Running ‘testthat.R’ [5m/12m]
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$xlevels)`: factor V1 has new levels -0.0939782665799758, -0.12304029781012, -0.201951511736946, -0.223380265155749, -0.340634250680086, -0.386661694538627, -0.43108751551081, -0.445114171893883, -0.456459768849211, -0.605638359324247, -0.691270111535082, -0.854356960386684, -1.01748890226764, -1.02465314084928, -1.06176040139529, -1.13078713129794, -1.66752680612742, 0.027327515596837, 0.0864095668126286, 0.153724248975345, 0.174287366531447, 0.181005814816888, 0.183365667290334, 0.257943141092974, 0.278145630468265, 0.637401390887289, 0.650664405502239, 0.693980779368625, 0.760924984758537, 0.844533378633181, 0.855629183131888, 0.992493298124676, 1.02189796666415, 1.15012697675501, 1.28762144181841, 1.53700455837348, 2.04870851050922, 2.05957522391168, 2.11004904832606, 2.87818571374204
  Backtrace:
       █
    1. ├─testthat::expect_is(...) test_output.R:130:10
    2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
    3. │   └─rlang::eval_bare(expr, quo_get_env(quo))
    4. └─CondIndTests::CondIndTest(X, Y, Z, method = method)
    5.   ├─base::do.call(InvariantTargetPrediction, c(argsSet, parsMethod))
    6.   └─(function (Y, E, X, alpha = 0.05, verbose = FALSE, fitWithGam = TRUE, ...
    7.     └─CondIndTests:::gamTargetY(...)
    8.       └─CondIndTests:::getgamPredictions(...)
    9.         ├─stats::predict(ga, newdata = XTest)
   10.         ├─stats::predict(ga, newdata = XTest)
   11.         └─stats::predict.lm(ga, newdata = XTest)
   12.           ├─stats::model.frame(Terms, newdata, na.action = na.action, xlev = object$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$xlevels)`: factor V1 has new levels -0.0268527643747564, -0.0852421881087856, -0.0989498220608393, -0.186003479865028, -0.225729104900081, -0.260547087359794, -0.501612637814858, -0.732151305525587, -0.791828931127159, -0.834218390088922, -0.991258968841669, -1.16552554007475, -1.33330741200029, -1.63124605600437, -1.77616225728582, -2.21980344419505, 0.0466812818677141, 0.0514188769478138, 0.0542995524852545, 0.203435873302239, 0.244772367350355, 0.256689089492982, 0.333190401642599, 0.429705567947234, 0.535630019118611, 0.57104377755528, 0.657784509766204, 0.854369460201534, 0.885629824303868, 0.930978453246217, 0.992452929278556, 1.04909880737909, 1.20917150464378, 1.23640434556598, 1.24372468677236, 1.33566584145115, 1.39679707733495, 1.6104189286211, 1.67598281786893, 2.40870653929136
  Backtrace:
       █
    1. ├─testthat::expect_is(...) test_output.R:130:10
    2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
    3. │   └─rlang::eval_bare(expr, quo_get_env(quo))
    4. └─CondIndTests::CondIndTest(X, Y, Z, method = method)
    5.   ├─base::do.call(InvariantTargetPrediction, c(argsSet, parsMethod))
    6.   └─(function (Y, E, X, alpha = 0.05, verbose = FALSE, fitWithGam = TRUE, ...
    7.     └─CondIndTests:::gamTargetY(...)
    8.       └─CondIndTests:::getgamPredictions(...)
    9.         ├─stats::predict(ga, newdata = XTest)
   10.         ├─stats::predict(ga, newdata = XTest)
   11.         └─stats::predict.lm(ga, newdata = XTest)
   12.           ├─stats::model.frame(Terms, newdata, na.action = na.action, xlev = object$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$xlevels)`: factor V1 has new levels -0.00619256261920548, -0.0737607741077918, -0.0979882694083263, -0.130572144925714, -0.136978024840809, -0.168924170945936, -0.173698599415799, -0.209840441071639, -0.28509697679095, -0.486654166991383, -0.491650281969602, -0.536251379450931, -0.641532501893077, -0.879811185094477, -0.944084109094019, -1.15045086367372, -1.22078298349947, -1.24273380985648, -1.46197266944443, -1.51941141698395, -1.77581168769384, -1.96516835689965, 0.0388877191603546, 0.0651628378834383, 0.153957448935731, 0.174855840420613, 0.207426588808405, 0.321941351523631, 0.355519412857904, 0.452697824431882, 0.483176065963594, 0.597506419334711, 0.733331105206662, 0.797515386884943, 0.965073219833068, 1.08704311253725, 1.21097482375567, 1.32925049678602, 1.42316032131198, 1.53869690862902
  Backtrace:
       █
    1. ├─testthat::expect_is(...) test_output.R:130:10
    2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
    3. │   └─rlang::eval_bare(expr, quo_get_env(quo))
    4. └─CondIndTests::CondIndTest(X, Y, Z, method = method)
    5.   ├─base::do.call(InvariantTargetPrediction, c(argsSet, parsMethod))
    6.   └─(function (Y, E, X, alpha = 0.05, verbose = FALSE, fitWithGam = TRUE, ...
    7.     └─CondIndTests:::gamTargetY(...)
    8.       └─CondIndTests:::getgamPredictions(...)
    9.         ├─stats::predict(ga, newdata = XTest)
   10.         ├─stats::predict(ga, newdata = XTest)
   11.         └─stats::predict.lm(ga, newdata = XTest)
   12.           ├─stats::model.frame(Terms, newdata, na.action = na.action, xlev = object$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$xlevels)`: factor V1 has new levels -0.0905506855031211, -0.117942008209594, -0.167234997266683, -0.169821302772248, -0.211816150459047, -0.332577166277811, -0.389859619316179, -0.392238660744435, -0.485108032758005, -0.655719339663236, -0.66770989793867, -0.71079442948822, -0.857922415938214, -0.927947417344387, -0.971972953428874, -1.0638032629476, -1.29661536458514, -1.30080785388814, -1.33313648669097, -1.45911804311612, -1.54846822833753, -2.7100663932846, 0.0667731357184102, 0.119650316958855, 0.241876460379034, 0.300118092841789, 0.348835672335828, 0.438578061998758, 0.605580685432306, 0.654474992187946, 0.655548787920353, 0.715827846394734, 0.737938434801388, 0.755128416295637, 0.781248477627998, 0.792634589801282, 0.960316773814245, 1.03545842308621, 1.09412775131815, 1.66301432812756
  Backtrace:
       █
    1. ├─testthat::expect_is(...) test_output.R:130:10
    2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
    3. │   └─rlang::eval_bare(expr, quo_get_env(quo))
    4. └─CondIndTests::CondIndTest(X, Y, Z, method = method)
    5.   ├─base::do.call(InvariantTargetPrediction, c(argsSet, parsMethod))
    6.   └─(function (Y, E, X, alpha = 0.05, verbose = FALSE, fitWithGam = TRUE, ...
    7.     └─CondIndTests:::gamTargetY(...)
    8.       └─CondIndTests:::getgamPredictions(...)
    9.         ├─stats::predict(ga, newdata = XTest)
   10.         ├─stats::predict(ga, newdata = XTest)
   11.         └─stats::predict.lm(ga, newdata = XTest)
   12.           ├─stats::model.frame(Terms, newdata, na.action = na.action, xlev = object$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$xlevels)`: factor V1 has new levels -0.00456103697410603, -0.0766221023125375, -0.118042916772186, -0.168813856437945, -0.200130820917857, -0.331262268256754, -0.423754246924308, -0.433639999979095, -0.436992111112698, -0.46294316376416, -0.463288545272275, -0.502771576729798, -0.559572631173177, -0.608895515813234, -0.733117362218484, -0.907048181634335, -0.926081542162761, -1.04546268049564, -1.11535745980404, -1.34794123428116, -1.5660567811533, -1.80266362267629, -2.26904701535423, 0.0745104486450278, 0.14299027719231, 0.151681591511451, 0.211159065344495, 0.372330780710776, 0.444785887146749, 0.522083778489298, 0.570783916935633, 0.582146106531798, 0.59768746955035, 0.689933637275003, 0.75316960065527, 0.809658551558267, 0.982445957842668, 1.24984801539364, 1.46761428444993, 1.80458376872284
  Backtrace:
       █
    1. ├─testthat::expect_is(...) test_output.R:130:10
    2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
    3. │   └─rlang::eval_bare(expr, quo_get_env(quo))
    4. └─CondIndTests::CondIndTest(X, Y, Z, method = method)
    5.   ├─base::do.call(InvariantTargetPrediction, c(argsSet, parsMethod))
    6.   └─(function (Y, E, X, alpha = 0.05, verbose = FALSE, fitWithGam = TRUE, ...
    7.     └─CondIndTests:::gamTargetY(...)
    8.       └─CondIndTests:::getgamPredictions(...)
    9.         ├─stats::predict(ga, newdata = XTest)
   10.         ├─stats::predict(ga, newdata = XTest)
   11.         └─stats::predict.lm(ga, newdata = XTest)
   12.           ├─stats::model.frame(Terms, newdata, na.action = na.action, xlev = object$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$xlevels)`: factor V1 has new levels -0.0460632295930596, -0.0957351835397751, -0.110741252003523, -0.230228852327217, -0.234478045311599, -0.244640307335496, -0.360732186356189, -0.471103287962942, -0.471757515136013, -0.56074450225278, -0.685518147126179, -0.745580671861082, -0.809018227569033, -0.878470187131555, -0.927622323105353, -0.946213588372619, -0.960844318322151, -1.1527401938684, 0.0429961588204724, 0.0821110460411703, 0.0960751764950113, 0.12643774994891, 0.23998175289909, 0.287636116343282, 0.323241493822534, 0.431436710779364, 0.445438680601139, 0.55010463062733, 0.571106643805524, 0.58615621002786, 0.791129573330844, 0.792302547795301, 0.823544975399554, 0.873279243999482, 1.13816527816649, 1.31161037631392, 1.4515463419513, 1.50555523944533, 1.74324380434349, 2.38025239871688
  Backtrace:
       █
    1. ├─testthat::expect_is(...) test_output.R:130:10
    2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
    3. │   └─rlang::eval_bare(expr, quo_get_env(quo))
    4. └─CondIndTests::CondIndTest(X, Y, Z, method = method)
    5.   ├─base::do.call(InvariantTargetPrediction, c(argsSet, parsMethod))
    6.   └─(function (Y, E, X, alpha = 0.05, verbose = FALSE, fitWithGam = TRUE, ...
    7.     └─CondIndTests:::gamTargetY(...)
    8.       └─CondIndTests:::getgamPredictions(...)
    9.         ├─stats::predict(ga, newdata = XTest)
   10.         ├─stats::predict(ga, newdata = XTest)
   11.         └─stats::predict.lm(ga, newdata = XTest)
   12.           ├─stats::model.frame(Terms, newdata, na.action = na.action, xlev = object$xlevels)
   13.           └─stats::model.frame.default(...)
  
  [ FAIL 6 | WARN 4 | SKIP 0 | PASS 90 ]
  Error: Test failures
  Execution halted