Running 'testthat.R' [4s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
  > library(testthat)
  > library(jfa)
  > 
  > test_check("jfa")
  # jfa prior distribution for arm method:
  #      
  # Prior sample size:     51 
  # Prior errors:          1.275 
  # Prior:                 beta(2.275, 50.725)# jfa planning results for beta prior with binomial likelihood:
  #      
  # Materiality:             5% 
  # Confidence:              95% 
  # Sample size:             169 
  # Allowed sample errors:   4.23 
  # Prior parameter alpha:   2.275 
  # Prior parameter beta:    50.725# jfa evaluation results for binomial method with prior:
  #   
  # Materiality:           5% 
  # Confidence:            95% 
  # Upper bound:           4.488% 
  # Sample size:           169 
  # Sample errors:         1 
  # Sum of taints:         3.375  
  # Conclusion:            Approve population-- 1. Failure: Audit workflow (@test-auditPrior.R#44)  -------------------------
  conclusion$confBound not equal to 0.03784768.
  1/1 mismatches
  [1] 0.0449 - 0.0378 == 0.00703
  
  # jfa evaluation results for poisson method:
  #   
  # Materiality:           5% 
  # Confidence:            95% 
  # Upper bound:           4.993% 
  # Sample size:           60 
  # Sample errors:         0 
  # Sum of taints:         0  
  # Conclusion:            Approve population# jfa evaluation results for poisson method with prior:
  #   
  # Materiality:           5% 
  # Confidence:            95% 
  # Upper bound:           4.911% 
  # Sample size:           60 
  # Sample errors:         0 
  # Sum of taints:         0  
  # Conclusion:            Approve population# jfa evaluation results for binomial method:
  #   
  # Materiality:           5% 
  # Confidence:            95% 
  # Upper bound:           4.87% 
  # Sample size:           60 
  # Sample errors:         0 
  # Sum of taints:         0  
  # Conclusion:            Approve population# jfa evaluation results for binomial method with prior:
  #   
  # Materiality:           5% 
  # Confidence:            95% 
  # Upper bound:           4.792% 
  # Sample size:           60 
  # Sample errors:         0 
  # Sum of taints:         0  
  # Conclusion:            Approve population# jfa evaluation results for hypergeometric method:
  #   
  # Materiality:           5% 
  # Confidence:            95% 
  # Upper bound:           4.181% 
  # Sample size:           60 
  # Sample errors:         0 
  # Sum of taints:         0  
  # Conclusion:            Approve population# jfa evaluation results for hypergeometric method with prior:
  #   
  # Materiality:           5% 
  # Confidence:            95% 
  # Upper bound:           4.6% 
  # Sample size:           60 
  # Sample errors:         0 
  # Sum of taints:         0  
  # Conclusion:            Approve population# jfa evaluation results for stringer method:
  #      
  # Confidence:            95% 
  # Upper bound:           4.87% 
  # Sample size:           60 
  # Sample errors:         0 
  # Sum of taints:         0# jfa evaluation results for stringer-meikle method:
  #      
  # Confidence:            95% 
  # Upper bound:           4.87% 
  # Sample size:           60 
  # Sample errors:         0 
  # Sum of taints:         0# jfa evaluation results for stringer-lta method:
  #      
  # Confidence:            95% 
  # Upper bound:           4.87% 
  # Sample size:           60 
  # Sample errors:         0 
  # Sum of taints:         0# jfa evaluation results for stringer-pvz method:
  #      
  # Confidence:            95% 
  # Upper bound:           4.87% 
  # Sample size:           60 
  # Sample errors:         0 
  # Sum of taints:         0# jfa evaluation results for rohrbach method:
  #      
  # Confidence:            95% 
  # Upper bound:           3.088% 
  # Sample size:           60 
  # Sample errors:         0 
  # Sum of taints:         0# jfa evaluation results for moment method:
  #      
  # Confidence:            95% 
  # Upper bound:           4.916% 
  # Sample size:           60 
  # Sample errors:         0 
  # Sum of taints:         0-- 2. Failure: Evaluation with direct method (@test-evaluation.R#148)  ---------
  jfaEval$pointEstimate not equal to 294231.508.
  1/1 mismatches
  [1] 286580 - 294232 == -7652
  
  -- 3. Failure: Evaluation with direct method (@test-evaluation.R#149)  ---------
  jfaEval$lowerBound not equal to 262653.9205.
  1/1 mismatches
  [1] 258356 - 262654 == -4298
  
  -- 4. Failure: Evaluation with direct method (@test-evaluation.R#150)  ---------
  jfaEval$upperBound not equal to 325809.1 - 0.00547.
  1/1 mismatches
  [1] 314803 - 325809 == -11006
  
  -- 5. Failure: Evaluation with difference method (@test-evaluation.R#160)  -----
  jfaEval$pointEstimate not equal to 297454 - 0.0243.
  1/1 mismatches
  [1] 296118 - 297454 == -1336
  
  -- 6. Failure: Evaluation with difference method (@test-evaluation.R#161)  -----
  jfaEval$lowerBound not equal to 297454 - 0.0243.
  1/1 mismatches
  [1] 296118 - 297454 == -1336
  
  -- 7. Failure: Evaluation with difference method (@test-evaluation.R#162)  -----
  jfaEval$upperBound not equal to 297454 - 0.0243.
  1/1 mismatches
  [1] 296118 - 297454 == -1336
  
  -- 8. Failure: Evaluation with quotient method (@test-evaluation.R#172)  -------
  jfaEval$pointEstimate not equal to 297454 - 0.0243.
  1/1 mismatches
  [1] 296118 - 297454 == -1336
  
  -- 9. Failure: Evaluation with quotient method (@test-evaluation.R#173)  -------
  jfaEval$lowerBound not equal to 297454 - 0.0243.
  1/1 mismatches
  [1] 296118 - 297454 == -1336
  
  -- 10. Failure: Evaluation with quotient method (@test-evaluation.R#174)  ------
  jfaEval$upperBound not equal to 297454 - 0.0243.
  1/1 mismatches
  [1] 296118 - 297454 == -1336
  
  -- 11. Failure: Evaluation with regression method (@test-evaluation.R#184)  ----
  jfaEval$pointEstimate not equal to 297454 - 0.0243.
  1/1 mismatches
  [1] 296118 - 297454 == -1336
  
  -- 12. Failure: Evaluation with regression method (@test-evaluation.R#185)  ----
  jfaEval$lowerBound not equal to 297454 - 0.0243.
  1/1 mismatches
  [1] 296118 - 297454 == -1336
  
  -- 13. Failure: Evaluation with regression method (@test-evaluation.R#186)  ----
  jfaEval$upperBound not equal to 297454 - 0.0243.
  1/1 mismatches
  [1] 296118 - 297454 == -1336
  
  # jfa planning results for poisson likelihood:
  #      
  # Materiality:             1% 
  # Confidence:              95% 
  # Sample size:             300 
  # Allowed sample errors:   0# jfa planning results for poisson likelihood:
  #      
  # Materiality:             5% 
  # Confidence:              95% 
  # Sample size:             60 
  # Allowed sample errors:   0# jfa planning results for poisson likelihood:
  #      
  # Materiality:             5% 
  # Confidence:              95% 
  # Sample size:             231 
  # Allowed sample errors:   5.78# jfa planning results for poisson likelihood:
  #      
  # Materiality:             5% 
  # Confidence:              95% 
  # Sample size:             126 
  # Allowed sample errors:   2# jfa planning results for gamma prior with poisson likelihood:
  #      
  # Materiality:             5% 
  # Confidence:              95% 
  # Sample size:             231 
  # Allowed sample errors:   5.78 
  # Prior parameter alpha:   1 
  # Prior parameter beta:    0# jfa planning results for gamma prior with poisson likelihood:
  #      
  # Materiality:             5% 
  # Confidence:              95% 
  # Sample size:             285 
  # Allowed sample errors:   7.12 
  # Prior parameter alpha:   2 
  # Prior parameter beta:    7# jfa planning results for binomial likelihood:
  #      
  # Materiality:             1% 
  # Confidence:              95% 
  # Sample size:             299 
  # Allowed sample errors:   0# jfa planning results for binomial likelihood:
  #      
  # Materiality:             5% 
  # Confidence:              95% 
  # Sample size:             59 
  # Allowed sample errors:   0# jfa planning results for binomial likelihood:
  #      
  # Materiality:             5% 
  # Confidence:              95% 
  # Sample size:             234 
  # Allowed sample errors:   6# jfa planning results for binomial likelihood:
  #      
  # Materiality:             5% 
  # Confidence:              95% 
  # Sample size:             124 
  # Allowed sample errors:   2# jfa planning results for beta prior with binomial likelihood:
  #      
  # Materiality:             5% 
  # Confidence:              95% 
  # Sample size:             220 
  # Allowed sample errors:   5.5 
  # Prior parameter alpha:   1 
  # Prior parameter beta:    1# jfa planning results for beta prior with binomial likelihood:
  #      
  # Materiality:             5% 
  # Confidence:              95% 
  # Sample size:             273 
  # Allowed sample errors:   6.83 
  # Prior parameter alpha:   2 
  # Prior parameter beta:    7# jfa planning results for hypergeometric likelihood:
  #      
  # Materiality:             1% 
  # Confidence:              95% 
  # Sample size:             258 
  # Allowed sample errors:   0# jfa planning results for hypergeometric likelihood:
  #      
  # Materiality:             5% 
  # Confidence:              95% 
  # Sample size:             57 
  # Allowed sample errors:   0# jfa planning results for hypergeometric likelihood:
  #      
  # Materiality:             5% 
  # Confidence:              95% 
  # Sample size:             197 
  # Allowed sample errors:   5# jfa planning results for hypergeometric likelihood:
  #      
  # Materiality:             5% 
  # Confidence:              95% 
  # Sample size:             119 
  # Allowed sample errors:   2# jfa planning results for beta-binomial prior with hypergeometric likelihood:
  #      
  # Materiality:             5% 
  # Confidence:              95% 
  # Sample size:             160 
  # Allowed sample errors:   4 
  # Prior parameter alpha:   1 
  # Prior parameter beta:    1# jfa planning results for beta-binomial prior with hypergeometric likelihood:
  #      
  # Materiality:             5% 
  # Confidence:              95% 
  # Sample size:             193 
  # Allowed sample errors:   5 
  # Prior parameter alpha:   2 
  # Prior parameter beta:    7# jfa sampling results for random random record sampling: 
  #      
  # Population size:         1000 
  # Sample size:             100 
  # Proportion n/N:          0.1# jfa sampling results for random monetary unit sampling: 
  #      
  # Population size:         1000 
  # Sample size:             100 
  # Proportion n/N:          0.1 
  # Percentage of value:     9.91%# jfa sampling results for cell cell record sampling: 
  #      
  # Population size:         1000 
  # Sample size:             100 
  # Proportion n/N:          0.1# jfa sampling results for cell monetary unit sampling: 
  #      
  # Population size:         1000 
  # Sample size:             100 
  # Proportion n/N:          0.1 
  # Percentage of value:     10.971%# jfa sampling results for interval interval record sampling: 
  #      
  # Population size:         1000 
  # Sample size:             100 
  # Proportion n/N:          0.1# jfa sampling results for interval monetary unit sampling: 
  #      
  # Population size:         1000 
  # Sample size:             100 
  # Proportion n/N:          0.1 
  # Percentage of value:     10.387%== testthat results  ===========================================================
  [ OK: 60 | SKIPPED: 0 | WARNINGS: 0 | FAILED: 13 ]
  1. Failure: Audit workflow (@test-auditPrior.R#44) 
  2. Failure: Evaluation with direct method (@test-evaluation.R#148) 
  3. Failure: Evaluation with direct method (@test-evaluation.R#149) 
  4. Failure: Evaluation with direct method (@test-evaluation.R#150) 
  5. Failure: Evaluation with difference method (@test-evaluation.R#160) 
  6. Failure: Evaluation with difference method (@test-evaluation.R#161) 
  7. Failure: Evaluation with difference method (@test-evaluation.R#162) 
  8. Failure: Evaluation with quotient method (@test-evaluation.R#172) 
  9. Failure: Evaluation with quotient method (@test-evaluation.R#173) 
  1. ...
  
  Error: testthat unit tests failed
  Execution halted