Add brms examples for non-linear model

[gowerc]

Closes #417

Also moved a bunch of older stuff that I don't think is relevant anymore to a "legacy" folder to clean up the design area a bit

[github-actions]

Unit Tests Summary

    1 files    179 suites   6m 10s ⏱️
  157 tests   145 ✅ 12 💤 0 ❌
1 098 runs  1 085 ✅ 13 💤 0 ❌

Results for commit 546eb55.

♻️ This comment has been updated with latest results.

[github-actions]

Unit Test Performance Difference

Test Suite	$Status$	Time on main	$±Time$	$±Tests$	$±Skipped$	$±Failures$	$±Errors$
JointModelSamples	💔	$8.26$	$+24.34$	$0$	$-1$	$0$	$0$
compile	💚	$10.41$	$-8.76$	$0$	$0$	$0$	$0$
extract_quantities	💚	$12.26$	$-7.90$	$0$	$0$	$0$	$0$
misc_models	💚	$11.63$	$-7.77$	$0$	$0$	$0$	$0$
model_multi_chain	💚	$52.22$	$-49.61$	$0$	$0$	$0$	$0$

Additional test case details

Test Suite	$Status$	Time on main	$±Time$	Test Case
Grid	💚	$85.60$	$-83.44$	Grid_objects_work_with_QuantityGenerator_and_QuantityCollapser
GridPrediction	💔	$114.87$	$+13.10$	GridPrediction_works_as_expected_for_Survival_models
JointModelSamples	💔	$8.26$	$+24.34$	print_works_as_expected_for_JointModelSamples
LongitudinalClaretBruno	💚	$1770.08$	$-1763.65$	LongitudinalClaretBruno_works_as_expected_with_default_arguments
LongitudinalGSF	💚	$683.93$	$-676.63$	LongitudinalGSF_works_as_expected_with_default_arguments
LongitudinalQuantiles	💔	$39.08$	$+11.78$	Test_that_LongitudinalQuantities_works_as_expected
LongitudinalRandomSlope	💚	$67.58$	$-41.46$	Print_method_for_LongitudinalRandomSlope_works_as_expected
LongitudinalSteinFojo	💚	$1446.63$	$-1438.86$	LongitudinalSteinFojo_works_as_expected_with_default_arguments
SimSurvival	💔	$3.18$	$+1.11$	SimSurvivalExponential_creates_a_dataset_with_the_correct_parameter
SurvivalExponential	💚	$23.64$	$-21.98$	Can_load_and_compile_SurvivalExponential_model
SurvivalGamma	💚	$193.96$	$-192.45$	Print_method_for_SurvivalGamma_works_as_expected
SurvivalLoglogistic	💚	$40.06$	$-38.57$	Can_load_and_compile_SurvivalLogLogistic_model
SurvivalQuantities	💚	$78.73$	$-48.28$	SurvivalQuantities_and_autoplot.SurvivalQuantities_works_as_expected
SurvivalWeibullPH	💚	$14.69$	$-13.28$	Print_method_for_SurvivalWeibullPH_works_as_expected
brierScore	💚	$17.18$	$-11.29$	brierScore_SurvivalQuantities_returns_same_results_as_survreg
brms_compare	💚	$327.21$	$-327.13$	jmpost_and_brms_get_similar_loo_for_longitudinal_models
compile	💚	$10.41$	$-8.76$	compileStanModel_doesn_t_error_if_the_directory_doesn_t_exist
extract_quantities	💚	$12.26$	$-7.90$	extract_quantities_works_as_expected
misc_models	💚	$11.63$	$-7.77$	Longitudinal_Model_doesn_t_print_sampler_rejection_messages
model_multi_chain	💚	$52.22$	$-49.61$	Can_recover_known_distribution_parameters_from_random_slope_model_when_using_multiple_chains
stan_functions	💚	$38.12$	$-7.68$	GSF_SLD_function_works_as_expected

Results for commit ca96482

♻️ This comment has been updated with latest results.

[gravesti]

@gowerc For the brms examples I noticed the estimates are not near the diagonals like the jmpost ones are. Is that expected?

jmpost model

brms model

[gowerc]

@gravesti - That is not expected ...

Will double check and update accordingly

[gowerc]

@gravesti - I think the code is fine (ish) I think its just super sensitive to starting values. Most of the time I run the brms code I get the correct output as expected:

But every now and again I do get plots similar to what you showed, in these instances the sampler completes in about 10% of the usual time and the diagnostics are completely off. Running with longer warmups seems to correct this.

[gravesti]

Thanks @gowerc Maybe worth a note in the script for posterity to say that the models are sensitive to initial values are require a good warmup phase?

[gowerc]

@gravesti - Added a stronger warning message to highlight this.

[github-actions]

Code Coverage Summary

Filename                           Stmts    Miss  Cover    Missing
-------------------------------  -------  ------  -------  --------------------------------
R/brier_score.R                      167       0  100.00%
R/DataJoint.R                         76       2  97.37%   264, 270
R/DataLongitudinal.R                 119       1  99.16%   244
R/DataSubject.R                       85       1  98.82%   142
R/DataSurvival.R                      98       0  100.00%
R/defaults.R                          10       6  40.00%   18-57, 84
R/generics.R                          33       4  87.88%   52, 382, 402, 457
R/Grid.R                              27       1  96.30%   173
R/GridEven.R                          32       0  100.00%
R/GridEvent.R                         22       0  100.00%
R/GridFixed.R                         30       0  100.00%
R/GridGrouped.R                       52       0  100.00%
R/GridManual.R                        23       3  86.96%   78-80
R/GridObserved.R                      20       0  100.00%
R/GridPopulation.R                    31       4  87.10%   61, 69-71
R/GridPrediction.R                    36       6  83.33%   83, 91-95
R/JointModel.R                       129      10  92.25%   148-153, 203, 207, 249, 295, 301
R/JointModelSamples.R                 66       0  100.00%
R/link_generics.R                     16       4  75.00%   59, 76, 91, 106
R/Link.R                              62       4  93.55%   200-203
R/LinkComponent.R                     19       3  84.21%   88, 120-121
R/LongitudinalClaretBruno.R           90       6  93.33%   168-172, 187
R/LongitudinalGSF.R                   95       0  100.00%
R/LongitudinalModel.R                 19       0  100.00%
R/LongitudinalQuantities.R            71       0  100.00%
R/LongitudinalRandomSlope.R           44       5  88.64%   102-106
R/LongitudinalSteinFojo.R             86       5  94.19%   159-163
R/Parameter.R                         14       0  100.00%
R/ParameterList.R                     42       1  97.62%   184
R/Prior.R                            254       6  97.64%   510, 654-668
R/Promise.R                           25       0  100.00%
R/Quantities.R                        60       0  100.00%
R/QuantityGeneratorPopulation.R       22       0  100.00%
R/QuantityGeneratorPrediction.R       48       0  100.00%
R/QuantityGeneratorSubject.R          19       0  100.00%
R/settings.R                          12      12  0.00%    55-69
R/SimGroup.R                           5       0  100.00%
R/SimJointData.R                      72       1  98.61%   103
R/SimLongitudinal.R                    5       2  60.00%   22, 40
R/SimLongitudinalClaretBruno.R        74       0  100.00%
R/SimLongitudinalGSF.R                80       0  100.00%
R/SimLongitudinalRandomSlope.R        42       0  100.00%
R/SimLongitudinalSteinFojo.R          69       0  100.00%
R/SimSurvival.R                      116       0  100.00%
R/StanModel.R                         15       0  100.00%
R/StanModule.R                       176       6  96.59%   192-193, 235, 246, 383, 411
R/SurvivalExponential.R               10       0  100.00%
R/SurvivalGamma.R                     13       0  100.00%
R/SurvivalLoglogistic.R               11       0  100.00%
R/SurvivalModel.R                     19       0  100.00%
R/SurvivalQuantities.R               170       1  99.41%   125
R/SurvivalWeibullPH.R                 13       0  100.00%
R/utilities.R                        144       2  98.61%   13, 335
R/zzz.R                               29      26  10.34%   4-8, 10-31, 38-47
TOTAL                               3117     122  96.09%

Diff against main

Filename      Stmts    Miss  Cover
----------  -------  ------  --------
TOTAL             0       0  +100.00%

Results for commit: 546eb55

Minimum allowed coverage is 80%

♻️ This comment has been updated with latest results