CRAN Package Check Results for Package trialr

Last updated on 2020-04-07 15:48:48 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.1.3 777.66 422.50 1200.16 NOTE
r-devel-linux-x86_64-debian-gcc 0.1.4 732.35 302.45 1034.80 NOTE
r-devel-linux-x86_64-fedora-clang 0.1.4 974.89 NOTE
r-devel-linux-x86_64-fedora-gcc 0.1.4 1791.86 NOTE
r-devel-windows-ix86+x86_64 0.1.3 1856.00 777.00 2633.00 ERROR
r-devel-windows-ix86+x86_64-gcc8 0.1.3 1324.00 626.00 1950.00 NOTE
r-patched-linux-x86_64 0.1.3 710.19 430.93 1141.12 NOTE
r-patched-solaris-x86 0.1.4 1455.80 NOTE
r-release-linux-x86_64 0.1.4 702.62 376.13 1078.75 NOTE
r-release-windows-ix86+x86_64 0.1.3 1674.00 724.00 2398.00 ERROR
r-release-osx-x86_64 0.1.3 NOTE
r-oldrel-windows-ix86+x86_64 0.1.3 1404.00 511.00 1915.00 ERROR
r-oldrel-osx-x86_64 0.1.3 NOTE

Check Details

Version: 0.1.3
Check: for GNU extensions in Makefiles
Result: NOTE
    GNU make is a SystemRequirements.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-windows-ix86+x86_64, r-devel-windows-ix86+x86_64-gcc8, r-patched-linux-x86_64, r-release-windows-ix86+x86_64, r-release-osx-x86_64, r-oldrel-windows-ix86+x86_64, r-oldrel-osx-x86_64

Version: 0.1.4
Check: for GNU extensions in Makefiles
Result: NOTE
    GNU make is a SystemRequirements.
Flavors: r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-patched-solaris-x86, r-release-linux-x86_64

Version: 0.1.4
Check: installed package size
Result: NOTE
     installed size is 126.9Mb
     sub-directories of 1Mb or more:
     doc 3.8Mb
     libs 122.1Mb
Flavors: r-devel-linux-x86_64-fedora-clang, r-patched-solaris-x86

Version: 0.1.4
Check: dependencies in R code
Result: NOTE
    Namespace in Imports field not imported from: ‘tidyr’
     All declared Imports should be used.
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-patched-solaris-x86

Version: 0.1.3
Check: installed package size
Result: NOTE
     installed size is 16.5Mb
     sub-directories of 1Mb or more:
     doc 4.1Mb
     libs 11.5Mb
Flavors: r-devel-windows-ix86+x86_64, r-devel-windows-ix86+x86_64-gcc8, r-release-windows-ix86+x86_64, r-release-osx-x86_64, r-oldrel-windows-ix86+x86_64, r-oldrel-osx-x86_64

Version: 0.1.3
Check: running tests for arch ‘i386’
Result: ERROR
     Running 'testthat.R' [128s]
    Running the tests in 'tests/testthat.R' failed.
    Complete output:
     > library(testthat)
     > library(trialr)
     Loading required package: Rcpp
     >
     > test_check("trialr")
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 1).
     Chain 1:
     Chain 1: Gradient evaluation took 0 seconds
     Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 1: Adjust your expectations accordingly!
     Chain 1:
     Chain 1:
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     Chain 1: Iteration: 1001 / 2000 [ 50%] (Sampling)
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     Chain 1: Iteration: 1800 / 2000 [ 90%] (Sampling)
     Chain 1: Iteration: 2000 / 2000 [100%] (Sampling)
     Chain 1:
     Chain 1: Elapsed Time: 0.031 seconds (Warm-up)
     Chain 1: 0.031 seconds (Sampling)
     Chain 1: 0.062 seconds (Total)
     Chain 1:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 2).
     Chain 2:
     Chain 2: Gradient evaluation took 0 seconds
     Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 2: Adjust your expectations accordingly!
     Chain 2:
     Chain 2:
     Chain 2: Iteration: 1 / 2000 [ 0%] (Warmup)
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     Chain 2: Iteration: 1800 / 2000 [ 90%] (Sampling)
     Chain 2: Iteration: 2000 / 2000 [100%] (Sampling)
     Chain 2:
     Chain 2: Elapsed Time: 0.032 seconds (Warm-up)
     Chain 2: 0.046 seconds (Sampling)
     Chain 2: 0.078 seconds (Total)
     Chain 2:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 3).
     Chain 3:
     Chain 3: Gradient evaluation took 0 seconds
     Chain 3: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 3: Adjust your expectations accordingly!
     Chain 3:
     Chain 3:
     Chain 3: Iteration: 1 / 2000 [ 0%] (Warmup)
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     Chain 3: Iteration: 1001 / 2000 [ 50%] (Sampling)
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     Chain 3: Iteration: 1800 / 2000 [ 90%] (Sampling)
     Chain 3: Iteration: 2000 / 2000 [100%] (Sampling)
     Chain 3:
     Chain 3: Elapsed Time: 0.032 seconds (Warm-up)
     Chain 3: 0.046 seconds (Sampling)
     Chain 3: 0.078 seconds (Total)
     Chain 3:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 4).
     Chain 4:
     Chain 4: Gradient evaluation took 0 seconds
     Chain 4: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 4: Adjust your expectations accordingly!
     Chain 4:
     Chain 4:
     Chain 4: Iteration: 1 / 2000 [ 0%] (Warmup)
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     Chain 4:
     Chain 4: Elapsed Time: 0.032 seconds (Warm-up)
     Chain 4: 0.031 seconds (Sampling)
     Chain 4: 0.063 seconds (Total)
     Chain 4:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 1).
     Chain 1:
     Chain 1: Gradient evaluation took 0 seconds
     Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 1: Adjust your expectations accordingly!
     Chain 1:
     Chain 1:
     Chain 1: Iteration: 1 / 2000 [ 0%] (Warmup)
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     Chain 1: Iteration: 1001 / 2000 [ 50%] (Sampling)
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     Chain 1: Iteration: 1800 / 2000 [ 90%] (Sampling)
     Chain 1: Iteration: 2000 / 2000 [100%] (Sampling)
     Chain 1:
     Chain 1: Elapsed Time: 0.031 seconds (Warm-up)
     Chain 1: 0.032 seconds (Sampling)
     Chain 1: 0.063 seconds (Total)
     Chain 1:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 2).
     Chain 2:
     Chain 2: Gradient evaluation took 0 seconds
     Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 2: Adjust your expectations accordingly!
     Chain 2:
     Chain 2:
     Chain 2: Iteration: 1 / 2000 [ 0%] (Warmup)
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     Chain 2: Iteration: 1001 / 2000 [ 50%] (Sampling)
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     Chain 2: Iteration: 1800 / 2000 [ 90%] (Sampling)
     Chain 2: Iteration: 2000 / 2000 [100%] (Sampling)
     Chain 2:
     Chain 2: Elapsed Time: 0.016 seconds (Warm-up)
     Chain 2: 0.031 seconds (Sampling)
     Chain 2: 0.047 seconds (Total)
     Chain 2:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 3).
     Chain 3:
     Chain 3: Gradient evaluation took 0 seconds
     Chain 3: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 3: Adjust your expectations accordingly!
     Chain 3:
     Chain 3:
     Chain 3: Iteration: 1 / 2000 [ 0%] (Warmup)
     Chain 3: Iteration: 200 / 2000 [ 10%] (Warmup)
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     Chain 3: Iteration: 1800 / 2000 [ 90%] (Sampling)
     Chain 3: Iteration: 2000 / 2000 [100%] (Sampling)
     Chain 3:
     Chain 3: Elapsed Time: 0.031 seconds (Warm-up)
     Chain 3: 0.031 seconds (Sampling)
     Chain 3: 0.062 seconds (Total)
     Chain 3:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 4).
     Chain 4:
     Chain 4: Gradient evaluation took 0 seconds
     Chain 4: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 4: Adjust your expectations accordingly!
     Chain 4:
     Chain 4:
     Chain 4: Iteration: 1 / 2000 [ 0%] (Warmup)
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     Chain 4: Iteration: 1800 / 2000 [ 90%] (Sampling)
     Chain 4: Iteration: 2000 / 2000 [100%] (Sampling)
     Chain 4:
     Chain 4: Elapsed Time: 0.047 seconds (Warm-up)
     Chain 4: 0.031 seconds (Sampling)
     Chain 4: 0.078 seconds (Total)
     Chain 4:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 1).
     Chain 1:
     Chain 1: Gradient evaluation took 0 seconds
     Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 1: Adjust your expectations accordingly!
     Chain 1:
     Chain 1:
     Chain 1: Iteration: 1 / 2000 [ 0%] (Warmup)
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     Chain 1: Iteration: 2000 / 2000 [100%] (Sampling)
     Chain 1:
     Chain 1: Elapsed Time: 0.047 seconds (Warm-up)
     Chain 1: 0.047 seconds (Sampling)
     Chain 1: 0.094 seconds (Total)
     Chain 1:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 2).
     Chain 2:
     Chain 2: Gradient evaluation took 0 seconds
     Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 2: Adjust your expectations accordingly!
     Chain 2:
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     Chain 2: Iteration: 1 / 2000 [ 0%] (Warmup)
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     Chain 2:
     Chain 2: Elapsed Time: 0.031 seconds (Warm-up)
     Chain 2: 0.031 seconds (Sampling)
     Chain 2: 0.062 seconds (Total)
     Chain 2:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 3).
     Chain 3:
     Chain 3: Gradient evaluation took 0 seconds
     Chain 3: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 3: Adjust your expectations accordingly!
     Chain 3:
     Chain 3:
     Chain 3: Iteration: 1 / 2000 [ 0%] (Warmup)
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     Chain 3: Iteration: 2000 / 2000 [100%] (Sampling)
     Chain 3:
     Chain 3: Elapsed Time: 0.031 seconds (Warm-up)
     Chain 3: 0.031 seconds (Sampling)
     Chain 3: 0.062 seconds (Total)
     Chain 3:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 4).
     Chain 4:
     Chain 4: Gradient evaluation took 0 seconds
     Chain 4: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 4: Adjust your expectations accordingly!
     Chain 4:
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     Chain 4: Iteration: 1 / 2000 [ 0%] (Warmup)
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     Chain 4:
     Chain 4: Elapsed Time: 0.031 seconds (Warm-up)
     Chain 4: 0.047 seconds (Sampling)
     Chain 4: 0.078 seconds (Total)
     Chain 4:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 1).
     Chain 1:
     Chain 1: Gradient evaluation took 0 seconds
     Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 1: Adjust your expectations accordingly!
     Chain 1:
     Chain 1:
     Chain 1: Iteration: 1 / 2000 [ 0%] (Warmup)
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     Chain 1:
     Chain 1: Elapsed Time: 0.031 seconds (Warm-up)
     Chain 1: 0.047 seconds (Sampling)
     Chain 1: 0.078 seconds (Total)
     Chain 1:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 2).
     Chain 2:
     Chain 2: Gradient evaluation took 0 seconds
     Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 2: Adjust your expectations accordingly!
     Chain 2:
     Chain 2:
     Chain 2: Iteration: 1 / 2000 [ 0%] (Warmup)
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     Chain 2:
     Chain 2: Elapsed Time: 0.031 seconds (Warm-up)
     Chain 2: 0.031 seconds (Sampling)
     Chain 2: 0.062 seconds (Total)
     Chain 2:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 3).
     Chain 3:
     Chain 3: Gradient evaluation took 0 seconds
     Chain 3: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 3: Adjust your expectations accordingly!
     Chain 3:
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     Chain 3:
     Chain 3: Elapsed Time: 0.031 seconds (Warm-up)
     Chain 3: 0.031 seconds (Sampling)
     Chain 3: 0.062 seconds (Total)
     Chain 3:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 4).
     Chain 4:
     Chain 4: Gradient evaluation took 0 seconds
     Chain 4: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 4: Adjust your expectations accordingly!
     Chain 4:
     Chain 4:
     Chain 4: Iteration: 1 / 2000 [ 0%] (Warmup)
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     Chain 4:
     Chain 4: Elapsed Time: 0.047 seconds (Warm-up)
     Chain 4: 0.047 seconds (Sampling)
     Chain 4: 0.094 seconds (Total)
     Chain 4:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 1).
     Chain 1:
     Chain 1: Gradient evaluation took 0 seconds
     Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 1: Adjust your expectations accordingly!
     Chain 1:
     Chain 1:
     Chain 1: Iteration: 1 / 2000 [ 0%] (Warmup)
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     Chain 1:
     Chain 1: Elapsed Time: 0.047 seconds (Warm-up)
     Chain 1: 0.046 seconds (Sampling)
     Chain 1: 0.093 seconds (Total)
     Chain 1:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 2).
     Chain 2:
     Chain 2: Gradient evaluation took 0 seconds
     Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 2: Adjust your expectations accordingly!
     Chain 2:
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     -- 1. Error: careful_escalation advocates start_dose when n = 0 (@test_stan_crm.
     Assigned data `draws[, c(".chain", ".iteration", ".draw")]` must be compatible with existing data.
     x Existing data has 16000 rows.
     x Element 1 of assigned data has 4000 rows.
     i Only vectors of size 1 are recycled.
     Backtrace:
     1. trialr::careful_escalation(...)
     3. trialr:::prob_tox_exceeds.dose_finding_fit(...)
     10. tidybayes::gather_draws(., prob_tox[dose])
     12. base::lapply(...)
     13. tidybayes:::FUN(X[[i]], ...)
     16. tidybayes:::spread_draws_(...)
     17. tidybayes:::spread_draws_long_(...)
     19. tibble:::`[<-.tbl_df`(...)
     20. tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
     21. tibble:::vectbl_recycle_rhs(...)
     22. base::tryCatch(...)
     23. base:::tryCatchList(expr, classes, parentenv, handlers)
     24. base:::tryCatchOne(expr, names, parentenv, handlers[[1L]])
     25. value[[3L]](cond)
    
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 1).
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     Chain 4:
     -- 2. Error: careful_escalation does not skip doses (@test_stan_crm.R#386) ----
     Assigned data `draws[, c(".chain", ".iteration", ".draw")]` must be compatible with existing data.
     x Existing data has 16000 rows.
     x Element 1 of assigned data has 4000 rows.
     i Only vectors of size 1 are recycled.
     Backtrace:
     1. trialr::careful_escalation(fit1, tox_threshold = 0.33, certainty_threshold = 0.8)
     3. trialr:::prob_tox_exceeds.dose_finding_fit(...)
     10. tidybayes::gather_draws(., prob_tox[dose])
     12. base::lapply(...)
     13. tidybayes:::FUN(X[[i]], ...)
     16. tidybayes:::spread_draws_(...)
     17. tidybayes:::spread_draws_long_(...)
     19. tibble:::`[<-.tbl_df`(...)
     20. tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
     21. tibble:::vectbl_recycle_rhs(...)
     22. base::tryCatch(...)
     23. base:::tryCatchList(expr, classes, parentenv, handlers)
     24. base:::tryCatchOne(expr, names, parentenv, handlers[[1L]])
     25. value[[3L]](cond)
    
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 1).
     Chain 1:
     Chain 1: Gradient evaluation took 0 seconds
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     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 2).
     Chain 2:
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     -- 3. Error: careful_escalation stops appropriately (@test_stan_crm.R#405) ----
     Assigned data `draws[, c(".chain", ".iteration", ".draw")]` must be compatible with existing data.
     x Existing data has 16000 rows.
     x Element 1 of assigned data has 4000 rows.
     i Only vectors of size 1 are recycled.
     Backtrace:
     1. trialr::careful_escalation(...)
     3. trialr:::prob_tox_exceeds.dose_finding_fit(...)
     10. tidybayes::gather_draws(., prob_tox[dose])
     12. base::lapply(...)
     13. tidybayes:::FUN(X[[i]], ...)
     16. tidybayes:::spread_draws_(...)
     17. tidybayes:::spread_draws_long_(...)
     19. tibble:::`[<-.tbl_df`(...)
     20. tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
     21. tibble:::vectbl_recycle_rhs(...)
     22. base::tryCatch(...)
     23. base:::tryCatchList(expr, classes, parentenv, handlers)
     24. base:::tryCatchOne(expr, names, parentenv, handlers[[1L]])
     25. value[[3L]](cond)
    
    
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     == testthat results ===========================================================
     [ OK: 732 | SKIPPED: 0 | WARNINGS: 34 | FAILED: 3 ]
     1. Error: careful_escalation advocates start_dose when n = 0 (@test_stan_crm.R#361)
     2. Error: careful_escalation does not skip doses (@test_stan_crm.R#386)
     3. Error: careful_escalation stops appropriately (@test_stan_crm.R#405)
    
     Error: testthat unit tests failed
     Execution halted
Flavor: r-devel-windows-ix86+x86_64

Version: 0.1.3
Check: running tests for arch ‘x64’
Result: ERROR
     Running 'testthat.R' [119s]
    Running the tests in 'tests/testthat.R' failed.
    Complete output:
     > library(testthat)
     > library(trialr)
     Loading required package: Rcpp
     >
     > test_check("trialr")
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 1).
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     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 1).
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     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 3).
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     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 4).
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     Chain 4:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 1).
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     Chain 1: Gradient evaluation took 0 seconds
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     Chain 1:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 2).
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     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 3).
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     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 4).
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     -- 1. Error: careful_escalation advocates start_dose when n = 0 (@test_stan_crm.
     Assigned data `draws[, c(".chain", ".iteration", ".draw")]` must be compatible with existing data.
     x Existing data has 16000 rows.
     x Element 1 of assigned data has 4000 rows.
     i Only vectors of size 1 are recycled.
     Backtrace:
     1. trialr::careful_escalation(...)
     3. trialr:::prob_tox_exceeds.dose_finding_fit(...)
     10. tidybayes::gather_draws(., prob_tox[dose])
     12. base::lapply(...)
     13. tidybayes:::FUN(X[[i]], ...)
     16. tidybayes:::spread_draws_(...)
     17. tidybayes:::spread_draws_long_(...)
     19. tibble:::`[<-.tbl_df`(...)
     20. tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
     21. tibble:::vectbl_recycle_rhs(...)
     22. base::tryCatch(...)
     23. base:::tryCatchList(expr, classes, parentenv, handlers)
     24. base:::tryCatchOne(expr, names, parentenv, handlers[[1L]])
     25. value[[3L]](cond)
    
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 1).
     Chain 1:
     Chain 1: Gradient evaluation took 0 seconds
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     Chain 1: Adjust your expectations accordingly!
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     Chain 1: 0.078 seconds (Total)
     Chain 1:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 2).
     Chain 2:
     Chain 2: Gradient evaluation took 0 seconds
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     Chain 2: 0.062 seconds (Total)
     Chain 2:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 3).
     Chain 3:
     Chain 3: Gradient evaluation took 0 seconds
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     Chain 3: 0.078 seconds (Total)
     Chain 3:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 4).
     Chain 4:
     Chain 4: Gradient evaluation took 0 seconds
     Chain 4: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 4: Adjust your expectations accordingly!
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     Chain 4:
     -- 2. Error: careful_escalation does not skip doses (@test_stan_crm.R#386) ----
     Assigned data `draws[, c(".chain", ".iteration", ".draw")]` must be compatible with existing data.
     x Existing data has 16000 rows.
     x Element 1 of assigned data has 4000 rows.
     i Only vectors of size 1 are recycled.
     Backtrace:
     1. trialr::careful_escalation(fit1, tox_threshold = 0.33, certainty_threshold = 0.8)
     3. trialr:::prob_tox_exceeds.dose_finding_fit(...)
     10. tidybayes::gather_draws(., prob_tox[dose])
     12. base::lapply(...)
     13. tidybayes:::FUN(X[[i]], ...)
     16. tidybayes:::spread_draws_(...)
     17. tidybayes:::spread_draws_long_(...)
     19. tibble:::`[<-.tbl_df`(...)
     20. tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
     21. tibble:::vectbl_recycle_rhs(...)
     22. base::tryCatch(...)
     23. base:::tryCatchList(expr, classes, parentenv, handlers)
     24. base:::tryCatchOne(expr, names, parentenv, handlers[[1L]])
     25. value[[3L]](cond)
    
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 1).
     Chain 1:
     Chain 1: Gradient evaluation took 0 seconds
     Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 1: Adjust your expectations accordingly!
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     Chain 1:
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     Chain 1: 0.047 seconds (Sampling)
     Chain 1: 0.094 seconds (Total)
     Chain 1:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 2).
     Chain 2:
     Chain 2: Gradient evaluation took 0 seconds
     Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 2: Adjust your expectations accordingly!
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     Chain 2:
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     Chain 2: 0.093 seconds (Total)
     Chain 2:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 3).
     Chain 3:
     Chain 3: Gradient evaluation took 0 seconds
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     Chain 3: Adjust your expectations accordingly!
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     Chain 3: 0.047 seconds (Sampling)
     Chain 3: 0.094 seconds (Total)
     Chain 3:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 4).
     Chain 4:
     Chain 4: Gradient evaluation took 0 seconds
     Chain 4: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 4: Adjust your expectations accordingly!
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     Chain 4:
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     Chain 4:
     -- 3. Error: careful_escalation stops appropriately (@test_stan_crm.R#405) ----
     Assigned data `draws[, c(".chain", ".iteration", ".draw")]` must be compatible with existing data.
     x Existing data has 16000 rows.
     x Element 1 of assigned data has 4000 rows.
     i Only vectors of size 1 are recycled.
     Backtrace:
     1. trialr::careful_escalation(...)
     3. trialr:::prob_tox_exceeds.dose_finding_fit(...)
     10. tidybayes::gather_draws(., prob_tox[dose])
     12. base::lapply(...)
     13. tidybayes:::FUN(X[[i]], ...)
     16. tidybayes:::spread_draws_(...)
     17. tidybayes:::spread_draws_long_(...)
     19. tibble:::`[<-.tbl_df`(...)
     20. tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
     21. tibble:::vectbl_recycle_rhs(...)
     22. base::tryCatch(...)
     23. base:::tryCatchList(expr, classes, parentenv, handlers)
     24. base:::tryCatchOne(expr, names, parentenv, handlers[[1L]])
     25. value[[3L]](cond)
    
    
     SAMPLING FOR MODEL 'EffTox' NOW (CHAIN 1).
     Chain 1:
     Chain 1: Gradient evaluation took 0 seconds
     Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 1: Adjust your expectations accordingly!
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     Chain 1:
     Chain 1: Elapsed Time: 0.093 seconds (Warm-up)
     Chain 1: 0.063 seconds (Sampling)
     Chain 1: 0.156 seconds (Total)
     Chain 1:
    
     SAMPLING FOR MODEL 'EffTox' NOW (CHAIN 2).
     Chain 2:
     Chain 2: Gradient evaluation took 0 seconds
     Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 2: Adjust your expectations accordingly!
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     Chain 2: Elapsed Time: 0.125 seconds (Warm-up)
     Chain 2: 0.046 seconds (Sampling)
     Chain 2: 0.171 seconds (Total)
     Chain 2:
    
     SAMPLING FOR MODEL 'EffTox' NOW (CHAIN 1).
     Chain 1:
     Chain 1: Gradient evaluation took 0.016 seconds
     Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 160 seconds.
     Chain 1: Adjust your expectations accordingly!
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     Chain 1:
     Chain 1: Elapsed Time: 0.156 seconds (Warm-up)
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     Chain 1: 0.374 seconds (Total)
     Chain 1:
    
     SAMPLING FOR MODEL 'EffTox' NOW (CHAIN 2).
     Chain 2:
     Chain 2: Gradient evaluation took 0 seconds
     Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 2: Adjust your expectations accordingly!
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     Chain 2: Elapsed Time: 0.156 seconds (Warm-up)
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     Chain 2: 0.421 seconds (Total)
     Chain 2:
    
     SAMPLING FOR MODEL 'EffTox' NOW (CHAIN 3).
     Chain 3:
     Chain 3: Gradient evaluation took 0 seconds
     Chain 3: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 3: Adjust your expectations accordingly!
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     Chain 3: Elapsed Time: 0.172 seconds (Warm-up)
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     Chain 3: 0.281 seconds (Total)
     Chain 3:
    
     SAMPLING FOR MODEL 'EffTox' NOW (CHAIN 4).
     Chain 4:
     Chain 4: Gradient evaluation took 0 seconds
     Chain 4: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 4: Adjust your expectations accordingly!
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     Chain 4: 0.266 seconds (Total)
     Chain 4:
    
     SAMPLING FOR MODEL 'EffTox' NOW (CHAIN 1).
     Chain 1:
     Chain 1: Gradient evaluation took 0 seconds
     Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 1: Adjust your expectations accordingly!
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     Chain 1: Elapsed Time: 0.187 seconds (Warm-up)
     Chain 1: 0.125 seconds (Sampling)
     Chain 1: 0.312 seconds (Total)
     Chain 1:
    
     SAMPLING FOR MODEL 'EffTox' NOW (CHAIN 2).
     Chain 2:
     Chain 2: Gradient evaluation took 0 seconds
     Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 2: Adjust your expectations accordingly!
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     Chain 2: 0.303 seconds (Total)
     Chain 2:
    
     SAMPLING FOR MODEL 'EffTox' NOW (CHAIN 3).
     Chain 3:
     Chain 3: Gradient evaluation took 0 seconds
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     Chain 3: Adjust your expectations accordingly!
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     Chain 3: Elapsed Time: 0.233 seconds (Warm-up)
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     Chain 3: 0.358 seconds (Total)
     Chain 3:
    
     SAMPLING FOR MODEL 'EffTox' NOW (CHAIN 4).
     Chain 4:
     Chain 4: Gradient evaluation took 0 seconds
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     Chain 4: Adjust your expectations accordingly!
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     Chain 4: 0.327 seconds (Total)
     Chain 4:
    
     SAMPLING FOR MODEL 'EffTox' NOW (CHAIN 1).
     Chain 1:
     Chain 1: Gradient evaluation took 0 seconds
     Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 1: Adjust your expectations accordingly!
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     Chain 4:
     == testthat results ===========================================================
     [ OK: 732 | SKIPPED: 0 | WARNINGS: 37 | FAILED: 3 ]
     1. Error: careful_escalation advocates start_dose when n = 0 (@test_stan_crm.R#361)
     2. Error: careful_escalation does not skip doses (@test_stan_crm.R#386)
     3. Error: careful_escalation stops appropriately (@test_stan_crm.R#405)
    
     Error: testthat unit tests failed
     Execution halted
Flavor: r-devel-windows-ix86+x86_64

Version: 0.1.3
Check: re-building of vignette outputs
Result: WARN
    Error(s) in re-building vignettes:
    --- re-building 'BEBOP.Rmd' using rmarkdown
    Loading required package: Rcpp
    ci_level: 0.8 (80% intervals)
    outer_level: 0.95 (95% intervals)
    --- finished re-building 'BEBOP.Rmd'
    
    --- re-building 'CRM-pathways.Rmd' using rmarkdown
    Loading required package: Rcpp
    
    Attaching package: 'dplyr'
    
    The following objects are masked from 'package:stats':
    
     filter, lag
    
    The following objects are masked from 'package:base':
    
     intersect, setdiff, setequal, union
    
    New names:
    * `` -> ...1
    * `` -> ...2
    * `` -> ...3
    * `` -> ...4
    * `` -> ...5
    Quitting from lines 128-136 (CRM-pathways.Rmd)
    Error: processing vignette 'CRM-pathways.Rmd' failed with diagnostics:
    Assigned data `draws[, c(".chain", ".iteration", ".draw")]` must be compatible with existing data.
    x Existing data has 20000 rows.
    x Element 1 of assigned data has 4000 rows.
    i Only vectors of size 1 are recycled.
    --- failed re-building 'CRM-pathways.Rmd'
    
    --- re-building 'CRM-visualisation.Rmd' using rmarkdown
    Loading required package: Rcpp
    
    Attaching package: 'dplyr'
    
    The following objects are masked from 'package:stats':
    
     filter, lag
    
    The following objects are masked from 'package:base':
    
     intersect, setdiff, setequal, union
    
    Quitting from lines 61-68 (CRM-visualisation.Rmd)
    Error: processing vignette 'CRM-visualisation.Rmd' failed with diagnostics:
    Assigned data `draws[, c(".chain", ".iteration", ".draw")]` must be compatible with existing data.
    x Existing data has 20000 rows.
    x Element 1 of assigned data has 4000 rows.
    i Only vectors of size 1 are recycled.
    --- failed re-building 'CRM-visualisation.Rmd'
    
    --- re-building 'CRM.Rmd' using rmarkdown
    Loading required package: Rcpp
    Warning: There were 1 divergent transitions after warmup. Increasing adapt_delta above 0.8 may help. See
    http://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup
    Warning: Examine the pairs() plot to diagnose sampling problems
    
    --- finished re-building 'CRM.Rmd'
    
    --- re-building 'EffTox.Rmd' using rmarkdown
    Loading required package: Rcpp
    --- finished re-building 'EffTox.Rmd'
    
    --- re-building 'HierarchicalBayesianResponse.Rmd' using rmarkdown
    Loading required package: Rcpp
    Loading required package: StanHeaders
    rstan (Version 2.19.3, GitRev: 2e1f913d3ca3)
    For execution on a local, multicore CPU with excess RAM we recommend calling
    options(mc.cores = parallel::detectCores()).
    To avoid recompilation of unchanged Stan programs, we recommend calling
    rstan_options(auto_write = TRUE)
    For improved execution time, we recommend calling
    Sys.setenv(LOCAL_CPPFLAGS = '-march=corei7 -mtune=corei7')
    although this causes Stan to throw an error on a few processors.
    
    Attaching package: 'dplyr'
    
    The following objects are masked from 'package:stats':
    
     filter, lag
    
    The following objects are masked from 'package:base':
    
     intersect, setdiff, setequal, union
    
    ci_level: 0.8 (80% intervals)
    outer_level: 0.95 (95% intervals)
    --- finished re-building 'HierarchicalBayesianResponse.Rmd'
    
    --- re-building 'LevyCaseStudy.Rmd' using rmarkdown
    
    Attaching package: 'dplyr'
    
    The following objects are masked from 'package:stats':
    
     filter, lag
    
    The following objects are masked from 'package:base':
    
     intersect, setdiff, setequal, union
    
    Warning: There were 1975 divergent transitions after warmup. Increasing adapt_delta above 0.8 may help. See
    http://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup
    Warning: Examine the pairs() plot to diagnose sampling problems
    
    Warning: Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable.
    Running the chains for more iterations may help. See
    http://mc-stan.org/misc/warnings.html#bulk-ess
    Warning: Tail Effective Samples Size (ESS) is too low, indicating posterior variances and tail quantiles may be unreliable.
    Running the chains for more iterations may help. See
    http://mc-stan.org/misc/warnings.html#tail-ess
    Warning: There were 1943 divergent transitions after warmup. Increasing adapt_delta above 0.8 may help. See
    http://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup
    Warning: Examine the pairs() plot to diagnose sampling problems
    
    Warning: Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable.
    Running the chains for more iterations may help. See
    http://mc-stan.org/misc/warnings.html#bulk-ess
    Warning: Tail Effective Samples Size (ESS) is too low, indicating posterior variances and tail quantiles may be unreliable.
    Running the chains for more iterations may help. See
    http://mc-stan.org/misc/warnings.html#tail-ess
    Warning: There were 2073 divergent transitions after warmup. Increasing adapt_delta above 0.8 may help. See
    http://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup
    Warning: Examine the pairs() plot to diagnose sampling problems
    
    Warning: The largest R-hat is NA, indicating chains have not mixed.
    Running the chains for more iterations may help. See
    http://mc-stan.org/misc/warnings.html#r-hat
    Warning: Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable.
    Running the chains for more iterations may help. See
    http://mc-stan.org/misc/warnings.html#bulk-ess
    Warning: Tail Effective Samples Size (ESS) is too low, indicating posterior variances and tail quantiles may be unreliable.
    Running the chains for more iterations may help. See
    http://mc-stan.org/misc/warnings.html#tail-ess
    Warning: There were 1999 divergent transitions after warmup. Increasing adapt_delta above 0.8 may help. See
    http://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup
    Warning: Examine the pairs() plot to diagnose sampling problems
    
    Warning: Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable.
    Running the chains for more iterations may help. See
    http://mc-stan.org/misc/warnings.html#bulk-ess
    Warning: There were 2028 divergent transitions after warmup. Increasing adapt_delta above 0.8 may help. See
    http://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup
    Warning: Examine the pairs() plot to diagnose sampling problems
    
    Warning: There were 1995 divergent transitions after warmup. Increasing adapt_delta above 0.8 may help. See
    http://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup
    Warning: Examine the pairs() plot to diagnose sampling problems
    
    Warning: Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable.
    Running the chains for more iterations may help. See
    http://mc-stan.org/misc/warnings.html#bulk-ess
    Warning: There were 2058 divergent transitions after warmup. Increasing adapt_delta above 0.8 may help. See
    http://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup
    Warning: Examine the pairs() plot to diagnose sampling problems
    
    Warning: Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable.
    Running the chains for more iterations may help. See
    http://mc-stan.org/misc/warnings.html#bulk-ess
    Warning: There were 185 divergent transitions after warmup. Increasing adapt_delta above 0.99 may help. See
    http://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup
    Warning: Examine the pairs() plot to diagnose sampling problems
    
    Warning: There were 66 divergent transitions after warmup. Increasing adapt_delta above 0.99 may help. See
    http://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup
    Warning: Examine the pairs() plot to diagnose sampling problems
    
    Warning: There were 17 divergent transitions after warmup. Increasing adapt_delta above 0.99 may help. See
    http://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup
    Warning: Examine the pairs() plot to diagnose sampling problems
    
    Warning: There were 1 divergent transitions after warmup. Increasing adapt_delta above 0.99 may help. See
    http://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup
    Warning: Examine the pairs() plot to diagnose sampling problems
    
    Warning: There were 1 divergent transitions after warmup. Increasing adapt_delta above 0.99 may help. See
    http://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup
    Warning: Examine the pairs() plot to diagnose sampling problems
    
    Warning: There were 1 divergent transitions after warmup. Increasing adapt_delta above 0.99 may help. See
    http://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup
    Warning: Examine the pairs() plot to diagnose sampling problems
    
    Warning: There were 1 divergent transitions after warmup. Increasing adapt_delta above 0.99 may help. See
    http://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup
    Warning: Examine the pairs() plot to diagnose sampling problems
    
    Warning: There were 5 divergent transitions after warmup. Increasing adapt_delta above 0.99 may help. See
    http://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup
    Warning: Examine the pairs() plot to diagnose sampling problems
    
    Warning: There were 1 divergent transitions after warmup. Increasing adapt_delta above 0.99 may help. See
    http://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup
    Warning: Examine the pairs() plot to diagnose sampling problems
    
    --- finished re-building 'LevyCaseStudy.Rmd'
    
    --- re-building 'TITE-CRM.Rmd' using rmarkdown
    Loading required package: Rcpp
    --- finished re-building 'TITE-CRM.Rmd'
    
    SUMMARY: processing the following files failed:
     'CRM-pathways.Rmd' 'CRM-visualisation.Rmd'
    
    Error: Vignette re-building failed.
    Execution halted
Flavor: r-devel-windows-ix86+x86_64

Version: 0.1.3
Check: running tests for arch ‘i386’
Result: ERROR
     Running 'testthat.R' [124s]
    Running the tests in 'tests/testthat.R' failed.
    Complete output:
     > library(testthat)
     > library(trialr)
     Loading required package: Rcpp
     >
     > test_check("trialr")
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 1).
     Chain 1:
     Chain 1: Gradient evaluation took 0 seconds
     Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
     Chain 1: Adjust your expectations accordingly!
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     Chain 1:
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     Chain 1: 0.031 seconds (Sampling)
     Chain 1: 0.062 seconds (Total)
     Chain 1:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 2).
     Chain 2:
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     Chain 2: 0.078 seconds (Total)
     Chain 2:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 3).
     Chain 3:
     Chain 3: Gradient evaluation took 0 seconds
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     Chain 3: 0.063 seconds (Total)
     Chain 3:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 4).
     Chain 4:
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     Chain 4:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 1).
     Chain 1:
     Chain 1: Gradient evaluation took 0 seconds
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     Chain 1: Adjust your expectations accordingly!
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     Chain 1:
     Chain 1: Elapsed Time: 0.032 seconds (Warm-up)
     Chain 1: 0.031 seconds (Sampling)
     Chain 1: 0.063 seconds (Total)
     Chain 1:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 2).
     Chain 2:
     Chain 2: Gradient evaluation took 0 seconds
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     Chain 2: Adjust your expectations accordingly!
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     Chain 2:
     Chain 2: Elapsed Time: 0.047 seconds (Warm-up)
     Chain 2: 0.031 seconds (Sampling)
     Chain 2: 0.078 seconds (Total)
     Chain 2:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 3).
     Chain 3:
     Chain 3: Gradient evaluation took 0 seconds
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     Chain 3: Adjust your expectations accordingly!
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     Chain 3:
     Chain 3: Elapsed Time: 0.047 seconds (Warm-up)
     Chain 3: 0.031 seconds (Sampling)
     Chain 3: 0.078 seconds (Total)
     Chain 3:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 4).
     Chain 4:
     Chain 4: Gradient evaluation took 0 seconds
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     Chain 4: Adjust your expectations accordingly!
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     Chain 4: 0.078 seconds (Total)
     Chain 4:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 1).
     Chain 1:
     Chain 1: Gradient evaluation took 0 seconds
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     Chain 1: Adjust your expectations accordingly!
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     Chain 1: Elapsed Time: 0.047 seconds (Warm-up)
     Chain 1: 0.031 seconds (Sampling)
     Chain 1: 0.078 seconds (Total)
     Chain 1:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 2).
     Chain 2:
     Chain 2: Gradient evaluation took 0 seconds
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     Chain 2: Adjust your expectations accordingly!
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     Chain 2:
     Chain 2: Elapsed Time: 0.032 seconds (Warm-up)
     Chain 2: 0.046 seconds (Sampling)
     Chain 2: 0.078 seconds (Total)
     Chain 2:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 3).
     Chain 3:
     Chain 3: Gradient evaluation took 0 seconds
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     Chain 3: Adjust your expectations accordingly!
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     Chain 3: Elapsed Time: 0.047 seconds (Warm-up)
     Chain 3: 0.031 seconds (Sampling)
     Chain 3: 0.078 seconds (Total)
     Chain 3:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 4).
     Chain 4:
     Chain 4: Gradient evaluation took 0 seconds
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     Chain 4: Adjust your expectations accordingly!
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     Chain 4:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 1).
     Chain 1:
     Chain 1: Gradient evaluation took 0 seconds
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     Chain 1: Adjust your expectations accordingly!
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     Chain 1:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 2).
     Chain 2:
     Chain 2: Gradient evaluation took 0 seconds
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     Chain 2: Adjust your expectations accordingly!
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     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 3).
     Chain 3:
     Chain 3: Gradient evaluation took 0 seconds
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     Chain 3:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 4).
     Chain 4:
     Chain 4: Gradient evaluation took 0 seconds
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     Chain 4: Adjust your expectations accordingly!
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     Chain 4:
    
     SAMPLING FOR MODEL 'CrmEmpiricNormalPrior' NOW (CHAIN 1).
     Chain 1:
     Chain 1: Gradient evaluation took 0 seconds
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     C