Running 'RunAllTests.R' [291s]
Running the tests in 'tests/RunAllTests.R' failed.
Complete output:
  > # Run all unit tests, i.e. all checks of all test-functions
  > # 
  > # Author: Andre Schuetzenmeister
  > ###############################################################################
  > 
  > library(VCA)
  > library(RUnit)
  > 
  > # enable/disable time-consuming model 1 and model 2 testcases with real-world data
  > # see file "runit.VCAinference.R"
  > 
  > realWorldModel2 <- FALSE
  > realWorldModel1 <- FALSE
  > # large dataset leads to out of memory errors in many testing-environments
  > runTF033.runit.anovaVCA.r  <- FALSE			
  > 
  > options(warn=1)
  > 
  > # current working directory
  > wd <- getwd()
  > 
  > # set path from wd, where RunAllTests.R resided to RUnit test-scripts (scripts directory)
  > sd <- "./runit/UnitTests"
  > tc.path <- sub("\\./", "/", paste0(wd, sd))
  > 
  > # test function regexpr fits to string "TFxyz" which are used as identifiers for easier referencing
  > 
  > testSuite <- defineTestSuite(name="VCA", dirs=tc.path,
  +                              testFileRegexp="runit.*\\.R$",
  + 							 testFuncRegexp = "^TF[[:digit:]]{3}.+",					# use custom regexpr for test functions
  +                              rngKind="default",
  +                              rngNormalKind="default")
  > 
  >                      
  > testData <- runTestSuite(testSuite, verbose=0L)
  
  
  ***************************************************************************
  Variance Component Analysis (VCA) - test cases for function 'VCAinference'.
  ***************************************************************************
  
  Mixed model equations solved locally. Results could not be assigned to object!
  Mixed model equations solved locally. Results could not be assigned to object!
  Mixed model equations solved locally. Results could not be assigned to object!
  Mixed model equations solved locally. Results could not be assigned to object!
  Mixed model equations solved locally. Results could not be assigned to object!
  Mixed model equations solved locally. Results could not be assigned to object!
  Mixed model equations solved locally. Results could not be assigned to object!
  Mixed model equations solved locally. Results could not be assigned to object!
  Mixed model equations solved locally. Results could not be assigned to object!
  Mixed model equations solved locally. Results could not be assigned to object!
  Mixed model equations solved locally. Results could not be assigned to object!
  Mixed model equations solved locally. Results could not be assigned to object!
  Mixed model equations solved locally. Results could not be assigned to object!
  Mixed model equations solved locally. Results could not be assigned to object!
  Mixed model equations solved locally. Results could not be assigned to object!
  
  
  SAS PROC MIXED uses the inverse of the Fisher-Information Matrix as approximation of Covariance-Matrix of Variance Components.
  This is equal to the one obtained via ANOVA-approach stated in "Variance Components" (Searle et al. 1991) in case
  of balanced designs, otherwise Var(VC) of both results may differ:
  
                     SAS_Est   R_Est   SAS_LCL     R_LCL  SAS_UCL    R_UCL
  lot                0.01377 0.01377 -0.013750 -0.016870 0.041280 0.044400
  device             0.06190 0.06190 -0.062340 -0.063040 0.186100 0.186800
  lot:device:day     0.01235 0.01235 -0.004180 -0.004480 0.028870 0.029180
  lot:device:day:run 0.05125 0.05125  0.033110  0.032950 0.069400 0.069560
  error              0.00118 0.00118  0.000932  0.000932 0.001543 0.001543
                     Est_Diff LCL_Diff UCL_Diff
  lot                       0  0.00312 -0.00312
  device                    0  0.00070 -0.00070
  lot:device:day            0  0.00030 -0.00031
  lot:device:day:run        0  0.00016 -0.00016
  error                     0  0.00000  0.00000
  Mixed model equations solved locally. Results could not be assigned to object!
  Mixed model equations solved locally. Results could not be assigned to object!
  
  
  SAS PROC MIXED uses the inverse of the Fisher-Information Matrix as approximation of Covariance-Matrix of Variance Components.
  This is equal to the one obtained via ANOVA-approach stated in "Variance Components" (Searle et al. 1991) in case
  of balanced designs, otherwise Var(VC) of both results may differ:
  
                     SAS_Est   R_Est  SAS_LCL    R_LCL SAS_UCL   R_UCL Est_Diff
  lot                0.18920 0.18920 -0.19090 -0.21540 0.56920 0.59380        0
  device             0.43590 0.43590 -0.46080 -0.45200 1.33260 1.32380        0
  lot:device:day     0.31780 0.31780  0.18600  0.18680 0.44960 0.44870        0
  lot:device:day:run 0.05724 0.05724  0.02931  0.02931 0.08517 0.08517        0
  error              0.04108 0.04108  0.03241  0.03241 0.05376 0.05376        0
                     LCL_Diff UCL_Diff
  lot                  0.0245  -0.0246
  device              -0.0088   0.0088
  lot:device:day      -0.0008   0.0009
  lot:device:day:run   0.0000   0.0000
  error                0.0000   0.0000
  Mixed model equations solved locally. Results could not be assigned to object!
  Mixed model equations solved locally. Results could not be assigned to object!
  
  
  SAS PROC MIXED uses the inverse of the Fisher-Information Matrix as approximation of Covariance-Matrix of Variance Components.
  This is equal to the one obtained via ANOVA-approach stated in "Variance Components" (Searle et al. 1991) in case
  of balanced designs, otherwise Var(VC) of both results may differ:
  
                       SAS_Est     R_Est   SAS_LCL     R_LCL    SAS_UCL
  lot                -0.000850 -0.000850 -0.001540 -0.001690 -1.700e-04
  device              0.058040  0.058040 -0.057620 -0.058080  1.737e-01
  lot:device:day     -0.017410 -0.017410 -0.034820 -0.035110 -3.250e-06
  lot:device:day:run  0.084000  0.084000  0.053940  0.054130  1.141e-01
  error               0.000337  0.000337  0.000266  0.000266  4.400e-04
                           R_UCL Est_Diff LCL_Diff    UCL_Diff
  lot                -0.00002000        0  0.00015 -0.00015000
  device              0.17420000        0  0.00046 -0.00050000
  lot:device:day      0.00028594        0  0.00029 -0.00028919
  lot:device:day:run  0.11390000        0 -0.00019  0.00020000
  error               0.00044000        0  0.00000  0.00000000
  Mixed model equations solved locally. Results could not be assigned to object!
  Mixed model equations solved locally. Results could not be assigned to object!
  Mixed model equations solved locally. Results could not be assigned to object!
  Mixed model equations solved locally. Results could not be assigned to object!
  Warning in VCAinference(fit, ci.method = "satterthwaite") :
    Point estimate(s) of VC(s) 'Site:Day:Run' found outside of confidence interval, CI was set to 'NA'!
  
  
  
  Inference from (V)ariance (C)omponent (A)nalysis
  ------------------------------------------------
  
  > VC:
  -----
               Estimate      DF CI LCL     CI UCL One-Sided LCL One-Sided UCL
  total          0.3405 15.5385 0.1875     0.8005        0.2059        0.6927
  Site           0.1381  2.6726 0.0423     2.4767        0.0510        1.4414
  Site:Day       0.0084  0.4506 0.0012 36811.9725        0.0017     1697.8716
  Site:Day:Run   0.0004  0.0005                                           Inf
  error          0.1936 80.0000 0.1452     0.2710        0.1520        0.2564
  
  
  95% Confidence Level  
  Satterthwaite methodology used for computing CIs 
  
  boundary (singular) fit: see help('isSingular')
  boundary (singular) fit: see help('isSingular')
  
  
  **************************************************************************
  Variance Component Analysis (VCA) - test cases defined in runit.anovaMM.R.
  **************************************************************************
  
  Error in anovaMM() : argument "form" is missing, with no default
  Error in anovaMM(Data = 1) : argument "form" is missing, with no default
  Error in anovaMM(Data = data.frame()) : 
    argument "form" is missing, with no default
  Error in anovaMM(Data = data.frame(y = 1:10)) : 
    argument "form" is missing, with no default
  Error in orderData(Data, tobj, quiet = quiet, order.data = order.data) : 
    all(vars %in% colnames(Data)) is not TRUE
  Error in orderData(Data, tobj, quiet = quiet, order.data = order.data) : 
    all(vars %in% colnames(Data)) is not TRUE
  There are 3 missing values for the response variable (obs: 43, 57, 66)!
  Variable 'run' has 3 missing values (obs: 19, 38, 50)!
  Variable 'day' has 3 missing values (obs: 78, 79, 80)!
  Convert variable Site from "character" to "factor"!
  Convert variable ID from "character" to "factor"!
  Warning in anovaMM(y ~ day + cov + day:(run), dat1) :
    All values of response variable 'y' are equal!
  Warning in anovaMM(y ~ day/(run), dat1) :
    All values of response variable 'y' are equal!
  Warning in anovaMM(y ~ (day)/(run), dat1) :
    All values of response variable 'y' are equal!
  
  
  ***********************************************************************
  Variance Component Analysis (VCA) - test cases for function 'anovaVCA'.
  ***********************************************************************
  
  Error in anovaVCA() : argument "form" is missing, with no default
  Error in anovaVCA(Data = 1) : argument "form" is missing, with no default
  Error in anovaVCA(Data = data.frame()) : 
    argument "form" is missing, with no default
  Error in anovaVCA(Data = data.frame(y = 1:10)) : 
    argument "form" is missing, with no default
  Error in orderData(Data, tobj, quiet = quiet, exclude.numeric = FALSE,  : 
    all(vars %in% colnames(Data)) is not TRUE
  Error in orderData(Data, tobj, quiet = quiet, exclude.numeric = FALSE,  : 
    all(vars %in% colnames(Data)) is not TRUE
  There are 3 missing values for the response variable (obs: 43, 57, 66)!
  Variable 'day' has 3 missing values (obs: 78, 79, 80)!
  Variable 'run' has 3 missing values (obs: 19, 38, 50)!
  Warning in anovaVCA(y ~ day, dat1) :
    All values of response variable 'y' are equal!
  Warning in anovaVCA(y ~ day/run, dat1) :
    All values of response variable 'y' are equal!
  Error in anovaVCA(y ~ day, dataEP05A2_3[seq(1, 77, 4), ]) : 
    Variable 'day': number of levels of each grouping factor must be < number of observations!
  
  
  ***********************************************************************
  Variance Component Analysis (VCA) - test cases defined in runit.misc.R.
  ***********************************************************************
  
  boundary (singular) fit: see help('isSingular')
  Mixed model equations solved locally. Results could not be assigned to object!
  Warning in lsmMat(obj, NULL, quiet = quiet) :
    'Sex:age2' is "numeric", LS Means cannot be estimated,'Sex:age2' will be skipped!
  Warning in lsmMat(obj, NULL, quiet = quiet) :
    'Sex:age2' is "numeric", LS Means cannot be estimated,'Sex:age2' will be skipped!
  Warning in lsmMat(obj, NULL, quiet = quiet) :
    'Sex:age2' is "numeric", LS Means cannot be estimated,'Sex:age2' will be skipped!
  [1] TRUE
  [1] TRUE
  [1] TRUE
  [1] TRUE
  [1] TRUE
  [1] TRUE
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  Mixed model equations were solved but results could not be assigned to 'VCA' object!
  Mixed model equations were solved but results could not be assigned to 'VCA' object!
  Mixed model equations were solved but results could not be assigned to 'VCA' object!
  Mixed model equations were solved but results could not be assigned to 'VCA' object!
  Matrices 'H' and 'Q' were comuted but could not be assigned to 'VCA' object!
  Mixed model equations were solved but results could not be assigned to 'VCA' object!
  Matrices 'H' and 'Q' were comuted but could not be assigned to 'VCA' object!
  Mixed model equations were solved but results could not be assigned to 'VCA' object!
  Matrices 'H' and 'Q' were comuted but could not be assigned to 'VCA' object!
  Matrices 'H' and 'Q' were comuted but could not be assigned to 'VCA' object!
  Mixed model equations were solved but results could not be assigned to 'VCA' object!
  Mixed model equations were solved but results could not be assigned to 'VCA' object!
  Mixed model equations were solved but results could not be assigned to 'VCA' object!
  [1] TRUE
  [1] TRUE
  [1] TRUE
  [1] TRUE
  [1] TRUE
  [1] TRUE
  Note: 'ddfm' set to "satterthwaite", currently option "contain" does not work for REML-estimation!
  Warning in lsmeans(fit.vca, var = "snp", at = list(tim = 1:4)) :
    Argument 'at' was not correctly specified! Neither covariables nor factor variables could be matched!
  Warning in lsmeans(fit.vca, var = "snp", at = list(sex = c(Male = 0.3, Female = 0.6))) :
    Sum of all coefficients of factor-variable 'sex' is not equal to 1! It will be skipped!
  Warning in lsmeans(fit.vca, var = "snp", at = list(sex = c(Male = 0.5, Female = 0.6))) :
    Sum of all coefficients of factor-variable 'sex' is not equal to 1! It will be skipped!
  Error in orderData(Data, tobj, quiet = quiet, order.data = order.data) : 
    all(vars %in% colnames(Data)) is not TRUE
  Error in orderData(Data, trms, quiet = quiet, order.data = order.data) : 
    all(vars %in% colnames(Data)) is not TRUE
  Mixed model equations solved locally. Results could not be assigned to object!
  boundary (singular) fit: see help('isSingular')
  boundary (singular) fit: see help('isSingular')
  boundary (singular) fit: see help('isSingular')
  boundary (singular) fit: see help('isSingular')
  boundary (singular) fit: see help('isSingular')
  boundary (singular) fit: see help('isSingular')
  boundary (singular) fit: see help('isSingular')
  boundary (singular) fit: see help('isSingular')
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  
  sample 1 :
  [1] TRUE
  [1] TRUE
  
  sample 2 :
  [1] TRUE
  [1] TRUE
  boundary (singular) fit: see help('isSingular')
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  boundary (singular) fit: see help('isSingular')
  
  sample 3 :
  [1] TRUE
  [1] TRUE
  
  sample 4 :
  [1] TRUE
  [1] TRUE
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  
  sample 5 :
  [1] TRUE
  [1] TRUE
  boundary (singular) fit: see help('isSingular')
  boundary (singular) fit: see help('isSingular')
  
  sample 6 :
  [1] TRUE
  [1] TRUE
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  
  sample 7 :
  [1] TRUE
  [1] TRUE
  
  sample 8 :
  [1] TRUE
  [1] TRUE
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  
  sample 9 :
  [1] TRUE
  [1] TRUE
  
  sample 10 :
  [1] TRUE
  [1] TRUE
  boundary (singular) fit: see help('isSingular')
  boundary (singular) fit: see help('isSingular')
  boundary (singular) fit: see help('isSingular')
  boundary (singular) fit: see help('isSingular')
  Error in ranef.VCA(fit) : 
    (converted from warning) The fitted model has not been re-scaled yet! Results are likely to differ from correct results!
  Error in residuals.VCA(fit) : 
    (converted from warning) The fitted model has not been re-scaled yet! Results are likely to differ from correct results!
  Mixed model equations were solved but results could not be assigned to 'VCA' object!
  Mixed model equations were solved but results could not be assigned to 'VCA' object!
  Matrices 'H' and 'Q' were comuted but could not be assigned to 'VCA' object!
  Matrices 'H' and 'Q' were comuted but could not be assigned to 'VCA' object!
  Mixed model equations were solved but results could not be assigned to 'VCA' object!
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  Some required information missing! Usually solving mixed model equations has to be done as a prerequisite!
  Matrices 'H' and 'Q' were comuted but could not be assigned to 'VCA' object!
  Matrices 'H' and 'Q' were comuted but could not be assigned to 'VCA' object!
  Mixed model equations solved locally. Results could not be assigned to object!
  Convert variable day from "character" to "factor"!
  Convert variable day from "character" to "factor"!
  
  TF075.protectedCall.anovaVCA
  smpl: Error in Fsweep(M, asgn = asgn) : 
    Inverting the C Matrix failed! Double check the specified model! Are there replicates?
  
  dtld: 
   try-error:Error in Fsweep(M, asgn = asgn) : 
    Inverting the C Matrix failed! Double check the specified model! Are there replicates?
   Additional error checks:
    Levels of 'run' are indistinguishable from levels of 'day'!
  
  TF076.protectedCall.remlVCA
  smpl: Error in solve.default(VCvar[nze, nze]) : 
    system is computationally singular: reciprocal condition number = 1.42946e-28
  
  dtld: 
   try-error:Error in solve.default(VCvar[nze, nze]) : 
    system is computationally singular: reciprocal condition number = 1.42946e-28
   Additional error checks:
    REML-estimation error! Zero variation within factor-levels of 'day:run'!
  
  TF077.protectedCall.remlMM
  smpl: Error in solve.default(VCvar[nze, nze]) : 
    system is computationally singular: reciprocal condition number = 5.73223e-27
  
  dtld: 
   try-error:Error in solve.default(VCvar[nze, nze]) : 
    system is computationally singular: reciprocal condition number = 5.73223e-27
   Additional error checks:
    REML-estimation error! Zero variation within factor-levels of 'day:run'!
  Convert variable day from "character" to "factor"!
  Convert variable day from "character" to "factor"!
  
  TF078.protectedCall.anovaMM
  smpl: Error in Fsweep(M, asgn = asgn) : 
    Inverting the C Matrix failed! Double check the specified model! Are there replicates?
  
  dtld: 
   try-error:Error in Fsweep(M, asgn = asgn) : 
    Inverting the C Matrix failed! Double check the specified model! Are there replicates?
   Additional error checks:
    Levels of 'run' are indistinguishable from levels of 'day'!
  Convert variable day from "character" to "factor"!
  Convert variable day from "character" to "factor"!
  
  TF079.protectedCall.fitVCA.anova
  smpl: Error in Fsweep(M, asgn = asgn) : 
    Inverting the C Matrix failed! Double check the specified model! Are there replicates?
  
  dtld: 
   try-error:Error in Fsweep(M, asgn = asgn) : 
    Inverting the C Matrix failed! Double check the specified model! Are there replicates?
   Additional error checks:
    Levels of 'run' are indistinguishable from levels of 'day'!
  
  TF080.protectedCall.fitVCA.reml
  smpl: Error in solve.default(VCvar[nze, nze]) : 
    system is computationally singular: reciprocal condition number = 1.09583e-28
  
  dtld: 
   try-error:Error in solve.default(VCvar[nze, nze]) : 
    system is computationally singular: reciprocal condition number = 1.09583e-28
   Additional error checks:
    REML-estimation error! Zero variation within factor-levels of 'day:run'!
  Convert variable day from "character" to "factor"!
  Convert variable day from "character" to "factor"!
  
  TF081.protectedCall.fitLMM.anova
  smpl: Error in Fsweep(M, asgn = asgn) : 
    Inverting the C Matrix failed! Double check the specified model! Are there replicates?
  
  dtld: 
   try-error:Error in Fsweep(M, asgn = asgn) : 
    Inverting the C Matrix failed! Double check the specified model! Are there replicates?
   Additional error checks:
    Levels of 'run' are indistinguishable from levels of 'day'!
  
  TF082.protectedCall.fitLMM.remlss
  smpl: Error in solve.default(VCvar[nze, nze]) : 
    system is computationally singular: reciprocal condition number = 2.66558e-27
  
  dtld: 
   try-error:Error in solve.default(VCvar[nze, nze]) : 
    system is computationally singular: reciprocal condition number = 2.66558e-27
   Additional error checks:
    REML-estimation error! Zero variation within factor-levels of 'day:run'!
  Mixed model equations solved locally. Results could not be assigned to object!
  Mixed model equations solved locally. Results could not be assigned to object!
  
  
  (V)ariance (C)omponent (A)nalysis Summary:
  ------------------------------------------
  
  y ~ device + lot + device:lot:day + device:lot:day:run
  <environment: 0x000002eaafd7d148>
  
  
                                 sample.1    sample.2    sample.3   sample.4
  Mean                           2.678798  23.7639580   0.7782802   3.405321
  N                            252.000000 252.0000000 252.0000000 252.000000
  total_DF                      27.677330  10.4631344 106.3063696  52.904536
  total_CV                      11.521830   4.0772765  37.7323877   8.319502
  total_CV_OS_UCL               14.843153   6.4110853  42.5715597   9.921952
  device_DF                      2.000000   2.0000000   2.0000000   2.000000
  device_CV                      4.617069   2.4071231   8.0872550   3.070430
  device_CV_OS_UCL               7.782026   3.9767325  14.3368560   5.223580
  lot_DF                         2.000000   2.0000000   2.0000000   2.000000
  lot_CV                         4.650544   1.8771975   0.0000000   1.594418
  lot_CV_OS_UCL                  7.834560   3.1320676          NA   3.013999
  device:lot:day_DF             58.000000  58.0000000  58.0000000  58.000000
  device:lot:day_CV              4.183296   2.3605729   0.0000000   1.870305
  device:lot:day_CV_OS_UCL       6.070271   2.7367160          NA   3.935697
  device:lot:day:run_DF         63.000000  63.0000000  63.0000000  63.000000
  device:lot:day:run_CV          8.408436   0.9762235  36.7811417   7.215819
  device:lot:day:run_CV_OS_UCL   9.573839   1.1640214  41.8346312   8.220375
  error_DF                     126.000000 126.0000000 126.0000000 126.000000
  error_CV                       1.267246   0.8836037   2.3403004   1.295500
  error_CV_OS_UCL                1.414902   0.9865581   2.6129840   1.446447
                                 sample.5   sample.6    sample.7   sample.8
  Mean                          17.462955   3.458896  48.3054268  92.725640
  N                            252.000000 252.000000 252.0000000 252.000000
  total_DF                      15.178552  93.088028   9.3223311   8.557229
  total_CV                       4.488937   8.087736   4.4752154   4.506293
  total_CV_OS_UCL                6.435376   9.206565   7.2817636   7.536043
  device_DF                      2.000000   2.000000   2.0000000   2.000000
  device_CV                      2.126569   2.134276   2.3280878   1.989328
  device_CV_OS_UCL               3.536592   3.713031   3.8487385   3.301919
  lot_DF                         2.000000   2.000000   2.0000000   2.000000
  lot_CV                         2.234642   0.000000   2.6356079   2.923038
  lot_CV_OS_UCL                  3.708641         NA   4.3416471   4.799338
  device:lot:day_DF             58.000000  58.000000  58.0000000  58.000000
  device:lot:day_CV              2.144759   0.000000   2.3004471   2.005682
  device:lot:day_CV_OS_UCL       2.615303         NA   2.6773175   2.404009
  device:lot:day:run_DF         63.000000  63.000000  63.0000000  63.000000
  device:lot:day:run_CV          1.857450   7.696234   0.9147208   1.536632
  device:lot:day:run_CV_OS_UCL   2.205796   8.765273   1.1543753   1.809268
  error_DF                     126.000000 126.000000 126.0000000 126.000000
  error_CV                       1.607645   1.274489   1.2378853   1.192098
  error_CV_OS_UCL                1.794962   1.422988   1.3821194   1.330997
                                 sample.9  sample.10
  Mean                           2.904678  23.584607
  N                            252.000000 252.000000
  total_DF                      89.602208  11.590610
  total_CV                       9.861496   3.972798
  total_CV_OS_UCL               11.255893   6.074576
  device_DF                      2.000000   2.000000
  device_CV                      2.259144   2.131203
  device_CV_OS_UCL               4.225087   3.522144
  lot_DF                         2.000000   2.000000
  lot_CV                         1.693129   2.040083
  lot_CV_OS_UCL                  3.456151   3.376425
  device:lot:day_DF             58.000000  58.000000
  device:lot:day_CV              4.701276   1.935390
  device:lot:day_CV_OS_UCL       6.447736   2.306301
  device:lot:day:run_DF         63.000000  63.000000
  device:lot:day:run_CV          8.087492   1.307916
  device:lot:day:run_CV_OS_UCL   9.210681   1.571198
  error_DF                     126.000000 126.000000
  error_CV                       1.330103   1.273885
  error_CV_OS_UCL                1.485082   1.422314
  
  
  
  
  (V)ariance (C)omponent (A)nalysis Summary:
  ------------------------------------------
  
  y ~ device + lot + device:lot:day + device:lot:day:run
  <environment: 0x000002eaae272a00>
  
  
                                   sample.1    sample.2     sample.3     sample.4
  Mean                           2.67879779  23.7639580   0.77828016   3.40532077
  N                            252.00000000 252.0000000 252.00000000 252.00000000
  total_DF                      27.67732955  10.4631344 106.30636959  52.90453614
  total_SD                       0.30864653   0.9689223   0.29366369   0.28330573
  total_SD_OS_UCL                0.39761806   1.5235276   0.33132600   0.33787429
  total_CV                      11.52183005   4.0772765  37.73238770   8.31950203
  total_CV_OS_UCL               14.84315308   6.4110853  42.57155973   9.92195197
  device_DF                      2.00000000   2.0000000   2.00000000   2.00000000
  device_SD                      0.12368195   0.5720277   0.06294150   0.10455799
  device_SD_OS_UCL               0.20846473   0.9450291   0.11158091   0.17787964
  device_CV                      4.61706933   2.4071231   8.08725495   3.07043011
  device_CV_OS_UCL               7.78202561   3.9767325  14.33685599   5.22357959
  lot_DF                         2.00000000   2.0000000   2.00000000   2.00000000
  lot_SD                         0.12457866   0.4460964   0.00000000   0.05429504
  lot_SD_OS_UCL                  0.20987202   0.7443032           NA   0.10263632
  lot_CV                         4.65054364   1.8771975   0.00000000   1.59441791
  lot_CV_OS_UCL                  7.83455993   3.1320676           NA   3.01399865
  device:lot:day_DF             58.00000000  58.0000000  58.00000000  58.00000000
  device:lot:day_SD              0.11206204   0.5609655   0.00000000   0.06368988
  device:lot:day_SD_OS_UCL       0.16261028   0.6503520           NA   0.13402309
  device:lot:day_CV              4.18329594   2.3605729   0.00000000   1.87030474
  device:lot:day_CV_OS_UCL       6.07027081   2.7367160           NA   3.93569653
  device:lot:day:run_DF         63.00000000  63.0000000  63.00000000  63.00000000
  device:lot:day:run_SD          0.22524501   0.2319893   0.28626033   0.24572179
  device:lot:day:run_SD_OS_UCL   0.25646379   0.2766175   0.32559064   0.27993012
  device:lot:day:run_CV          8.40843646   0.9762235  36.78114167   7.21581910
  device:lot:day:run_CV_OS_UCL   9.57383906   1.1640214  41.83463125   8.22037450
  error_DF                     126.00000000 126.0000000 126.00000000 126.00000000
  error_SD                       0.03394697   0.2099792   0.01821409   0.04411592
  error_SD_OS_UCL                0.03790235   0.2344453   0.02033634   0.04925615
  error_CV                       1.26724648   0.8836037   2.34030041   1.29549965
  error_CV_OS_UCL                1.41490158   0.9865581   2.61298396   1.44644671
                                  sample.5     sample.6    sample.7   sample.8
  Mean                          17.4629546   3.45889648  48.3054268  92.725640
  N                            252.0000000 252.00000000 252.0000000 252.000000
  total_DF                      15.1785521  93.08802820   9.3223311   8.557229
  total_SD                       0.7839010   0.27974643   2.1617719   4.178489
  total_SD_OS_UCL                1.1238067   0.31844554   3.5174870   6.987844
  total_CV                       4.4889370   8.08773649   4.4752154   4.506293
  total_CV_OS_UCL                6.4353756   9.20656460   7.2817636   7.536043
  device_DF                      2.0000000   2.00000000   2.0000000   2.000000
  device_SD                      0.3713618   0.07382240   1.1245928   1.844617
  device_SD_OS_UCL               0.6175935   0.12842988   1.8591496   3.061726
  device_CV                      2.1265692   2.13427608   2.3280878   1.989328
  device_CV_OS_UCL               3.5365921   3.71303059   3.8487385   3.301919
  lot_DF                         2.0000000   2.00000000   2.0000000   2.000000
  lot_SD                         0.3902345   0.00000000   1.2731416   2.710406
  lot_SD_OS_UCL                  0.6476383           NA   2.0972511   4.450217
  lot_CV                         2.2346418   0.00000000   2.6356079   2.923038
  lot_CV_OS_UCL                  3.7086411           NA   4.3416471   4.799338
  device:lot:day_DF             58.0000000  58.00000000  58.0000000  58.000000
  device:lot:day_SD              0.3745383   0.00000000   1.1112408   1.859782
  device:lot:day_SD_OS_UCL       0.4567092           NA   1.2932896   2.229133
  device:lot:day_CV              2.1447590   0.00000000   2.3004471   2.005682
  device:lot:day_CV_OS_UCL       2.6153033           NA   2.6773175   2.404009
  device:lot:day:run_DF         63.0000000  63.00000000  63.0000000  63.000000
  device:lot:day:run_SD          0.3243656   0.26620478   0.4418598   1.424852
  device:lot:day:run_SD_OS_UCL   0.3851972   0.30318171   0.5576259   1.677656
  device:lot:day:run_CV          1.8574499   7.69623447   0.9147208   1.536632
  device:lot:day:run_CV_OS_UCL   2.2057962   8.76527264   1.1543753   1.809268
  error_DF                     126.0000000 126.00000000 126.0000000 126.000000
  error_SD                       0.2807424   0.04408325   0.5979658   1.105380
  error_SD_OS_UCL                0.3134535   0.04921968   0.6676387   1.234175
  error_CV                       1.6076452   1.27448898   1.2378853   1.192098
  error_CV_OS_UCL                1.7949624   1.42298795   1.3821194   1.330997
                                   sample.9   sample.10
  Mean                           2.90467770  23.5846069
  N                            252.00000000 252.0000000
  total_DF                      89.60220814  11.5906101
  total_SD                       0.28644468   0.9369689
  total_SD_OS_UCL                0.32694742   1.4326650
  total_CV                       9.86149600   3.9727984
  total_CV_OS_UCL               11.25589315   6.0745765
  device_DF                      2.00000000   2.0000000
  device_SD                      0.06562086   0.5026359
  device_SD_OS_UCL               0.12272515   0.8306837
  device_CV                      2.25914424   2.1312032
  device_CV_OS_UCL               4.22508664   3.5221435
  lot_DF                         2.00000000   2.0000000
  lot_SD                         0.04917994   0.4811455
  lot_SD_OS_UCL                  0.10039004   0.7963165
  lot_CV                         1.69312900   2.0400830
  lot_CV_OS_UCL                  3.45615065   3.3764249
  device:lot:day_DF             58.00000000  58.0000000
  device:lot:day_SD              0.13655690   0.4564541
  device:lot:day_SD_OS_UCL       0.18728594   0.5439321
  device:lot:day_CV              4.70127557   1.9353900
  device:lot:day_CV_OS_UCL       6.44773581   2.3063015
  device:lot:day:run_DF         63.00000000  63.0000000
  device:lot:day:run_SD          0.23491556   0.3084668
  device:lot:day:run_SD_OS_UCL   0.26754059   0.3705608
  device:lot:day:run_CV          8.08749155   1.3079157
  device:lot:day:run_CV_OS_UCL   9.21068073   1.5711977
  error_DF                     126.00000000 126.0000000
  error_SD                       0.03863520   0.3004408
  error_SD_OS_UCL                0.04313684   0.3354471
  error_CV                       1.33010277   1.2738852
  error_CV_OS_UCL                1.48508166   1.4223138
  
  
  
  
  (V)ariance (C)omponent (A)nalysis Summary:
  ------------------------------------------
  
  y ~ device + lot + device:lot:day + device:lot:day:run
  <environment: 0x000002eaae272a00>
  
  
                                   sample.1    sample.2     sample.3     sample.4
  Mean                           2.67879779  23.7639580   0.77828016   3.40532077
  N                            252.00000000 252.0000000 252.00000000 252.00000000
  total_DF                      27.67732955  10.4631344 106.30636959  52.90453614
  total_SD                       0.30864653   0.9689223   0.29366369   0.28330573
  total_SD_OS_UCL                0.39761806   1.5235276   0.33132600   0.33787429
  total_CV                      11.52183005   4.0772765  37.73238770   8.31950203
  total_CV_OS_UCL               14.84315308   6.4110853  42.57155973   9.92195197
  device_DF                      2.00000000   2.0000000   2.00000000   2.00000000
  device_SD                      0.12368195   0.5720277   0.06294150   0.10455799
  device_SD_OS_UCL               0.20846473   0.9450291   0.11158091   0.17787964
  device_CV                      4.61706933   2.4071231   8.08725495   3.07043011
  device_CV_OS_UCL               7.78202561   3.9767325  14.33685599   5.22357959
  lot_DF                         2.00000000   2.0000000   2.00000000   2.00000000
  lot_SD                         0.12457866   0.4460964   0.00000000   0.05429504
  lot_SD_OS_UCL                  0.20987202   0.7443032           NA   0.10263632
  lot_CV                         4.65054364   1.8771975   0.00000000   1.59441791
  lot_CV_OS_UCL                  7.83455993   3.1320676           NA   3.01399865
  device:lot:day_DF             58.00000000  58.0000000  58.00000000  58.00000000
  device:lot:day_SD              0.11206204   0.5609655   0.00000000   0.06368988
  device:lot:day_SD_OS_UCL       0.16261028   0.6503520           NA   0.13402309
  device:lot:day_CV              4.18329594   2.3605729   0.00000000   1.87030474
  device:lot:day_CV_OS_UCL       6.07027081   2.7367160           NA   3.93569653
  device:lot:day:run_DF         63.00000000  63.0000000  63.00000000  63.00000000
  device:lot:day:run_SD          0.22524501   0.2319893   0.28626033   0.24572179
  device:lot:day:run_SD_OS_UCL   0.25646379   0.2766175   0.32559064   0.27993012
  device:lot:day:run_CV          8.40843646   0.9762235  36.78114167   7.21581910
  device:lot:day:run_CV_OS_UCL   9.57383906   1.1640214  41.83463125   8.22037450
  error_DF                     126.00000000 126.0000000 126.00000000 126.00000000
  error_SD                       0.03394697   0.2099792   0.01821409   0.04411592
  error_SD_OS_UCL                0.03790235   0.2344453   0.02033634   0.04925615
  error_CV                       1.26724648   0.8836037   2.34030041   1.29549965
  error_CV_OS_UCL                1.41490158   0.9865581   2.61298396   1.44644671
                                  sample.5     sample.6    sample.7   sample.8
  Mean                          17.4629546   3.45889648  48.3054268  92.725640
  N                            252.0000000 252.00000000 252.0000000 252.000000
  total_DF                      15.1785521  93.08802820   9.3223311   8.557229
  total_SD                       0.7839010   0.27974643   2.1617719   4.178489
  total_SD_OS_UCL                1.1238067   0.31844554   3.5174870   6.987844
  total_CV                       4.4889370   8.08773649   4.4752154   4.506293
  total_CV_OS_UCL                6.4353756   9.20656460   7.2817636   7.536043
  device_DF                      2.0000000   2.00000000   2.0000000   2.000000
  device_SD                      0.3713618   0.07382240   1.1245928   1.844617
  device_SD_OS_UCL               0.6175935   0.12842988   1.8591496   3.061726
  device_CV                      2.1265692   2.13427608   2.3280878   1.989328
  device_CV_OS_UCL               3.5365921   3.71303059   3.8487385   3.301919
  lot_DF                         2.0000000   2.00000000   2.0000000   2.000000
  lot_SD                         0.3902345   0.00000000   1.2731416   2.710406
  lot_SD_OS_UCL                  0.6476383           NA   2.0972511   4.450217
  lot_CV                         2.2346418   0.00000000   2.6356079   2.923038
  lot_CV_OS_UCL                  3.7086411           NA   4.3416471   4.799338
  device:lot:day_DF             58.0000000  58.00000000  58.0000000  58.000000
  device:lot:day_SD              0.3745383   0.00000000   1.1112408   1.859782
  device:lot:day_SD_OS_UCL       0.4567092           NA   1.2932896   2.229133
  device:lot:day_CV              2.1447590   0.00000000   2.3004471   2.005682
  device:lot:day_CV_OS_UCL       2.6153033           NA   2.6773175   2.404009
  device:lot:day:run_DF         63.0000000  63.00000000  63.0000000  63.000000
  device:lot:day:run_SD          0.3243656   0.26620478   0.4418598   1.424852
  device:lot:day:run_SD_OS_UCL   0.3851972   0.30318171   0.5576259   1.677656
  device:lot:day:run_CV          1.8574499   7.69623447   0.9147208   1.536632
  device:lot:day:run_CV_OS_UCL   2.2057962   8.76527264   1.1543753   1.809268
  error_DF                     126.0000000 126.00000000 126.0000000 126.000000
  error_SD                       0.2807424   0.04408325   0.5979658   1.105380
  error_SD_OS_UCL                0.3134535   0.04921968   0.6676387   1.234175
  error_CV                       1.6076452   1.27448898   1.2378853   1.192098
  error_CV_OS_UCL                1.7949624   1.42298795   1.3821194   1.330997
                                   sample.9   sample.10
  Mean                           2.90467770  23.5846069
  N                            252.00000000 252.0000000
  total_DF                      89.60220814  11.5906101
  total_SD                       0.28644468   0.9369689
  total_SD_OS_UCL                0.32694742   1.4326650
  total_CV                       9.86149600   3.9727984
  total_CV_OS_UCL               11.25589315   6.0745765
  device_DF                      2.00000000   2.0000000
  device_SD                      0.06562086   0.5026359
  device_SD_OS_UCL               0.12272515   0.8306837
  device_CV                      2.25914424   2.1312032
  device_CV_OS_UCL               4.22508664   3.5221435
  lot_DF                         2.00000000   2.0000000
  lot_SD                         0.04917994   0.4811455
  lot_SD_OS_UCL                  0.10039004   0.7963165
  lot_CV                         1.69312900   2.0400830
  lot_CV_OS_UCL                  3.45615065   3.3764249
  device:lot:day_DF             58.00000000  58.0000000
  device:lot:day_SD              0.13655690   0.4564541
  device:lot:day_SD_OS_UCL       0.18728594   0.5439321
  device:lot:day_CV              4.70127557   1.9353900
  device:lot:day_CV_OS_UCL       6.44773581   2.3063015
  device:lot:day:run_DF         63.00000000  63.0000000
  device:lot:day:run_SD          0.23491556   0.3084668
  device:lot:day:run_SD_OS_UCL   0.26754059   0.3705608
  device:lot:day:run_CV          8.08749155   1.3079157
  device:lot:day:run_CV_OS_UCL   9.21068073   1.5711977
  error_DF                     126.00000000 126.0000000
  error_SD                       0.03863520   0.3004408
  error_SD_OS_UCL                0.04313684   0.3354471
  error_CV                       1.33010277   1.2738852
  error_CV_OS_UCL                1.48508166   1.4223138
  
  
  
  
  **************************************************************************
  Variance Component Analysis (VCA) - test cases defined in runit.remlMM.R.
  **************************************************************************
  
  boundary (singular) fit: see help('isSingular')
  boundary (singular) fit: see help('isSingular')
  Error in remlMM() : argument "form" is missing, with no default
  In addition: There were 16 warnings (use warnings() to see them)
  Error in remlMM(Data = 1) : argument "form" is missing, with no default
  Error in remlMM(Data = data.frame()) : 
    argument "form" is missing, with no default
  Error in remlMM(Data = data.frame(y = 1:10)) : 
    argument "form" is missing, with no default
  Error in orderData(Data, trms, quiet = quiet, order.data = order.data) : 
    all(vars %in% colnames(Data)) is not TRUE
  Error in orderData(Data, trms, quiet = quiet, order.data = order.data) : 
    all(vars %in% colnames(Data)) is not TRUE
  boundary (singular) fit: see help('isSingular')
  boundary (singular) fit: see help('isSingular')
  
  
  ***********************************************************************
  Variance Component Analysis (VCA) - test cases for function 'remlVCA'.
  ***********************************************************************
  
  Error in remlVCA() : argument "form" is missing, with no default
  In addition: Warning messages:
  1: In remlMM(y ~ day + cov + day:(run), dat1) :
    All values of response variable 'y' are equal!
  2: In remlMM(y ~ day/(run), dat1) :
    All values of response variable 'y' are equal!
  3: In remlMM(y ~ (day)/(run), dat1) :
    All values of response variable 'y' are equal!
  Error in remlVCA(Data = 1) : argument "form" is missing, with no default
  Error in remlVCA(Data = data.frame()) : 
    argument "form" is missing, with no default
  Error in remlVCA(Data = data.frame(y = 1:10)) : 
    argument "form" is missing, with no default
  Error in orderData(Data, trms, quiet = quiet, exclude.numeric = FALSE,  : 
    all(vars %in% colnames(Data)) is not TRUE
  Error in orderData(Data, trms, quiet = quiet, exclude.numeric = FALSE,  : 
    all(vars %in% colnames(Data)) is not TRUE
  boundary (singular) fit: see help('isSingular')
  boundary (singular) fit: see help('isSingular')
  boundary (singular) fit: see help('isSingular')
  Warning messages:
  1: In remlVCA(y ~ 1, Data = dataRS0003_1) :
    No random effects specified! Call function 'anovaVCA' instead!
  2: In remlVCA(y ~ 1, Data = dataRS0003_2) :
    No random effects specified! Call function 'anovaVCA' instead!
  3: In remlVCA(y ~ 1, Data = dataRS0003_3) :
    No random effects specified! Call function 'anovaVCA' instead!
  4: In remlVCA(y ~ day, dat1) :
    All values of response variable 'y' are equal!
  5: In remlVCA(y ~ day/run, dat1) :
    All values of response variable 'y' are equal!
  > 
  > sInfo <- sessionInfo()
  > cat("Test Summary Report R-Paket VCA", paste("V", sInfo$otherPkgs[["VCA"]]$Version, sep=""), file="./VCA_UnitTest_Protocol.txt", append=FALSE)
  > cat("\n-------------------------------------", file="./VCA_UnitTest_Protocol.txt", append=TRUE )
  > cat("\n\n\n1) Package Description:", file="./VCA_UnitTest_Protocol.txt", append=TRUE)
  > cat("\n-----------------------\n\n", file="./VCA_UnitTest_Protocol.txt", append=TRUE)
  > capture.output(print(sInfo$otherPkgs[["VCA"]]), file="./VCA_UnitTest_Protocol.txt", append=TRUE)
  > cat("\n\n\n2) Test Environment:", file="./VCA_UnitTest_Protocol.txt", append=TRUE)
  > cat("\n--------------------\n", file="./VCA_UnitTest_Protocol.txt", append=TRUE)
  > sinfo <- Sys.info()
  > snam <- names(sinfo)
  > for(i in 1:length(sinfo))
  + {
  + 	cat(paste("\n", snam[i], paste(rep(" ", 20-nchar(snam[i])), collapse=""), sep=""),":\t", sinfo[i], file="./VCA_UnitTest_Protocol.txt", append=TRUE)
  + }
  > 
  > cat("\n\n\n\n3) Test Protocol:", file="./VCA_UnitTest_Protocol.txt", append=TRUE)
  > cat("\n-----------------\n\n", file="./VCA_UnitTest_Protocol.txt", append=TRUE)
  > 
  > printTextProtocol(testData, showDetails=FALSE)
  RUNIT TEST PROTOCOL -- Sat Mar 23 10:32:09 2024 
  *********************************************** 
  Number of test functions: 179 
  Number of errors: 0 
  Number of failures: 0 
  
   
  1 Test Suite : 
  VCA - 179 test functions, 0 errors, 0 failures
  > capture.output(printTextProtocol(testData, showDetails=TRUE), file="./VCA_UnitTest_Protocol.txt", append=TRUE)
  > printHTMLProtocol(testData, file="./VCA_UnitTest_Protocol.html")
  > 
  > options(warn=0)
  > 
  > 
  > proc.time()
     user  system elapsed 
   130.26    2.35  132.67