• using R version 2.15.0 Patched (2012-05-26 r59450)
• using platform: sparc-sun-solaris2.10 (32-bit)
• using session charset: UTF-8
• checking for file ‘bbmle/DESCRIPTION’ ... OK
• this is package ‘bbmle’ version ‘1.0.4.1’
• 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 .dll and .exe files ... OK
• checking whether package ‘bbmle’ 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 ... OK
• 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 installed files from ‘inst/doc’ ... OK
• checking examples ... [33s/33s] OK
• checking for unstated dependencies in tests ... OK
• checking tests ... [272s/272s] OK
  Running ‘BIC.R’
  Comparing ‘BIC.Rout’ to ‘BIC.Rout.save’ ... OK
  Running ‘ICtab.R’
  Comparing ‘ICtab.Rout’ to ‘ICtab.Rout.save’ ... OK
  Running ‘RUnit-tests.R’
  Comparing ‘RUnit-tests.Rout’ to ‘RUnit-tests.Rout.save’ ... OK
  Running ‘binomtest1.R’ [16s/16s]
  Comparing ‘binomtest1.Rout’ to ‘binomtest1.Rout.save’ ...34,38c34,38
  < 1 -4.2047395 0.294898436 -0.002923494
  < 2 -3.1552101 0.341179388 0.002586046
  < 3 -2.2351061 0.387460339 0.007009817
  < 4 -1.4145449 0.433741290 0.010694607
  < 5 -0.6726268 0.480022241 0.013859299
  ---
  > 1 -4.2047344 0.294898645 -0.002923466
  > 2 -3.1552066 0.341179554 0.002586064
  > 3 -2.2351038 0.387460464 0.007009828
  > 4 -1.4145435 0.433741374 0.010694613
  > 5 -0.6726261 0.480022283 0.013859302
  40,46c40,46
  < 7 0.6321743 0.572584144 0.019113309
  < 8 1.2156062 0.618865095 0.021399153
  < 9 1.7630620 0.665146046 0.023494927
  < 10 2.2804946 0.711426998 0.025475105
  < 11 2.7729166 0.757707949 0.027355956
  < 12 3.2447751 0.803988900 0.029170766
  < 13 3.7001551 0.850269851 0.030945285
  ---
  > 7 0.6321738 0.572584102 0.019113307
  > 8 1.2156051 0.618865012 0.021399150
  > 9 1.7630606 0.665145921 0.023494921
  > 10 2.2804928 0.711426831 0.025475099
  > 11 2.7729144 0.757707740 0.027355948
  > 12 3.2447726 0.803988650 0.029170757
  > 13 3.7001523 0.850269559 0.030945274
  50,62c50,62
  < 1 -3.7637605 0.326856968 -0.002427402
  < 2 -3.1748381 0.354263794 0.000751101
  < 3 -2.5644483 0.384375811 0.003929604
  < 4 -1.9359430 0.417049307 0.007108107
  < 5 -1.2938768 0.451955479 0.010286610
  < 6 -0.6437604 0.488600094 0.013465113
  < 7 0.0000000 0.526303193 0.016643616
  < 8 0.6563184 0.564651278 0.019822119
  < 9 1.2951046 0.602851362 0.023000622
  < 10 1.9201253 0.640512980 0.026179125
  < 11 2.5281055 0.677305561 0.029357628
  < 12 3.1168292 0.713017842 0.032536131
  < 13 3.6849944 0.747542530 0.035714634
  ---
  > 1 -3.7637543 0.3268572493 -0.0024273676
  > 2 -3.1748327 0.3542640536 0.0007511297
  > 3 -2.5644438 0.3843760379 0.0039296269
  > 4 -1.9359396 0.4170494900 0.0071081242
  > 5 -1.2938745 0.4519556085 0.0102866214
  > 6 -0.6437592 0.4886001613 0.0134651187
  > 7 0.0000000 0.5263031926 0.0166436159
  > 8 0.6563173 0.5646512092 0.0198221132
  > 9 1.2951023 0.6028512247 0.0230006104
  > 10 1.9201220 0.6405127788 0.0261791077
  > 11 2.5281012 0.6773052997 0.0293576049
  > 12 3.1168240 0.7130175259 0.0325361022
  > 13 3.6849884 0.7475421634 0.0357145994
  66c66
  < a 0.402495804 0.68249529
  ---
  > a 0.402495803 0.68249529
  87c87
  < a 0.402495804 0.68249529
  ---
  > a 0.402495803 0.68249529
  Running ‘controleval.R’
  Comparing ‘controleval.Rout’ to ‘controleval.Rout.save’ ... OK
  Running ‘doRUnit.R’
  Running ‘eval.R’
  Comparing ‘eval.Rout’ to ‘eval.Rout.save’ ... OK
  Running ‘formulatest.R’ [19s/19s]
  Comparing ‘formulatest.Rout’ to ‘formulatest.Rout.save’ ...15,18c15,16
  < 1: In dpois(x = c(26, 17, 13, 12, 20, 5, 9, 8, 5, 4, 8), lambda = c(15.9069797531213, :
  < NaNs produced
  < 2: In dpois(x = c(26, 17, 13, 12, 20, 5, 9, 8, 5, 4, 8), lambda = c(33.2333275588048, :
  < NaNs produced
  ---
  > 1: In dpois(x, lambda, log) : NaNs produced
  > 2: In dpois(x, lambda, log) : NaNs produced
  22,37c20,27
  < 1: In dpois(x = c(26, 17, 13, 12, 20, 5, 9, 8, 5, 4, 8), lambda = c(30.4960491806568, :
  < NaNs produced
  < 2: In dpois(x = c(26, 17, 13, 12, 20, 5, 9, 8, 5, 4, 8), lambda = c(33.2466993251375, :
  < NaNs produced
  < 3: In dpois(x = c(26, 17, 13, 12, 20, 5, 9, 8, 5, 4, 8), lambda = c(35.9973494696183, :
  < NaNs produced
  < 4: In dpois(x = c(26, 17, 13, 12, 20, 5, 9, 8, 5, 4, 8), lambda = c(38.747999614099, :
  < NaNs produced
  < 5: In dpois(x = c(26, 17, 13, 12, 20, 5, 9, 8, 5, 4, 8), lambda = c(41.4986497585797, :
  < NaNs produced
  < 6: In dpois(x = c(26, 17, 13, 12, 20, 5, 9, 8, 5, 4, 8), lambda = c(41.4986497585797, :
  < NaNs produced
  < 7: In dpois(x = c(26, 17, 13, 12, 20, 5, 9, 8, 5, 4, 8), lambda = c(44.2492999030605, :
  < NaNs produced
  < 8: In dpois(x = c(26, 17, 13, 12, 20, 5, 9, 8, 5, 4, 8), lambda = c(44.2492999030605, :
  < NaNs produced
  ---
  > 1: In dpois(x, lambda, log) : NaNs produced
  > 2: In dpois(x, lambda, log) : NaNs produced
  > 3: In dpois(x, lambda, log) : NaNs produced
  > 4: In dpois(x, lambda, log) : NaNs produced
  > 5: In dpois(x, lambda, log) : NaNs produced
  > 6: In dpois(x, lambda, log) : NaNs produced
  > 7: In dpois(x, lambda, log) : NaNs produced
  > 8: In dpois(x, lambda, log) : NaNs produced
  42,45c32,33
  < 1: In dpois(x = c(26, 17, 13, 12, 20, 5, 9, 8, 5, 4, 8), lambda = c(15.9069797531213, :
  < NaNs produced
  < 2: In dpois(x = c(26, 17, 13, 12, 20, 5, 9, 8, 5, 4, 8), lambda = c(33.2333275588048, :
  < NaNs produced
  ---
  > 1: In dpois(x, lambda, log) : NaNs produced
  > 2: In dpois(x, lambda, log) : NaNs produced
  98,101c86,87
  < 1: In dpois(x = c(16, 8, 6, 6, 8, 0, 2, 3, 5, 3, 1, 5, 3, 2, 5, 1, :
  < NaNs produced
  < 2: In dpois(x = c(16, 8, 6, 6, 8, 0, 2, 3, 5, 3, 1, 5, 3, 2, 5, 1, :
  < NaNs produced
  ---
  > 1: In dpois(x, lambda, log) : NaNs produced
  > 2: In dpois(x, lambda, log) : NaNs produced
  Running ‘glmcomp.R’
  Comparing ‘glmcomp.Rout’ to ‘glmcomp.Rout.save’ ...18c18
  < -1.354668e-09
  ---
  > -2.709339e-10
  20c20
  < 'log Lik.' 1.421085e-14 (df=1)
  ---
  > 'log Lik.' 7.105427e-15 (df=1)
  31c31
  < [7] -0.7491345 -1.0434374 -1.9263460 -2.2206488 -1.0434374
  ---
  > [7] -0.7491346 -1.0434374 -1.9263460 -2.2206488 -1.0434374
  Running ‘grtest1.R’
  Comparing ‘grtest1.Rout’ to ‘grtest1.Rout.save’ ...15c15
  < 1.090239e-13 1.000000e+00
  ---
  > 1.092459e-13 1.000000e+00
  Running ‘methods.R’
  Comparing ‘methods.Rout’ to ‘methods.Rout.save’ ...19c19
  < [7] -0.7491345 -1.0434374 -1.9263460 -2.2206488 -1.0434374
  ---
  > [7] -0.7491346 -1.0434374 -1.9263460 -2.2206488 -1.0434374
  Running ‘mortanal.R’ [12s/12s]
  Comparing ‘mortanal.Rout’ to ‘mortanal.Rout.save’ ...58,59c58
  < In dweibull(x = c(391L, 370L, 346L, 341L, 334L, 320L, 319L, 317L, :
  < NaNs produced
  ---
  > In dweibull(x, shape, scale, log) : NaNs produced
  65,68c64,65
  < 1: In dweibull(x = c(391L, 370L, 346L, 341L, 334L, 320L, 319L, 317L, :
  < NaNs produced
  < 2: In dweibull(x = c(391L, 370L, 346L, 341L, 334L, 320L, 319L, 317L, :
  < NaNs produced
  ---
  > 1: In dweibull(x, shape, scale, log) : NaNs produced
  > 2: In dweibull(x, shape, scale, log) : NaNs produced
  74,81c71,74
  < 1: In dweibull(x = c(391L, 370L, 346L, 341L, 334L, 320L, 319L, 317L, :
  < NaNs produced
  < 2: In dweibull(x = c(391L, 370L, 346L, 341L, 334L, 320L, 319L, 317L, :
  < NaNs produced
  < 3: In dweibull(x = c(391L, 370L, 346L, 341L, 334L, 320L, 319L, 317L, :
  < NaNs produced
  < 4: In dweibull(x = c(391L, 370L, 346L, 341L, 334L, 320L, 319L, 317L, :
  < NaNs produced
  ---
  > 1: In dweibull(x, shape, scale, log) : NaNs produced
  > 2: In dweibull(x, shape, scale, log) : NaNs produced
  > 3: In dweibull(x, shape, scale, log) : NaNs produced
  > 4: In dweibull(x, shape, scale, log) : NaNs produced
  Running ‘optimize.R’
  Comparing ‘optimize.Rout’ to ‘optimize.Rout.save’ ... OK
  Running ‘optimizers.R’
  Comparing ‘optimizers.Rout’ to ‘optimizers.Rout.save’ ...13,14c13
  < 1: In dpois(x = c(26, 17, 13, 12, 20, 5, 9, 8, 5, 4, 8), lambda = c(31.4659916367342, :
  < NaNs produced
  ---
  > 1: In dpois(x, lambda, log) : NaNs produced
  Running ‘optimx.R’ [28s/28s]
  Comparing ‘optimx.Rout’ to ‘optimx.Rout.save’ ...4a5,22
  >
  > Attaching package: 'Rvmmin'
  >
  > The following object(s) are masked from 'package:Rcgmin':
  >
  > optansout
  >
  >
  > Attaching package: 'optimx'
  >
  > The following object(s) are masked from 'package:Rvmmin':
  >
  > optansout
  >
  > The following object(s) are masked from 'package:Rcgmin':
  >
  > optansout
  >
  16c34,35
  < There were 11 warnings (use warnings() to see them)
  ---
  > Warning message:
  > In dpois(x, lambda, log) : NaNs produced
  23,26c42,45
  < 1 -3.3769627 13.992596 9.990254
  < 2 -2.3408125 16.743624 6.538606
  < 3 -1.4582091 19.494652 4.793143
  < 4 -0.6872025 22.245680 3.747887
  ---
  > 1 -3.3769529 13.992620 9.990210
  > 2 -2.3408063 16.743642 6.538591
  > 3 -1.4582055 19.494664 4.793137
  > 4 -0.6872010 22.245686 3.747885
  28,34c47,53
  < 6 0.6199927 27.747736 2.567514
  < 7 1.1878580 30.498764 2.205221
  < 8 1.7126041 33.249792 1.926961
  < 9 2.2014998 36.000820 1.707195
  < 10 2.6601431 38.751848 1.529682
  < 11 3.0929263 41.502876 1.383618
  < 12 3.5033531 44.253904 1.261547
  ---
  > 6 0.6199914 27.747730 2.567515
  > 7 1.1878557 30.498752 2.205222
  > 8 1.7126008 33.249774 1.926962
  > 9 2.2014957 36.000796 1.707197
  > 10 2.6601382 38.751818 1.529684
  > 11 3.0929208 41.502840 1.383620
  > 12 3.5033471 44.253863 1.261549
  38,42c57,61
  < 1 -3.6930752 41.342788 1.035622
  < 2 -2.6386153 36.082859 1.372415
  < 3 -1.8618321 32.494520 1.709208
  < 4 -1.2549270 29.876424 2.046002
  < 5 -0.7619514 27.873805 2.382795
  ---
  > 1 -3.6930563 41.342691 1.035627
  > 2 -2.6386042 36.082806 1.372419
  > 3 -1.8618252 32.494490 1.709212
  > 4 -1.2549229 29.876407 2.046004
  > 5 -0.7619491 27.873796 2.382797
  44,58c63,77
  < 7 0.5712040 23.018945 3.729968
  < 8 1.0191678 21.567782 4.403555
  < 9 1.3826779 20.454239 5.077142
  < 10 1.6849411 19.570755 5.750728
  < 11 1.9410502 18.851516 6.424315
  < 12 2.1613344 18.253875 7.097902
  < 13 2.3531486 17.748921 7.771488
  < 14 2.5218978 17.316324 8.445075
  < 15 2.6716589 16.941351 9.118661
  < 16 2.8055737 16.613052 9.792248
  < 17 2.9261091 16.323114 10.465835
  < 18 3.0352320 16.065101 11.139421
  < 19 3.1345330 15.833955 11.813008
  < 20 3.2253136 15.625640 12.486595
  < 21 3.3086506 15.436900 13.160181
  ---
  > 7 0.5712027 23.018949 3.729967
  > 8 1.0191658 21.567789 4.403552
  > 9 1.3826755 20.454247 5.077137
  > 10 1.6849383 19.570763 5.750721
  > 11 1.9410472 18.851524 6.424306
  > 12 2.1613313 18.253883 7.097891
  > 13 2.3531454 17.748929 7.771476
  > 14 2.5218946 17.316332 8.445061
  > 15 2.6716557 16.941359 9.118646
  > 16 2.8055706 16.613060 9.792231
  > 17 2.9261059 16.323121 10.465816
  > 18 3.0352289 16.065108 11.139401
  > 19 3.1345299 15.833962 11.812986
  > 20 3.2253106 15.625647 12.486571
  > 21 3.3086476 15.436906 13.160156
  60c79
  < There were 50 or more warnings (use warnings() to see the first 50)
  ---
  > There were 14 warnings (use warnings() to see them)
  Running ‘order.R’
  Comparing ‘order.Rout’ to ‘order.Rout.save’ ... OK
  Running ‘parscale.R’
  Comparing ‘parscale.Rout’ to ‘parscale.Rout.save’ ...50c50
  < rate 1.045704e-11
  ---
  > rate 1.045669e-11
  147c147
  < rate 1.407221e-11
  ---
  > rate 1.407176e-11
  Running ‘predict.R’
  Comparing ‘predict.Rout’ to ‘predict.Rout.save’ ... OK
  Running ‘richards.R’ [54s/54s]
  Comparing ‘richards.Rout’ to ‘richards.Rout.save’ ...87,92c87,89
  < 1: In dpois(dat, calc_mean(p, times, N, incid = incid), log = TRUE) :
  < NaNs produced
  < 2: In dpois(dat, calc_mean(p, times, N, incid = incid), log = TRUE) :
  < NaNs produced
  < 3: In dpois(dat, calc_mean(p, times, N, incid = incid), log = TRUE) :
  < NaNs produced
  ---
  > 1: In dpois(x, lambda, log) : NaNs produced
  > 2: In dpois(x, lambda, log) : NaNs produced
  > 3: In dpois(x, lambda, log) : NaNs produced
  103,108c100,102
  < 1: In dpois(dat, calc_mean(p, times, N, incid = incid), log = TRUE) :
  < NaNs produced
  < 2: In dpois(dat, calc_mean(p, times, N, incid = incid), log = TRUE) :
  < NaNs produced
  < 3: In dpois(dat, calc_mean(p, times, N, incid = incid), log = TRUE) :
  < NaNs produced
  ---
  > 1: In dpois(x, lambda, log) : NaNs produced
  > 2: In dpois(x, lambda, log) : NaNs produced
  > 3: In dpois(x, lambda, log) : NaNs produced
  Running ‘startvals.R’
  Comparing ‘startvals.Rout’ to ‘startvals.Rout.save’ ...26,28c26,27
  < 1: In lbeta(theta * (1 - prob), theta * prob) : NaNs produced
  < 2: In lbeta(size - x + theta * (1 - prob), x + theta * prob) :
  < NaNs produced
  ---
  > 1: In lbeta(a, b) : NaNs produced
  > 2: In lbeta(a, b) : NaNs produced
  Running ‘startvals2.R’
  Comparing ‘startvals2.Rout’ to ‘startvals2.Rout.save’ ...189,196c189,192
  < 1: In dnorm(x = c(2.99573227355399, 3.76120011569356, 3.71357206670431, :
  < NaNs produced
  < 2: In dnorm(x = c(2.99573227355399, 3.76120011569356, 3.71357206670431, :
  < NaNs produced
  < 3: In dnorm(x = c(2.99573227355399, 3.76120011569356, 3.71357206670431, :
  < NaNs produced
  < 4: In dnorm(x = c(2.99573227355399, 3.76120011569356, 3.71357206670431, :
  < NaNs produced
  ---
  > 1: In dnorm(x, mean, sd, log) : NaNs produced
  > 2: In dnorm(x, mean, sd, log) : NaNs produced
  > 3: In dnorm(x, mean, sd, log) : NaNs produced
  > 4: In dnorm(x, mean, sd, log) : NaNs produced
  Running ‘test-relist1.R’
  Comparing ‘test-relist1.Rout’ to ‘test-relist1.Rout.save’ ... OK
  Running ‘testbounds.R’
  Comparing ‘testbounds.Rout’ to ‘testbounds.Rout.save’ ... OK
  Running ‘testderiv.R’
  Comparing ‘testderiv.Rout’ to ‘testderiv.Rout.save’ ...32,39c32,35
  < 1: In dbinom(x = c(7, 4, 4, 4, 4, 6, 1, 2, 3, 5, 4, 2, 6, 4, 3, 6, :
  < NaNs produced
  < 2: In dbinom(x = c(7, 4, 4, 4, 4, 6, 1, 2, 3, 5, 4, 2, 6, 4, 3, 6, :
  < NaNs produced
  < 3: In dbinom(x = c(7, 4, 4, 4, 4, 6, 1, 2, 3, 5, 4, 2, 6, 4, 3, 6, :
  < NaNs produced
  < 4: In dbinom(x = c(7, 4, 4, 4, 4, 6, 1, 2, 3, 5, 4, 2, 6, 4, 3, 6, :
  < NaNs produced
  ---
  > 1: In dbinom(x, size, prob, log) : NaNs produced
  > 2: In dbinom(x, size, prob, log) : NaNs produced
  > 3: In dbinom(x, size, prob, log) : NaNs produced
  > 4: In dbinom(x, size, prob, log) : NaNs produced
  Running ‘testenv.R’
  Comparing ‘testenv.Rout’ to ‘testenv.Rout.save’ ...21,26c21,26
  < 1 -5.4686708 2.5585122 27.2089090
  < 2 -3.2038315 2.6685690 2.2247879
  < 3 -2.5686071 2.7786257 1.9643700
  < 4 -1.9314586 2.8886824 1.7291896
  < 5 -1.2916431 2.9987392 1.5123049
  < 6 -0.6482128 3.1087959 1.3092611
  ---
  > 1 -5.4686774 2.5585146 27.2088421
  > 2 -3.2038200 2.6685710 2.2247829
  > 3 -2.5685978 2.7786273 1.9643664
  > 4 -1.9314516 2.8886836 1.7291871
  > 5 -1.2916385 2.9987400 1.5123034
  > 6 -0.6482105 3.1087963 1.3092604
  28,32c28,32
  < 8 0.6543910 3.3289094 0.9335199
  < 9 1.3165907 3.4389661 0.7571493
  < 10 1.9884564 3.5490229 0.5870931
  < 11 2.6720642 3.6590796 0.4223480
  < 12 3.3696896 3.7691363 0.2626573
  ---
  > 8 0.6543886 3.3289090 0.9335206
  > 9 1.3165858 3.4389653 0.7571506
  > 10 1.9884490 3.5490217 0.5870949
  > 11 2.6720542 3.6590780 0.4223504
  > 12 3.3696768 3.7691343 0.2626602
  36,48c36,48
  < 1 -3.7698011 3.7316282 0.0151656
  < 2 -2.9354326 3.6249130 0.2355394
  < 3 -2.1408145 3.5190799 0.4559132
  < 4 -1.3862383 3.4153867 0.6762870
  < 5 -0.6722993 3.3149740 0.8966608
  < 6 0.0000000 3.2188527 1.1170346
  < 7 0.6293003 3.1278886 1.3374084
  < 8 1.2140472 3.0427958 1.5577822
  < 9 1.7527518 2.9641245 1.7781560
  < 10 2.2442667 2.8922482 1.9985298
  < 11 2.6880452 2.8273623 2.2189036
  < 12 3.0843330 2.7694823 2.4392774
  < 13 3.4342624 2.7184536 2.6596512
  ---
  > 1 -3.7697805 3.73162558 0.01517093
  > 2 -2.9354168 3.62491097 0.23554367
  > 3 -2.1408033 3.51907842 0.45591641
  > 4 -1.3862312 3.41538568 0.67628915
  > 5 -0.6722959 3.31497356 0.89666188
  > 6 0.0000000 3.21885266 1.11703462
  > 7 0.6292974 3.12788901 1.33740736
  > 8 1.2140418 3.04279663 1.55778009
  > 9 1.7527443 2.96412561 1.77815283
  > 10 2.2442576 2.89224952 1.99852557
  > 11 2.6880351 2.82736380 2.21889831
  > 12 3.0843222 2.76948388 2.43927104
  > 13 3.4342513 2.71845517 2.65964378
  Running ‘testparpred.R’
  Comparing ‘testparpred.Rout’ to ‘testparpred.Rout.save’ ... OK
  Running ‘tmptest.R’
  Comparing ‘tmptest.Rout’ to ‘tmptest.Rout.save’ ... OK
  Running ‘update.R’
  Comparing ‘update.Rout’ to ‘update.Rout.save’ ...11,14c11,12
  < 1: In dpois(x = c(26, 17, 13, 12, 20, 5, 9, 8, 5, 4, 8), lambda = c(15.9069797531213, :
  < NaNs produced
  < 2: In dpois(x = c(26, 17, 13, 12, 20, 5, 9, 8, 5, 4, 8), lambda = c(33.2333275588048, :
  < NaNs produced
  ---
  > 1: In dpois(x, lambda, log) : NaNs produced
  > 2: In dpois(x, lambda, log) : NaNs produced
• checking for unstated dependencies in vignettes ... OK
• checking package vignettes in ‘inst/doc’ ... OK
• checking running R code from vignettes ... [150s/150s] OK
• checking re-building of vignette PDFs ... [147s/147s] OK
• checking PDF version of manual ... OK