CRAN Package Check Results for Package jfa

Last updated on 2020-04-02 21:47:47 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.1.0 3.41 32.07 35.48 OK
r-devel-linux-x86_64-debian-gcc 0.1.0 3.00 25.35 28.35 OK
r-devel-linux-x86_64-fedora-clang 0.1.0 43.78 OK
r-devel-linux-x86_64-fedora-gcc 0.1.0 43.48 OK
r-devel-windows-ix86+x86_64 0.1.0 10.00 42.00 52.00 OK
r-devel-windows-ix86+x86_64-gcc8 0.1.0 7.00 45.00 52.00 OK
r-patched-linux-x86_64 0.1.0 4.15 31.21 35.36 OK
r-patched-solaris-x86 0.1.0 64.50 OK
r-release-linux-x86_64 0.1.0 3.13 29.31 32.44 OK
r-release-windows-ix86+x86_64 0.1.0 6.00 43.00 49.00 OK
r-release-osx-x86_64 0.1.0 OK
r-oldrel-windows-ix86+x86_64 0.1.0 6.00 44.00 50.00 ERROR
r-oldrel-osx-x86_64 0.1.0 ERROR

Check Details

Version: 0.1.0
Check: tests
Result: ERROR
     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
Flavor: r-oldrel-windows-ix86+x86_64

Version: 0.1.0
Check: tests
Result: ERROR
     Running ‘testthat.R’ [3s/3s]
    Running the tests in ‘tests/testthat.R’ failed.
    Last 13 lines of output:
     # 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
Flavor: r-oldrel-osx-x86_64