0.15197531 -0.4696655 -1.9365440
  < [11,] 0.02774099 -1.45045669 0.64475321 -0.9186565 2.7434127
  < [12,] -1.20986783 -0.53804496 -0.61158222 0.2048140 -1.7331342
  < [13,] -0.53652445 0.22543548 -0.33127655 -0.3682755 -1.4081136
  < [14,] 1.81404626 1.30617094 0.91930422 1.9575350 2.5797391
  < [15,] 0.07692515 -1.08722137 0.45728664 -0.8408479 0.2074168
  <
  < $last.step$climb
  < [1] -966176.50 2013835.79 3764676.56 86124.33 -5851662.15
  <
  ---
  > NULL
  1049c1005
  < [1] 99
  ---
  > [1] 10
  1056,1070c1012,1026
  < [1,] 0.85211865 -0.2245178 0.07309993 -0.1445788 -0.9657084
  < [2,] 1.70266820 -0.0474478 1.19021708 1.6813039 -1.0127757
  < [3,] -1.75000411 -0.3336363 -1.72554205 1.8350739 1.7973527
  < [4,] -0.15556758 0.2029150 0.43314723 -0.6890365 -1.4303861
  < [5,] -0.12975405 -0.9833929 -0.68797890 -0.6769420 -0.5595092
  < [6,] -0.33024469 0.3064820 -0.38404066 -0.4918899 -1.5816197
  < [7,] 0.08049561 3.1852693 0.23689336 -0.6770554 6.0292298
  < [8,] 0.26595647 -0.3781746 -0.05572956 -0.5389266 -1.1087043
  < [9,] -1.14849869 -0.5939455 -0.30321984 0.1341180 -1.6158927
  < [10,] 0.43387830 0.4051182 0.15209289 -0.4696027 -1.9369132
  < [11,] 0.02789969 -1.4495674 0.64446788 -0.9181205 2.7397694
  < [12,] -1.20996677 -0.5378599 -0.61169868 0.2049860 -1.7339368
  < [13,] -0.53632072 0.2252150 -0.33113907 -0.3685712 -1.4086195
  < [14,] 1.81401661 1.3065864 0.91951039 1.9574555 2.5779915
  < [15,] 0.07725757 -1.0864533 0.45718161 -0.8403765 0.2054859
  ---
  > [1,] 0.85308347 -0.22558499 0.07261018 -0.1440032 -0.9609406
  > [2,] 1.70309377 -0.04839407 1.18987568 1.6807832 -1.0133140
  > [3,] -1.75084257 -0.33367521 -1.72755756 1.8353810 1.8043722
  > [4,] -0.15577754 0.20240005 0.43224639 -0.6891080 -1.4351384
  > [5,] -0.12950028 -0.98433611 -0.68943609 -0.6770203 -0.5543808
  > [6,] -0.33035927 0.30928374 -0.38471150 -0.4921375 -1.5793720
  > [7,] 0.08212546 3.18521797 0.23724723 -0.6766314 6.0271914
  > [8,] 0.26685304 -0.37888545 -0.05565469 -0.5385827 -1.1091112
  > [9,] -1.14824187 -0.59396378 -0.30328558 0.1329804 -1.6172740
  > [10,] 0.43505399 0.40640581 0.15245987 -0.4687583 -1.9364985
  > [11,] 0.02839190 -1.44795720 0.64407725 -0.9172652 2.7349914
  > [12,] -1.21047895 -0.53669838 -0.61328533 0.2055545 -1.7351239
  > [13,] -0.53592708 0.22523038 -0.33117481 -0.3691167 -1.4082836
  > [14,] 1.81460685 1.30608988 0.91951004 1.9573173 2.5815575
  > [15,] 0.07791890 -1.08513335 0.45707930 -0.8393920 0.2013182
  1123c1079
  < -4.63352 -1.67997 -2.24194 -0.12948 -0.01241
  ---
  > -4.63438 -1.68000 -2.24054 -0.12955 -0.01241
  1128c1084
  < BFGSR maximization, 78 iterations
  ---
  > BFGSR maximization, 10 iterations
  1130c1086
  < Log-Likelihood: -73.19883
  ---
  > Log-Likelihood: -73.19882
  1134,1138c1090,1094
  < (Intercept) -4.633520 0.474538 -9.7643 < 2.2e-16 ***
  < x1 -1.679967 0.209224 -8.0295 9.787e-16 ***
  < x2 -2.241944 0.673924 -3.3267 0.0008788 ***
  < logSigmaMu -0.129482 0.258053 -0.5018 0.6158321
  < logSigmaNu -0.012415 0.129689 -0.0957 0.9237377
  ---
  > (Intercept) -4.634377 0.474457 -9.7677 < 2.2e-16 ***
  > x1 -1.680004 0.209222 -8.0298 9.767e-16 ***
  > x2 -2.240544 0.673889 -3.3248 0.0008848 ***
  > logSigmaMu -0.129547 0.258070 -0.5020 0.6156791
  > logSigmaNu -0.012408 0.129690 -0.0957 0.9237792
  1154,1158c1110,1114
  < (Intercept) -4.63352 0.47454 -9.764 < 2e-16 ***
  < x1 -1.67997 0.20922 -8.030 9.79e-16 ***
  < x2 -2.24194 0.67392 -3.327 0.000879 ***
  < logSigmaMu -0.12948 0.25805 -0.502 0.615832
  < logSigmaNu -0.01241 0.12969 -0.096 0.923738
  ---
  > (Intercept) -4.63438 0.47446 -9.768 < 2e-16 ***
  > x1 -1.68000 0.20922 -8.030 9.77e-16 ***
  > x2 -2.24054 0.67389 -3.325 0.000885 ***
  > logSigmaMu -0.12955 0.25807 -0.502 0.615679
  > logSigmaNu -0.01241 0.12969 -0.096 0.923779
  1162c1118
  < BFGSR maximization, 78 iterations
  ---
  > BFGSR maximization, 10 iterations
  1164c1120
  < Log-likelihood: -73.19883 on 5 Df
  ---
  > Log-likelihood: -73.19882 on 5 Df
  1168c1124
  < -4.63352040 -1.67996657 -2.24194415 -0.12948241 -0.01241471
  ---
  > -4.63437676 -1.68000398 -2.24054396 -0.12954711 -0.01240798
  1171c1127
  < -4.633520 -1.679967 -2.241944 0.878550 0.987662
  ---
  > -4.6343768 -1.6800040 -2.2405440 0.8784932 0.9876687
  1174,1178c1130,1134
  < (Intercept) 0.225186539 -0.020587609 -0.254663173 0.023863583 0.002989013
  < x1 -0.020587609 0.043774800 0.008582003 -0.013406111 -0.002967692
  < x2 -0.254663173 0.008582003 0.454173951 -0.017204905 -0.001542476
  < logSigmaMu 0.023863583 -0.013406111 -0.017204905 0.066591548 -0.002636593
  < logSigmaNu 0.002989013 -0.002967692 -0.001542476 -0.002636593 0.016819309
  ---
  > (Intercept) 0.225109676 -0.020570169 -0.254602918 0.023824169 0.002973956
  > x1 -0.020570169 0.043773979 0.008562227 -0.013404084 -0.002969957
  > x2 -0.254602918 0.008562227 0.454125958 -0.017179555 -0.001505443
  > logSigmaMu 0.023824170 -0.013404084 -0.017179555 0.066600343 -0.002638875
  > logSigmaNu 0.002973956 -0.002969957 -0.001505443 -0.002638875 0.016819446
  1181,1185c1137,1141
  < (Intercept) 0.225186539 -0.020587609 -0.254663173 0.020965352 0.002952134
  < x1 -0.020587609 0.043774800 0.008582003 -0.011777939 -0.002931077
  < x2 -0.254663173 0.008582003 0.454173951 -0.015115370 -0.001523445
  < sigmaMu 0.020965352 -0.011777939 -0.015115370 0.051398697 -0.002287799
  < sigmaNu 0.002952134 -0.002931077 -0.001523445 -0.002287799 0.016406838
  ---
  > (Intercept) 0.225109676 -0.020570169 -0.254602918 0.020929371 0.002937284
  > x1 -0.020570169 0.043773979 0.008562227 -0.011775397 -0.002933333
  > x2 -0.254602918 0.008562227 0.454125958 -0.015092122 -0.001486879
  > sigmaMu 0.020929371 -0.011775397 -0.015092122 0.051398836 -0.002289647
  > sigmaNu 0.002937284 -0.002933333 -0.001486879 -0.002289647 0.016407191
  1187c1143
  < 'log Lik.' -73.19883 (df=5)
  ---
  > 'log Lik.' -73.19882 (df=5)
  1189c1145
  < [1] -40.0000 156.3977
  ---
  > [1] -40.0000 156.3976
  1192c1148
  < [1] -73.19883
  ---
  > [1] -73.19882
  1196c1152
  < -4.63352040 -1.67996657 -2.24194415 -0.12948241 -0.01241471
  ---
  > -4.63437676 -1.68000398 -2.24054396 -0.12954711 -0.01240798
  1200c1156
  < -0.0012016635 -0.0019554550 0.0024373147 -0.0002870474 0.0004376121
  ---
  > -1.752053e-07 -6.964484e-07 3.816903e-07 9.595136e-07 -6.239532e-06
  1204,1208c1160,1164
  < (Intercept) -13.319487 -4.096388 -7.3066081 2.1123722 1.3053147
  < x1 -4.096388 -26.076514 -1.9902130 -4.4843228 -4.7585842
  < x2 -7.306608 -1.990213 -6.2358372 0.6253373 0.4734638
  < logSigmaMu 2.112372 -4.484323 0.6253373 -16.6624564 -3.7212905
  < logSigmaNu 1.305315 -4.758584 0.4734638 -3.7212905 -61.0670038
  ---
  > (Intercept) -13.321986 -4.096607 -7.3075700 2.1079020 1.3088195
  > x1 -4.096607 -26.076783 -1.9905303 -4.4849634 -4.7620874
  > x2 -7.307570 -1.990530 -6.2362548 0.6238247 0.4803056
  > logSigmaMu 2.107902 -4.484963 0.6238247 -16.6581988 -3.7224012
  > logSigmaNu 1.308819 -4.762087 0.4803056 -3.7224013 -61.0683295
  1224c1180
  < [1] 78
  ---
  > [1] 10
  1231,1245c1187,1201
  < [1,] 0.85287634 -0.22533477 0.07274351 -0.1441378 -0.9620787
  < [2,] 1.70310899 -0.04814478 1.19007096 1.6811309 -1.0131027
  < [3,] -1.75071516 -0.33381829 -1.72707637 1.8353933 1.8024574
  < [4,] -0.15566432 0.20252396 0.43256517 -0.6891740 -1.4336207
  < [5,] -0.12953955 -0.98414576 -0.68903994 -0.6770191 -0.5557688
  < [6,] -0.33032143 0.30828297 -0.38448848 -0.4920893 -1.5799611
  < [7,] 0.08170518 3.18534435 0.23716391 -0.6767431 6.0278299
  < [8,] 0.26666118 -0.37872099 -0.05565206 -0.5386575 -1.1090314
  < [9,] -1.14833987 -0.59411706 -0.30326810 0.1332655 -1.6168289
  < [10,] 0.43479302 0.40603938 0.15239917 -0.4689479 -1.9366355
  < [11,] 0.02825990 -1.44853392 0.64424347 -0.9174953 2.7367618
  < [12,] -1.21037942 -0.53710323 -0.61283250 0.2053874 -1.7346953
  < [13,] -0.53595702 0.22517160 -0.33111761 -0.3690391 -1.4083848
  < [14,] 1.81454138 1.30622341 0.91955469 1.9574528 2.5807877
  < [15,] 0.07776912 -1.08562231 0.45717151 -0.8396137 0.2027087
  ---
  > [1,] 0.85308347 -0.22558499 0.07261018 -0.1440032 -0.9609406
  > [2,] 1.70309377 -0.04839407 1.18987568 1.6807832 -1.0133140
  > [3,] -1.75084257 -0.33367521 -1.72755756 1.8353810 1.8043722
  > [4,] -0.15577754 0.20240005 0.43224639 -0.6891080 -1.4351384
  > [5,] -0.12950028 -0.98433611 -0.68943609 -0.6770203 -0.5543808
  > [6,] -0.33035927 0.30928374 -0.38471150 -0.4921375 -1.5793720
  > [7,] 0.08212546 3.18521797 0.23724723 -0.6766314 6.0271914
  > [8,] 0.26685304 -0.37888545 -0.05565469 -0.5385827 -1.1091112
  > [9,] -1.14824187 -0.59396378 -0.30328558 0.1329804 -1.6172740
  > [10,] 0.43505399 0.40640581 0.15245987 -0.4687583 -1.9364985
  > [11,] 0.02839190 -1.44795720 0.64407725 -0.9172652 2.7349914
  > [12,] -1.21047895 -0.53669838 -0.61328533 0.2055545 -1.7351239
  > [13,] -0.53592708 0.22523038 -0.33117481 -0.3691167 -1.4082836
  > [14,] 1.81460685 1.30608988 0.91951004 1.9573173 2.5815575
  > [15,] 0.07791890 -1.08513335 0.45707930 -0.8393920 0.2013182
  1298c1254
  < -0.233036 1.892966 1.968305 0.001607 0.052530
  ---
  > -0.235535 1.893305 1.972325 0.001777 0.052887
  1303,1307c1259,1261
  < BFGSR maximization, 100 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: -64.31274
  ---
  > BFGSR maximization, 16 iterations
  > Return code 2: successive function values within tolerance limit
  > Log-Likelihood: -64.31272
  1311,1315c1265,1269
  < (Intercept) -0.2330360 0.5482047 -0.4251 0.67077
  < x1 1.8929659 0.3009932 6.2891 3.194e-10 ***
  < x2 1.9683050 0.8185135 2.4047 0.01618 *
  < logSigmaMu 0.0016072 0.2777572 0.0058 0.99538
  < logSigmaNu 0.0525300 0.1629643 0.3223 0.74719
  ---
  > (Intercept) -0.235536 0.548605 -0.4293 0.66768
  > x1 1.893306 0.301140 6.2871 3.234e-10 ***
  > x2 1.972325 0.819113 2.4079 0.01605 *
  > logSigmaMu 0.001777 0.277794 0.0064 0.99490
  > logSigmaNu 0.052887 0.163015 0.3244 0.74561
  1331,1335c1285,1289
  < (Intercept) -0.233036 0.548205 -0.425 0.6708
  < x1 1.892966 0.300993 6.289 3.19e-10 ***
  < x2 1.968305 0.818513 2.405 0.0162 *
  < logSigmaMu 0.001607 0.277757 0.006 0.9954
  < logSigmaNu 0.052530 0.162964 0.322 0.7472
  ---
  > (Intercept) -0.235535 0.548605 -0.429 0.668
  > x1 1.893305 0.301140 6.287 3.23e-10 ***
  > x2 1.972325 0.819113 2.408 0.016 *
  > logSigmaMu 0.001777 0.277794 0.006 0.995
  > logSigmaNu 0.052887 0.163015 0.324 0.746
  1339,1343c1293,1295
  < BFGSR maximization, 100 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: -64.31274 on 5 Df
  ---
  > BFGSR maximization, 16 iterations
  > Return code 2: successive function values within tolerance limit
  > Log-likelihood: -64.31272 on 5 Df
  1357,1361c1309,1313
  < (Intercept) -0.2330 0.5482 -0.425 0.670772
  < x1 1.8930 0.3010 6.289 3.19e-10 ***
  < x2 1.9683 0.8185 2.405 0.016184 *
  < sigmaMu 1.0016 0.2782 3.600 0.000318 ***
  < sigmaNu 1.0539 0.1718 6.136 8.45e-10 ***
  ---
  > (Intercept) -0.2355 0.5486 -0.429 0.667679
  > x1 1.8933 0.3011 6.287 3.23e-10 ***
  > x2 1.9723 0.8191 2.408 0.016046 *
  > sigmaMu 1.0018 0.2783 3.600 0.000318 ***
  > sigmaNu 1.0543 0.1719 6.134 8.55e-10 ***
  1365,1369c1317,1319
  < BFGSR maximization, 100 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: -64.31274 on 5 Df
  ---
  > BFGSR maximization, 16 iterations
  > Return code 2: successive function values within tolerance limit
  > Log-likelihood: -64.31272 on 5 Df
  1373c1323
  < -0.233035955 1.892965861 1.968305023 0.001607175 0.052530029
  ---
  > -0.235535467 1.893305460 1.972325289 0.001776973 0.052886968
  1376c1326
  < -0.233036 1.892966 1.968305 1.001608 1.053934
  ---
  > -0.2355355 1.8933055 1.9723253 1.0017786 1.0543105
  1379,1383c1329,1333
  < (Intercept) 0.30052834 -0.03134113 -0.36380747 -0.015914285 -0.016352123
  < x1 -0.03134113 0.09059691 0.03173221 0.035165101 0.015910366
  < x2 -0.36380747 0.03173221 0.66996433 0.018582034 0.024442389
  < logSigmaMu -0.01591429 0.03516510 0.01858203 0.077149086 0.004344097
  < logSigmaNu -0.01635212 0.01591037 0.02444239 0.004344097 0.026557347
  ---
  > (Intercept) 0.30096775 -0.03150689 -0.36439615 -0.016096679 -0.016446163
  > x1 -0.03150689 0.09068516 0.03196988 0.035193435 0.015934669
  > x2 -0.36439615 0.03196988 0.67094660 0.018772996 0.024627417
  > logSigmaMu -0.01609668 0.03519344 0.01877300 0.077169281 0.004356389
  > logSigmaNu -0.01644616 0.01593467 0.02462742 0.004356389 0.026573903
  1386,1390c1336,1340
  < (Intercept) 0.30052834 -0.03134113 -0.36380747 -0.015939883 -0.017234062
  < x1 -0.03134113 0.09059691 0.03173221 0.035221663 0.016768480
  < x2 -0.36380747 0.03173221 0.66996433 0.018611923 0.025760670
  < sigmaMu -0.01593988 0.03522166 0.01861192 0.077397469 0.004585757
  < sigmaNu -0.01723406 0.01676848 0.02576067 0.004585757 0.029499299
  ---
  > (Intercept) 0.30096775 -0.03150689 -0.36439615 -0.016125308 -0.017339362
  > x1 -0.03150689 0.09068516 0.03196988 0.035256029 0.016800088
  > x2 -0.36439615 0.03196988 0.67094660 0.018806384 0.025964943
  > sigmaMu -0.01612531 0.03525603 0.01880638 0.077444024 0.004601155
  > sigmaNu -0.01733936 0.01680009 0.02596494 0.004601155 0.029538768
  1393,1397c1343,1347
  < (Intercept) -0.233035955 0.5482047 -0.425089344 6.707715e-01
  < x1 1.892965861 0.3009932 6.289064999 3.193837e-10
  < x2 1.968305023 0.8185135 2.404731321 1.618436e-02
  < logSigmaMu 0.001607175 0.2777572 0.005786256 9.953833e-01
  < logSigmaNu 0.052530029 0.1629643 0.322340810 7.471945e-01
  ---
  > (Intercept) -0.235535467 0.5486053 -0.429335037 6.676794e-01
  > x1 1.893305460 0.3011398 6.287131891 3.233846e-10
  > x2 1.972325289 0.8191133 2.407878483 1.604552e-02
  > logSigmaMu 0.001776973 0.2777936 0.006396737 9.948962e-01
  > logSigmaNu 0.052886968 0.1630150 0.324429993 7.456125e-01
  1400,1404c1350,1354
  < (Intercept) -0.233036 0.5482047 -0.4250893 6.707715e-01
  < x1 1.892966 0.3009932 6.2890650 3.193837e-10
  < x2 1.968305 0.8185135 2.4047313 1.618436e-02
  < sigmaMu 1.001608 0.2782040 3.6002662 3.178916e-04
  < sigmaNu 1.053934 0.1717536 6.1363151 8.445756e-10
  ---
  > (Intercept) -0.2355355 0.5486053 -0.429335 6.676794e-01
  > x1 1.8933055 0.3011398 6.287132 3.233846e-10
  > x2 1.9723253 0.8191133 2.407878 1.604552e-02
  > sigmaMu 1.0017786 0.2782877 3.599795 3.184681e-04
  > sigmaNu 1.0543105 0.1718685 6.134403 8.547939e-10
  1406c1356
  < 'log Lik.' -64.31274 (df=5)
  ---
  > 'log Lik.' -64.31272 (df=5)
  1408c1358
  < [1] -40.0000 138.6255
  ---
  > [1] -40.0000 138.6254
  1411c1361
  < [1] -64.31274
  ---
  > [1] -64.31272
  1415c1365
  < -0.233035955 1.892965861 1.968305023 0.001607175 0.052530029
  ---
  > -0.235535467 1.893305460 1.972325289 0.001776973 0.052886968
  1419c1369
  < -0.0028454865 -0.0001882710 0.0041648354 0.0002417491 0.0079026524
  ---
  > 2.487688e-08 -2.871254e-06 1.028026e-06 4.853692e-07 -3.020918e-06
  1423,1427c1373,1377
  < (Intercept) -9.92949010 -1.4912086 -5.3075211 -0.07194787 -0.3238849
  < x1 -1.49120857 -15.1470845 -0.5453208 6.29837186 7.6279998
  < x2 -5.30752112 -0.5453208 -4.3923717 0.15104940 1.0765721
  < logSigmaMu -0.07194787 6.2983719 0.1510494 -15.80678054 -1.3710601
  < logSigmaNu -0.32388494 7.6279998 1.0765721 -1.37106006 -43.1902492
  ---
  > (Intercept) -9.92156107 -1.4895580 -5.3035083 -0.08203739 -0.3186171
  > x1 -1.48955800 -15.1354595 -0.5438191 6.29367769 7.6261353
  > x2 -5.30350830 -0.5438191 -4.3889375 0.14809035 1.0870164
  > logSigmaMu -0.08203739 6.2936777 0.1480904 -15.80452827 -1.3710175
  > logSigmaNu -0.31861714 7.6261353 1.0870164 -1.37101753 -43.1836339
  1430c1380
  < [1] 3
  ---
  > [1] 2
  1433c1383
  < [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"
  1436,1462c1386
  < $last.step$theta0
  < (Intercept) x1 x2 logSigmaMu logSigmaNu
  < -0.233070459 1.892796219 1.968322500 0.001741956 0.052796187
  <
  < $last.step$f0
  < [1] -64.31274
  < attr(,"gradient")
  < [,1] [,2] [,3] [,4] [,5]
  < [1,] -0.85377145 -0.10542175 -0.18111197 -0.02398548 -0.8369716
  < [2,] -1.41599060 -0.02576187 -0.97108514 1.45505008 -1.1647274
  < [3,] 1.29713303 1.02169406 0.92541839 1.09177069 0.1538427
  < [4,] 0.07063368 -0.25163723 -0.39812770 -0.70165021 -1.8278591
  < [5,] 0.08909056 0.80799288 0.64788059 -0.69083487 -0.2837871
  < [6,] 0.55928838 0.49502340 0.42893599 -0.29126808 -0.3605247
  < [7,] -0.12055560 -3.06050032 -0.23667261 -0.70634947 6.3396024
  < [8,] -0.20984411 0.33578108 0.08326638 -0.59066001 -1.0295613
  < [9,] 1.03392261 0.66100889 0.28819314 0.19624798 -1.2969967
  < [10,] -0.42784000 -0.58494452 -0.11713334 -0.39600638 -1.8013220
  < [11,] -0.04052129 1.09501690 -0.50807458 -0.86709146 2.0012706
  < [12,] 1.14003680 0.50517682 0.83219876 0.58497341 -0.7447206
  < [13,] 0.53422044 -0.28131504 0.34758908 -0.28684783 -1.4344029
  < [14,] -1.63728021 -1.34574791 -0.83735800 2.11812589 2.7627409
  < [15,] -0.02096102 0.73893535 -0.29924858 -0.89478994 -0.4816214
  <
  < $last.step$climb
  < [1] -592771.0 -2914420.9 300245.4 2315527.2 4572554.7
  <
  ---
  > NULL
  1469c1393
  < [1] 100
  ---
  > [1] 16
  1476,1490c1400,1414
  < [1,] -0.85422240 -0.10572470 -0.18129517 -0.02362373 -0.8365960
  < [2,] -1.41636562 -0.02612428 -0.97143340 1.45571221 -1.1647733
  < [3,] 1.29745390 1.02142681 0.92560970 1.09216006 0.1541369
  < [4,] 0.07051698 -0.25184275 -0.39844811 -0.70161793 -1.8270985
  < [5,] 0.08912226 0.80789007 0.64808165 -0.69087170 -0.2834545
  < [6,] 0.55936205 0.49470995 0.42911494 -0.29124884 -0.3597088
  < [7,] -0.12056169 -3.06249951 -0.23680971 -0.70643011 6.3450459
  < [8,] -0.20975133 0.33570328 0.08331297 -0.59075862 -1.0294035
  < [9,] 1.03419669 0.66081406 0.28827863 0.19650274 -1.2969513
  < [10,] -0.42811182 -0.58557987 -0.11720732 -0.39574223 -1.8006917
  < [11,] -0.04047228 1.09529847 -0.50817729 -0.86707355 2.0023249
  < [12,] 1.14015734 0.50522091 0.83233586 0.58505668 -0.7445239
  < [13,] 0.53463725 -0.28171824 0.34785114 -0.28652068 -1.4336925
  < [14,] -1.63797360 -1.34693536 -0.83777571 2.11960832 2.7643125
  < [15,] -0.02083322 0.73917288 -0.29927334 -0.89491088 -0.4810235
  ---
  > [1,] -0.85345502 -0.10600202 -0.1814284 -0.02424029 -0.8381663
  > [2,] -1.41652306 -0.02739585 -0.9720425 1.45685325 -1.1643003
  > [3,] 1.29710955 1.02071645 0.9249772 1.09192822 0.1536204
  > [4,] 0.07071079 -0.25221748 -0.3986639 -0.70161956 -1.8243307
  > [5,] 0.08940243 0.80718484 0.6470466 -0.69053380 -0.2869973
  > [6,] 0.55895982 0.49540605 0.4285452 -0.29156512 -0.3618361
  > [7,] -0.11968838 -3.06103611 -0.2365183 -0.70670422 6.3435264
  > [8,] -0.20931458 0.33524154 0.0832306 -0.59070813 -1.0295423
  > [9,] 1.03431545 0.66026310 0.2882436 0.19767251 -1.2965692
  > [10,] -0.42765160 -0.58469153 -0.1171546 -0.39622543 -1.8014625
  > [11,] -0.04032187 1.09571343 -0.5082752 -0.86763297 2.0031266
  > [12,] 1.14007145 0.50584814 0.8314616 0.58515264 -0.7454354
  > [13,] 0.53481223 -0.28157458 0.3477457 -0.28643956 -1.4343028
  > [14,] -1.63752640 -1.34696463 -0.8377496 2.11919025 2.7628210
  > [15,] -0.02090079 0.73950577 -0.2994167 -0.89512731 -0.4801545
  1543,1547c1467
  < [1] "Component 1: Mean relative difference: 1.121484e-06"
  < [2] "Component 2: Mean relative difference: 0.002397088"
  < [3] "Component 3: Mean relative difference: 2.973721"
  < [4] "Component 4: Mean relative difference: 0.001230245"
  < [5] "Component 9: Mean relative difference: 0.2222222"
  ---
  > [1] TRUE
  1549c1469
  < [1] "Mean relative difference: 0.001505179"
  ---
  > [1] TRUE
  1563c1483
  < -0.221220 1.640551 2.106133 -0.167678 -0.001021
  ---
  > -0.225080 1.640577 2.112079 -0.167313 -0.001134
  1568,1572c1488,1490
  < 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, 10 iterations
  > Return code 2: successive function values within tolerance limit
  > Log-Likelihood: -71.19256
  1576,1580c1494,1498
  < (Intercept) -0.2212200 0.4723840 -0.4683 0.639566
  < x1 1.6405506 0.2110596 7.7729 7.669e-15 ***
  < x2 2.1061327 0.6848595 3.0753 0.002103 **
  < logSigmaMu -0.1676775 0.2716417 -0.6173 0.537054
  < logSigmaNu -0.0010209 0.1322940 -0.0077 0.993843
  ---
  > (Intercept) -0.2250795 0.4726959 -0.4762 0.633959
  > x1 1.6405767 0.2110697 7.7727 7.685e-15 ***
  > x2 2.1120788 0.6849330 3.0836 0.002045 **
  > logSigmaMu -0.1673126 0.2714583 -0.6163 0.537665
  > logSigmaNu -0.0011337 0.1322715 -0.0086 0.993162
  1595,1599c1513,1517
  < (Intercept) -0.221220 0.472384 -0.468 0.6396
  < x1 1.640551 0.211060 7.773 7.67e-15 ***
  < x2 2.106133 0.684859 3.075 0.0021 **
  < logSigmaMu -0.167678 0.271642 -0.617 0.5371
  < logSigmaNu -0.001021 0.132294 -0.008 0.9938
  ---
  > (Intercept) -0.225080 0.472696 -0.476 0.63396
  > x1 1.640577 0.211070 7.773 7.68e-15 ***
  > x2 2.112079 0.684933 3.084 0.00204 **
  > logSigmaMu -0.167313 0.271458 -0.616 0.53767
  > logSigmaNu -0.001134 0.132271 -0.009 0.99316
  1603,1607c1521,1523
  < 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, 10 iterations
  > Return code 2: successive function values within tolerance limit
  > Log-likelihood: -71.19256 on 5 Df
  1610c1526
  < 'log Lik.' -71.1926 (df=5)
  ---
  > 'log Lik.' -71.19256 (df=5)
  1612c1528
  < [1] -36.0000 152.3852
  ---
  > [1] -36.0000 152.3851
  1615c1531
  < [1] -71.1926
  ---
  > [1] -71.19256
  1619c1535
  < -0.221220011 1.640550638 2.106132661 -0.167677520 -0.001020937
  ---
  > -0.225079532 1.640576704 2.112078831 -0.167312618 -0.001133654
  1623c1539
  < -0.008171728 -0.005122186 0.008179362 0.001477031 -0.006580622
  ---
  > -8.636040e-06 -1.453204e-05 -7.787637e-06 1.016841e-05 -1.994848e-05
  1627,1631c1543,1547
  < (Intercept) -13.797951 -4.347114 -7.5311473 -1.0995922 -1.945256
  < x1 -4.347114 -25.809896 -2.0583526 4.6515821 4.062586
  < x2 -7.531147 -2.058353 -6.2667758 -0.1388448 -1.070633
  < logSigmaMu -1.099592 4.651582 -0.1388448 -14.9127069 -3.781228
  < logSigmaNu -1.945256 4.062586 -1.0706330 -3.7812281 -58.823650
  ---
  > (Intercept) -13.784888 -4.345494 -7.5260689 -1.1169013 -1.938671
  > x1 -4.345494 -25.808843 -2.0565428 4.6495651 4.051833
  > x2 -7.526069 -2.056543 -6.2649095 -0.1454329 -1.045995
  > logSigmaMu -1.116901 4.649565 -0.1454329 -14.9357030 -3.771780
  > logSigmaNu -1.938671 4.051833 -1.0459950 -3.7717801 -58.831584
  1634c1550
  < [1] 3
  ---
  > [1] 2
  1637c1553
  < [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"
  1640,1666c1556
  < $last.step$theta0
  < (Intercept) x1 x2 logSigmaMu logSigmaNu
  < -0.221184633 1.640838544 2.106276976 -0.167766824 -0.001207716
  <
  < $last.step$f0
  < [1] -71.1926
  < attr(,"gradient")
  < [,1] [,2] [,3] [,4] [,5]
  < [1,] -0.50960693 0.088084223 0.10323765 -0.39345246 -0.52971851
  < [2,] -1.81818558 0.066341606 -1.24792045 1.79974396 -0.96143585
  < [3,] 1.78500821 0.483543710 1.77061021 1.73278117 1.89970761
  < [4,] 0.15195271 -0.162752802 -0.39579142 -0.73697189 -1.58718438
  < [5,] 0.08146041 1.038842809 0.69848460 -0.67801537 -0.44478197
  < [6,] 0.33211113 -0.235218281 0.37407119 -0.54032034 -1.57210280
  < [7,] -0.18144837 -3.030683104 -0.24881005 -0.62180777 5.48377913
  < [8,] 0.01857804 -0.004049548 0.01062544 -0.41758715 -0.58182142
  < [9,] 1.11588638 0.665632254 0.29579739 0.06322349 -1.68665638
  < [10,] -0.53901737 -0.421674537 -0.20470899 -0.40568322 -1.97350320
  < [11,] -0.08379215 1.377482472 -0.64762583 -0.82242562 2.49307183
  < [12,] 1.25935913 0.531154515 0.67038253 0.23091539 -1.79434282
  < [13,] 0.44680888 -0.163720591 0.28656582 -0.46831777 -1.44993993
  < [14,] -1.89423335 -1.289301886 -0.96306928 1.98564501 2.68433271
  < [15,] -0.17541884 1.042138589 -0.49522107 -0.72293098 0.02629086
  <
  < $last.step$climb
  < [1] 607785.7 4946200.4 2479313.1 -1534231.2 -3208828.0
  <
  ---
  > NULL
  1673c1563
  < [1] 80
  ---
  > [1] 10
  1680,1694c1570,1584
  < [1,] -0.50908965 0.088790519 0.10350386 -0.39377803 -0.52983819
  < [2,] -1.81760729 0.066936207 -1.24738123 1.79865825 -0.96141348
  < [3,] 1.78478935 0.484694558 1.77027296 1.73260958 1.89831924
  < [4,] 0.15208904 -0.162532902 -0.39546970 -0.73682144 -1.58812351
  < [5,] 0.08147497 1.039036634 0.69838066 -0.67797455 -0.44487234
  < [6,] 0.33249684 -0.233832122 0.37407635 -0.53998261 -1.57303799
  < [7,] -0.18139345 -3.028935764 -0.24868182 -0.62177999 5.47907652
  < [8,] 0.01860481 -0.004055382 0.01064075 -0.41753858 -0.58186811
  < [9,] 1.11561252 0.666117168 0.29570843 0.06306235 -1.68658356
  < [10,] -0.53860416 -0.420942355 -0.20454372 -0.40599166 -1.97408620
  < [11,] -0.08367217 1.377350533 -0.64747005 -0.82247479 2.49197190
  < [12,] 1.25925543 0.531194619 0.67031295 0.23107826 -1.79460982
  < [13,] 0.44660287 -0.163433946 0.28643449 -0.46846910 -1.45040613
  < [14,] -1.89338628 -1.287488735 -0.96249029 1.98388576 2.68283104
  < [15,] -0.17534456 1.041978782 -0.49511427 -0.72300641 0.02606001
  ---
  > [1,] -0.50840052 0.087714316 0.10287525 -0.39431964 -0.53426583
  > [2,] -1.81732267 0.065815016 -1.24804243 1.79967366 -0.96091655
  > [3,] 1.78433755 0.484533165 1.76843009 1.73329056 1.89069332
  > [4,] 0.15176201 -0.163179756 -0.39680494 -0.73698273 -1.58181515
  > [5,] 0.08189442 1.038061250 0.69691610 -0.67803233 -0.45084034
  > [6,] 0.33234643 -0.230428212 0.37329832 -0.53971463 -1.57493250
  > [7,] -0.17917946 -3.030324203 -0.24829015 -0.62279217 5.48422908
  > [8,] 0.01887239 -0.004113708 0.01079379 -0.41776542 -0.58162397
  > [9,] 1.11662282 0.666294925 0.29584825 0.06450853 -1.68416734
  > [10,] -0.53726364 -0.419646234 -0.20413611 -0.40687228 -1.97452123
  > [11,] -0.08242475 1.380218291 -0.64791274 -0.82394685 2.50003236
  > [12,] 1.25880532 0.532782587 0.66844750 0.23053623 -1.79300733
  > [13,] 0.44705025 -0.163466537 0.28638877 -0.46787239 -1.45058887
  > [14,] -1.89296358 -1.288373430 -0.96260700 1.98453208 2.67979864
  > [15,] -0.17414520 1.044098000 -0.49521247 -0.72423245 0.03190577
  Running ‘censRegTest.R’
  Comparing ‘censRegTest.Rout’ to ‘censRegTest.Rout.save’ ...5,11d4
  <
  < Attaching package: 'zoo'
  <
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• 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 ... OK
• checking PDF version of manual ... OK