Running ‘test_all.R’
Running the tests in ‘tests/test_all.R’ failed.
Complete output:
  > library("testthat")
  > test_check("bssm")
  Loading required package: bssm
  1. Failure: Test that bsm give identical results with gssm (@test_bootstrap_filter.R#10) 
  bsf_gssm$logLik not equal to -36.6658020894499.
  1/1 mismatches
  [1] -29.7 - -36.7 == 6.95
  
  
  2. Failure: Test that bsm give identical results with gssm (@test_bootstrap_filter.R#13) 
  bsf_gssm$alpha[c(1, 2, 11, 20)] not equal to `testvalues`.
  4/4 mismatches (average diff: 1.89)
  [1]  0.9368 - -0.0319 ==  0.969
  [2]  0.3949 -  5.4722 == -5.077
  [3] -0.0319 -  0.9368 == -0.969
  [4]  1.6662 -  2.1985 == -0.532
  
  
  3. Failure: Test that poisson ng_bsm give identical results with ngssm (@test_bootstrap_filter.R#27) 
  bsf_ng_bsm$logLik not equal to -36.4165815198814.
  1/1 mismatches
  [1] -35.2 - -36.4 == 1.23
  
  
  4. Failure: Test that binomial ng_bsm give identical results with ngssm (@test_bootstrap_filter.R#36) 
  out$logLik not equal to -6.7024830631489.
  1/1 mismatches
  [1] -5.68 - -6.7 == 1.02
  
  
  5. Failure: Test that negative binomial ng_bsm give identical results with ngssm (@test_bootstrap_filter.R#45) 
  out$logLik not equal to -13.6549970967291.
  1/1 mismatches
  [1] -13.4 - -13.7 == 0.225
  
  
  6. Failure: Test that still svm works (@test_bootstrap_filter.R#55) ------------
  out$logLik not equal to -933.056099469693.
  1/1 mismatches
  [1] -939 - -933 == -6.11
  
  
  7. Failure: Test that poisson ng_bsm give identical results with ngssm (@test_is.R#18) 
  sim_ng_bsm$weights not equal to `testvalues`.
  4/4 mismatches (average diff: 0.465)
  [1] 1.541 - 1.333 ==  0.208
  [2] 0.229 - 0.979 == -0.750
  [3] 0.158 - 0.327 == -0.169
  [4] 1.687 - 0.954 ==  0.733
  
  
  OMP: Warning #96: Cannot form a team with 24 threads, using 2 instead.
  OMP: Hint: Consider unsetting KMP_ALL_THREADS and OMP_THREAD_LIMIT (if either is set).
  8. Failure: Test that svm still works (@test_is.R#29) --------------------------
  sim$weights not equal to `testvalues`.
  4/4 mismatches (average diff: 2.77)
  [1] 0.0432 - 5.8670 == -5.824
  [2] 0.0371 - 0.2160 == -0.179
  [3] 2.6549 - 0.0131 ==  2.642
  [4] 3.0965 - 0.6666 ==  2.430
  
  
  9. Failure: MCMC results for Gaussian model are correct (@test_mcmc.R#16) ------
  `testvalues` not equivalent to out$posterior.
  3/3 mismatches (average diff: 0.14)
  [1] -23.2 - -23.1 == -0.0912
  [2] -23.3 - -23.3 ==  0.0304
  [3] -24.2 - -23.9 == -0.2998
  
  
  10. Failure: MCMC results for Gaussian model are correct (@test_mcmc.R#21) -----
  `testvalues` not equivalent to out$theta.
  6/6 mismatches (average diff: 0.121)
  [1] 0.821 - 0.760 ==  0.0613
  [2] 0.488 - 0.789 == -0.3011
  [3] 0.523 - 0.537 == -0.0135
  [4] 0.745 - 0.836 == -0.0905
  [5] 0.759 - 0.532 ==  0.2271
  [6] 0.522 - 0.557 == -0.0347
  
  
  11. Failure: MCMC results for Gaussian model are correct (@test_mcmc.R#25) -----
  `testvalues` not equivalent to out$alpha[c(1, 10, 20, 25, 31, 60)].
  6/6 mismatches (average diff: 0.414)
  [1] 1.5705 - 1.3923 ==  0.17818
  [2] 1.4059 - 2.4750 == -1.06910
  [3] 0.0673 - 0.5518 == -0.48442
  [4] 3.1348 - 3.7823 == -0.64749
  [5] 0.1572 - 0.0564 ==  0.10077
  [6] 0.0179 - 0.0164 ==  0.00141
  
  
  12. Failure: MCMC results for Poisson model are correct (@test_mcmc.R#47) ------
  `testvalues` not equal to out$posterior.
  3/3 mismatches (average diff: 0.971)
  [1] -37.2 - -37.1 == -0.0713
  [2] -34.4 - -35.0 ==  0.5886
  [3] -34.5 - -32.2 == -2.2525
  
  
  13. Failure: MCMC results for Poisson model are correct (@test_mcmc.R#51) ------
  `testvalues` not equal to out$theta.
  3/3 mismatches (average diff: 0.246)
  [1] 1.365 - 1.420 == -0.0555
  [2] 0.802 - 0.886 == -0.0840
  [3] 0.784 - 0.186 ==  0.5976
  
  
  14. Failure: MCMC results for Poisson model are correct (@test_mcmc.R#55) ------
  `testvalues` not equal to out$alpha[c(1, 10, 20, 25, 31, 60)].
  6/6 mismatches (average diff: 0.334)
  [1] -0.3688 - 0.2749 == -0.6437
  [2]  0.5406 - 0.3363 ==  0.2043
  [3] -0.3226 - 0.2277 == -0.5503
  [4]  0.3146 - 0.2557 ==  0.0589
  [5] -0.0677 - 0.1589 == -0.2267
  [6]  0.3993 - 0.0815 ==  0.3178
  
  
  15. Failure: MCMC results for binomial model are correct (@test_mcmc.R#70) -----
  `testvalues` not equal to out$posterior.
  3/3 mismatches (average diff: 0.789)
  [1] -35.9 - -35.9 ==  0.0286
  [2] -33.5 - -33.9 ==  0.3397
  [3] -33.4 - -31.4 == -1.9996
  
  
  16. Failure: MCMC results for binomial model are correct (@test_mcmc.R#74) -----
  `testvalues` not equal to out$theta.
  3/3 mismatches (average diff: 0.245)
  [1] 1.366 - 1.421 == -0.0548
  [2] 0.805 - 0.888 == -0.0834
  [3] 0.787 - 0.190 ==  0.5967
  
  
  17. Failure: MCMC results for binomial model are correct (@test_mcmc.R#78) -----
  `testvalues` not equal to out$alpha[c(1, 10, 20, 25, 31, 60)].
  6/6 mismatches (average diff: 0.484)
  [1] -0.4556 - 0.516 == -0.971
  [2]  0.4291 - 0.172 ==  0.257
  [3] -0.1087 - 0.331 == -0.440
  [4]  0.0798 - 0.655 == -0.575
  [5] -0.0959 - 0.414 == -0.510
  [6]  0.3116 - 0.158 ==  0.153
  
  
  18. Failure: MCMC results for negative binomial model are correct (@test_mcmc.R#95) 
  `testvalues` not equal to out$posterior.
  Lengths differ: 4 vs 5
  
  
  19. Failure: MCMC results for negative binomial model are correct (@test_mcmc.R#99) 
  `testvalues` not equal to out$theta.
  Lengths differ: 4 vs 5
  
  
  20. Failure: MCMC results for negative binomial model are correct (@test_mcmc.R#101) 
  1.379821 not equal to out$alpha[1].
  1/1 mismatches
  [1] 1.38 - 1.53 == -0.153
  
  
  21. Failure: MCMC results for negative binomial model are correct (@test_mcmc.R#102) 
  matrix(c(2, 1, 1, 1)) not equivalent to out$counts.
  Lengths differ: 4 vs 5
  
  
  22. Failure: MCMC results for SV model are correct (@test_mcmc.R#117) ----------
  `testvalues` not equivalent to out$posterior.
  Lengths differ: 2 vs 4
  
  
  23. Failure: MCMC results for SV model are correct (@test_mcmc.R#118) ----------
  matrix(2:3, 2, 1) not equivalent to out$counts.
  Lengths differ: 2 vs 4
  
  
  24. Failure: MCMC results for SV model are correct (@test_mcmc.R#123) ----------
  `testvalues` not equivalent to out$theta.
  Lengths differ: 6 vs 12
  
  
  25. Failure: MCMC results for SV model are correct (@test_mcmc.R#126) ----------
  `testvalues` not equivalent to out$alpha[c(1, 10, 20)].
  3/3 mismatches (average diff: 1.32)
  [1] -1.551 - -0.949 == -0.602
  [2] -0.527 - -2.683 ==  2.157
  [3] -1.137 - -2.338 ==  1.201
  
  
  26. Failure: MCMC results for SV model using IS-correction are correct (@test_mcmc.R#154) 
  `testvalues` not equivalent to out$posterior.
  Lengths differ: 4 vs 5
  
  
  27. Failure: MCMC results for SV model using IS-correction are correct (@test_mcmc.R#161) 
  `testvalues` not equivalent to out$theta.
  Lengths differ: 12 vs 15
  
  
  28. Failure: MCMC results for SV model using IS-correction are correct (@test_mcmc.R#164) 
  `testvalues` not equivalent to out$alpha[c(1, 10, 20)].
  3/3 mismatches (average diff: 1.48)
  [1]  1.658 - -1.732 ==  3.3902
  [2]  1.140 -  1.163 == -0.0236
  [3] -0.474 -  0.545 == -1.0199
  
  
  testthat results ================================================================
  OK: 134 SKIPPED: 0 FAILED: 28
  1. Failure: Test that bsm give identical results with gssm (@test_bootstrap_filter.R#10) 
  2. Failure: Test that bsm give identical results with gssm (@test_bootstrap_filter.R#13) 
  3. Failure: Test that poisson ng_bsm give identical results with ngssm (@test_bootstrap_filter.R#27) 
  4. Failure: Test that binomial ng_bsm give identical results with ngssm (@test_bootstrap_filter.R#36) 
  5. Failure: Test that negative binomial ng_bsm give identical results with ngssm (@test_bootstrap_filter.R#45) 
  6. Failure: Test that still svm works (@test_bootstrap_filter.R#55) 
  7. Failure: Test that poisson ng_bsm give identical results with ngssm (@test_is.R#18) 
  8. Failure: Test that svm still works (@test_is.R#29) 
  9. Failure: MCMC results for Gaussian model are correct (@test_mcmc.R#16) 
  1. ...
  
  Error: testthat unit tests failed
  Execution halted