Running ‘testthat.R’ [200s/328s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > library(CondIndTests)
  > 
  > test_check("CondIndTests")
  
  Method: KCI ; Setting 1 
  
  Method: InvariantConditionalQuantilePrediction ; Setting 1 
  
  Method: InvariantEnvironmentPrediction ; Setting 1 
  
  Method: InvariantResidualDistributionTest ; Setting 1 
  
  Method: InvariantTargetPrediction ; Setting 1 
  
  Method: ResidualPredictionTest ; Setting 1 
  
  Method: KCI ; Setting 2 
  
  Method: InvariantConditionalQuantilePrediction ; Setting 2 
  
  Method: InvariantEnvironmentPrediction ; Setting 2 
  
  Method: InvariantResidualDistributionTest ; Setting 2 
  
  Method: InvariantTargetPrediction ; Setting 2 
  Error in names(dat) <- object$term : 
    'names' attribute [1] must be the same length as the vector [0]
  
   *** reducing smoothing df
  Method: ResidualPredictionTest ; Setting 2 
  
  Method: KCI ; Setting 3 
  
  Method: InvariantConditionalQuantilePrediction ; Setting 3 
  
  Method: InvariantEnvironmentPrediction ; Setting 3 
  
  Method: InvariantResidualDistributionTest ; Setting 3 
  
  Method: InvariantTargetPrediction ; Setting 3 
  
  Method: ResidualPredictionTest ; Setting 3 
  
  Method: KCI ; Setting 4 
  
  Method: InvariantConditionalQuantilePrediction ; Setting 4 
  
  Method: InvariantEnvironmentPrediction ; Setting 4 
  
  Method: InvariantResidualDistributionTest ; Setting 4 
  
  Method: InvariantTargetPrediction ; Setting 4 
  Error in names(dat) <- object$term : 
    'names' attribute [1] must be the same length as the vector [0]
  
   *** reducing smoothing df
  Method: ResidualPredictionTest ; Setting 4 
  
  Method: KCI ; Setting 5 
  
  Method: InvariantConditionalQuantilePrediction ; Setting 5 
  
  Method: InvariantEnvironmentPrediction ; Setting 5 
  
  Method: InvariantResidualDistributionTest ; Setting 5 
  
  Method: InvariantTargetPrediction ; Setting 5 
  
  Method: ResidualPredictionTest ; Setting 5 
  
  Method: KCI ; Setting 6 
  
  Method: InvariantConditionalQuantilePrediction ; Setting 6 
  
  Method: InvariantEnvironmentPrediction ; Setting 6 
  
  Method: InvariantResidualDistributionTest ; Setting 6 
  
  Method: InvariantTargetPrediction ; Setting 6 
  Error in names(dat) <- object$term : 
    'names' attribute [1] must be the same length as the vector [0]
  
   *** reducing smoothing df
  Method: ResidualPredictionTest ; Setting 6 
  
  Method: KCI ; Setting 7 
  
  Method: InvariantConditionalQuantilePrediction ; Setting 7 
  
  Method: InvariantEnvironmentPrediction ; Setting 7 
  
  Method: InvariantResidualDistributionTest ; Setting 7 
  
  Method: InvariantTargetPrediction ; Setting 7 
  
  Method: ResidualPredictionTest ; Setting 7 
  
  Method: KCI ; Setting 8 
  
  Method: InvariantConditionalQuantilePrediction ; Setting 8 
  
  Method: InvariantEnvironmentPrediction ; Setting 8 
  
  Method: InvariantResidualDistributionTest ; Setting 8 
  
  Method: InvariantTargetPrediction ; Setting 8 
  Error in names(dat) <- object$term : 
    'names' attribute [1] must be the same length as the vector [0]
  
   *** reducing smoothing df
  Method: ResidualPredictionTest ; Setting 8 
  
  Method: KCI ; Setting 1 
  
  Method: InvariantConditionalQuantilePrediction ; Setting 1 
  
  Method: InvariantEnvironmentPrediction ; Setting 1 
  
  Method: InvariantResidualDistributionTest ; Setting 1 
  
  Method: InvariantTargetPrediction ; Setting 1 
  
  Method: ResidualPredictionTest ; Setting 1 
  
  Method: KCI ; Setting 2 
  
  Method: InvariantConditionalQuantilePrediction ; Setting 2 
  
  Method: InvariantEnvironmentPrediction ; Setting 2 
  
  Method: InvariantResidualDistributionTest ; Setting 2 
  
  Method: InvariantTargetPrediction ; Setting 2 
  
  Method: ResidualPredictionTest ; Setting 2 
  
  Method: KCI ; Setting 3 
  
  Method: InvariantConditionalQuantilePrediction ; Setting 3 
  
  Method: InvariantEnvironmentPrediction ; Setting 3 
  
  Method: InvariantResidualDistributionTest ; Setting 3 
  
  Method: InvariantTargetPrediction ; Setting 3 
  
  Method: ResidualPredictionTest ; Setting 3 
  
  Method: KCI ; Setting 4 
  
  Method: InvariantConditionalQuantilePrediction ; Setting 4 
  
  Method: InvariantEnvironmentPrediction ; Setting 4 
  
  Method: InvariantResidualDistributionTest ; Setting 4 
  
  Method: InvariantTargetPrediction ; Setting 4 
  
  Method: ResidualPredictionTest ; Setting 4 
  
  Method: KCI ; Setting 5 
  
  Method: InvariantConditionalQuantilePrediction ; Setting 5 
  
  Method: InvariantEnvironmentPrediction ; Setting 5 
  
  Method: InvariantResidualDistributionTest ; Setting 5 
  
  Method: InvariantTargetPrediction ; Setting 5 
  
  Method: ResidualPredictionTest ; Setting 5 
  
  Method: KCI ; Setting 6 
  
  Method: InvariantConditionalQuantilePrediction ; Setting 6 
  
  Method: InvariantEnvironmentPrediction ; Setting 6 
  
  Method: InvariantResidualDistributionTest ; Setting 6 
  
  Method: InvariantTargetPrediction ; Setting 6 
  Error in names(dat) <- object$term : 
    'names' attribute [1] must be the same length as the vector [0]
  
   *** reducing smoothing df
  Method: ResidualPredictionTest ; Setting 6 
  
  Method: KCI ; Setting 7 
  
  Method: InvariantConditionalQuantilePrediction ; Setting 7 
  
  Method: InvariantEnvironmentPrediction ; Setting 7 
  
  Method: InvariantResidualDistributionTest ; Setting 7 
  
  Method: InvariantTargetPrediction ; Setting 7 
  
  Method: ResidualPredictionTest ; Setting 7 
  
  Method: KCI ; Setting 8 
  
  Method: InvariantConditionalQuantilePrediction ; Setting 8 
  
  Method: InvariantEnvironmentPrediction ; Setting 8 
  
  Method: InvariantResidualDistributionTest ; Setting 8 
  
  Method: InvariantTargetPrediction ; Setting 8 
  Error in names(dat) <- object$term : 
    'names' attribute [1] must be the same length as the vector [0]
  
   *** reducing smoothing df
  Method: ResidualPredictionTest ; Setting 8 
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error (test_output.R:130:11): Checks output type for InvariantTargetPrediction and setting 2 ──
  Error in `model.frame.default(Terms, newdata, na.action = na.action, xlev = object$xlevels)`: factor V1 has new levels -0.0260992184522832, -0.0801533430841805, -0.128903404127135, -0.141578242652987, -0.233373987645164, -0.571785369224984, -0.587912012062706, -0.596552980797755, -0.775002809091493, -0.852988882580378, -0.885866521798781, -0.974680471773326, -0.974936125393821, -1.04449376051882, -1.21227792402098, -1.24067829909692, -1.27888193858263, -1.86578465806405, -2.18548806519638, 0.0786490568285407, 0.0955759591812767, 0.210511091150445, 0.269144784536258, 0.328275220239483, 0.388711184733258, 0.442364541623667, 0.579061128179959, 0.685031129557866, 0.861978971890402, 0.883055475248145, 1.15528751140553, 1.17462174367338, 1.20465220932224, 1.21426798631526, 1.24340654720188, 1.25626242403315, 1.44379983616521, 1.59451899877665, 1.91702725911189, 2.3090454993959
  Backtrace:
       █
    1. ├─testthat::expect_is(...) test_output.R:130:10
    2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
    3. │   └─rlang::eval_bare(expr, quo_get_env(quo))
    4. └─CondIndTests::CondIndTest(X, Y, Z, method = method)
    5.   ├─base::do.call(InvariantTargetPrediction, c(argsSet, parsMethod))
    6.   └─(function (Y, E, X, alpha = 0.05, verbose = FALSE, fitWithGam = TRUE, ...
    7.     └─CondIndTests:::gamTargetY(...)
    8.       └─CondIndTests:::getgamPredictions(...)
    9.         ├─stats::predict(ga, newdata = XTest)
   10.         ├─stats::predict(ga, newdata = XTest)
   11.         └─stats::predict.lm(ga, newdata = XTest)
   12.           ├─stats::model.frame(Terms, newdata, na.action = na.action, xlev = object$xlevels)
   13.           └─stats::model.frame.default(...)
  ── Error (test_output.R:130:11): Checks output type for InvariantTargetPrediction and setting 4 ──
  Error in `model.frame.default(Terms, newdata, na.action = na.action, xlev = object$xlevels)`: factor V1 has new levels -0.00939396331568474, -0.0491226743223273, -0.129138276094229, -0.141829927586973, -0.259036236044676, -0.261476831267129, -0.386368517240693, -0.387565985689425, -0.473673983268438, -0.602605754854299, -0.665678177122549, -0.86106964787631, -0.923828510799271, -0.946254130801312, -1.02460483379736, -1.19026183675142, -1.63763274482241, -2.136736815414, -2.53776295733108, -2.75186893475817, -2.80287408241344, 0.0562481215327753, 0.179878775939577, 0.200260932846519, 0.207037466533787, 0.220796699439403, 0.251884108470032, 0.257167215364097, 0.308256306901398, 0.462571594159074, 0.484400915096023, 0.504825113886058, 0.761555517646422, 0.978772615068083, 1.31395816813029, 1.51205977552919, 1.84726457141832, 2.21802807735853, 2.60996368319572, 3.19592281538441
  Backtrace:
       █
    1. ├─testthat::expect_is(...) test_output.R:130:10
    2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
    3. │   └─rlang::eval_bare(expr, quo_get_env(quo))
    4. └─CondIndTests::CondIndTest(X, Y, Z, method = method)
    5.   ├─base::do.call(InvariantTargetPrediction, c(argsSet, parsMethod))
    6.   └─(function (Y, E, X, alpha = 0.05, verbose = FALSE, fitWithGam = TRUE, ...
    7.     └─CondIndTests:::gamTargetY(...)
    8.       └─CondIndTests:::getgamPredictions(...)
    9.         ├─stats::predict(ga, newdata = XTest)
   10.         ├─stats::predict(ga, newdata = XTest)
   11.         └─stats::predict.lm(ga, newdata = XTest)
   12.           ├─stats::model.frame(Terms, newdata, na.action = na.action, xlev = object$xlevels)
   13.           └─stats::model.frame.default(...)
  ── Error (test_output.R:130:11): Checks output type for InvariantTargetPrediction and setting 6 ──
  Error in `model.frame.default(Terms, newdata, na.action = na.action, xlev = object$xlevels)`: factor V1 has new levels -0.0221636788807677, -0.0928246574193374, -0.160905692844673, -0.245680561021413, -0.253595409775315, -0.339155878274343, -0.347816146875316, -0.382844918942802, -0.387024488893594, -0.440222388965938, -0.598797161138528, -0.611038267736847, -0.668579335162604, -0.809023472197944, -0.872362838610206, -1.01824116835322, -1.0236089401825, -1.37412388003565, -1.81724199742251, 0.0532833702615206, 0.121435021377675, 0.156206273069402, 0.276892322833046, 0.309666249532559, 0.370652312034763, 0.447457716054909, 0.513777888000343, 0.541864865069384, 0.573717095120821, 0.658958962547983, 0.732327892711055, 0.769100679980138, 0.896743572902073, 0.929999145398253, 0.997056541258636, 1.12545879289885, 1.3996426629846, 1.76362571031645, 2.07538212663036, 3.06572342759619
  Backtrace:
       █
    1. ├─testthat::expect_is(...) test_output.R:130:10
    2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
    3. │   └─rlang::eval_bare(expr, quo_get_env(quo))
    4. └─CondIndTests::CondIndTest(X, Y, Z, method = method)
    5.   ├─base::do.call(InvariantTargetPrediction, c(argsSet, parsMethod))
    6.   └─(function (Y, E, X, alpha = 0.05, verbose = FALSE, fitWithGam = TRUE, ...
    7.     └─CondIndTests:::gamTargetY(...)
    8.       └─CondIndTests:::getgamPredictions(...)
    9.         ├─stats::predict(ga, newdata = XTest)
   10.         ├─stats::predict(ga, newdata = XTest)
   11.         └─stats::predict.lm(ga, newdata = XTest)
   12.           ├─stats::model.frame(Terms, newdata, na.action = na.action, xlev = object$xlevels)
   13.           └─stats::model.frame.default(...)
  ── Error (test_output.R:130:11): Checks output type for InvariantTargetPrediction and setting 8 ──
  Error in `model.frame.default(Terms, newdata, na.action = na.action, xlev = object$xlevels)`: factor V1 has new levels -0.00187712541849613, -0.0511467981943777, -0.0595105554475646, -0.130343413432615, -0.234625084659959, -0.29182193466848, -0.33069353579478, -0.33744213864294, -0.369654404778396, -0.382183774413791, -0.455520236279343, -0.538562128423792, -0.577194318472905, -0.673266085617537, -0.789526360147075, -0.892526615559236, -0.909399748746355, -0.911889211232163, -1.06728616050026, -1.17994185883186, -1.57721320448892, -1.63892483333963, 0.0405304644350704, 0.0892076003573692, 0.0923462385414561, 0.100664712584943, 0.106731569475283, 0.156875521749791, 0.165844200476713, 0.181167526802521, 0.328805433819233, 0.332418663036856, 0.356980447633014, 0.418524818223612, 0.47171527924254, 0.756596661315777, 0.818561073615901, 0.858616053455229, 0.872183200955017, 0.940853137856928
  Backtrace:
       █
    1. ├─testthat::expect_is(...) test_output.R:130:10
    2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
    3. │   └─rlang::eval_bare(expr, quo_get_env(quo))
    4. └─CondIndTests::CondIndTest(X, Y, Z, method = method)
    5.   ├─base::do.call(InvariantTargetPrediction, c(argsSet, parsMethod))
    6.   └─(function (Y, E, X, alpha = 0.05, verbose = FALSE, fitWithGam = TRUE, ...
    7.     └─CondIndTests:::gamTargetY(...)
    8.       └─CondIndTests:::getgamPredictions(...)
    9.         ├─stats::predict(ga, newdata = XTest)
   10.         ├─stats::predict(ga, newdata = XTest)
   11.         └─stats::predict.lm(ga, newdata = XTest)
   12.           ├─stats::model.frame(Terms, newdata, na.action = na.action, xlev = object$xlevels)
   13.           └─stats::model.frame.default(...)
  ── Error (test_output.R:130:11): Checks output type for InvariantTargetPrediction and setting 6 ──
  Error in `model.frame.default(Terms, newdata, na.action = na.action, xlev = object$xlevels)`: factor V1 has new levels -0.0986617582704426, -0.117472428308033, -0.193510017653419, -0.253860409138829, -0.33770401662028, -0.425934721668916, -0.463497202753685, -0.511535574563773, -0.542540202758997, -0.557316601679472, -0.568416639976609, -0.57741221609147, -0.580736956341632, -0.613662846719831, -1.07081976579017, -1.14360210286735, -1.21561082816308, -1.24260857707394, 0.0257088274710163, 0.0438529849415475, 0.158879156643944, 0.199150209178321, 0.296245000627549, 0.301391015340981, 0.331382381069996, 0.683375516324751, 0.728785758479478, 0.812433591878805, 0.854586036070153, 1.07524383121853, 1.07989116298024, 1.08938537953521, 1.35397033529815, 1.43316679433514, 1.44186989641205, 1.56448418660341, 1.56605846427997, 1.60409895032162, 1.67204140132118, 2.79286085202346
  Backtrace:
       █
    1. ├─testthat::expect_is(...) test_output.R:130:10
    2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
    3. │   └─rlang::eval_bare(expr, quo_get_env(quo))
    4. └─CondIndTests::CondIndTest(X, Y, Z, method = method)
    5.   ├─base::do.call(InvariantTargetPrediction, c(argsSet, parsMethod))
    6.   └─(function (Y, E, X, alpha = 0.05, verbose = FALSE, fitWithGam = TRUE, ...
    7.     └─CondIndTests:::gamTargetY(...)
    8.       └─CondIndTests:::getgamPredictions(...)
    9.         ├─stats::predict(ga, newdata = XTest)
   10.         ├─stats::predict(ga, newdata = XTest)
   11.         └─stats::predict.lm(ga, newdata = XTest)
   12.           ├─stats::model.frame(Terms, newdata, na.action = na.action, xlev = object$xlevels)
   13.           └─stats::model.frame.default(...)
  ── Error (test_output.R:130:11): Checks output type for InvariantTargetPrediction and setting 8 ──
  Error in `model.frame.default(Terms, newdata, na.action = na.action, xlev = object$xlevels)`: factor V1 has new levels -0.00854554632535414, -0.0728794795245317, -0.0736865568799379, -0.112746058408944, -0.115711881686401, -0.165079639162208, -0.199215286278185, -0.200641740234181, -0.385808708983672, -0.439780841074682, -0.605190121545504, -0.660028518758795, -0.780759672855708, -0.91433999842244, -0.929890277403389, -1.10490114361467, -1.46867579236675, -1.48230171473253, -1.56409676753, -1.65696044438433, -1.91386814937294, -2.17925222128641, -2.66300664211502, 0.0275683697593044, 0.0957047807487568, 0.104989113992654, 0.355657612101638, 0.467955220882075, 0.520546454770957, 0.581032117469588, 0.621676431317436, 0.695246279809597, 0.892447886587174, 0.913193186890937, 0.92512987266355, 1.24974243317418, 1.43670187228419, 1.44016832524395, 1.54216401476187, 1.90340131300388
  Backtrace:
       █
    1. ├─testthat::expect_is(...) test_output.R:130:10
    2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
    3. │   └─rlang::eval_bare(expr, quo_get_env(quo))
    4. └─CondIndTests::CondIndTest(X, Y, Z, method = method)
    5.   ├─base::do.call(InvariantTargetPrediction, c(argsSet, parsMethod))
    6.   └─(function (Y, E, X, alpha = 0.05, verbose = FALSE, fitWithGam = TRUE, ...
    7.     └─CondIndTests:::gamTargetY(...)
    8.       └─CondIndTests:::getgamPredictions(...)
    9.         ├─stats::predict(ga, newdata = XTest)
   10.         ├─stats::predict(ga, newdata = XTest)
   11.         └─stats::predict.lm(ga, newdata = XTest)
   12.           ├─stats::model.frame(Terms, newdata, na.action = na.action, xlev = object$xlevels)
   13.           └─stats::model.frame.default(...)
  
  [ FAIL 6 | WARN 5 | SKIP 0 | PASS 90 ]
  Error: Test failures
  Execution halted