- Prevent parameter values above upper bound being passed to the relaxed rate model in
run_daisie_ml()
(#34). - Lower the value given as initial parameter value when estimated as infinite for the relaxed rate model in
run_daisie_ml()
.
- Migrate from now defunct Peregrine HPCC to the new Hábrók HPCC
- Prevent
Inf
from being passed to the relaxed rate model inrun_daisie_ml()
(#33)
- The version of R and DAISIE are incremented to 4.2 and 4.4.0, respectively
- The relaxed-rate DAISIE model now has an initial DAISIE optimisation to get better initial conditions (in
run_daisie_ml()
) - Removed an old documentation section causing warning
- Allow relaxed-rate DAISIE ML models.
- This requires new a argument for
run_daisie_ml()
andsetup_model()
:par_upper_bound
, which sets the upper limit of the integration of a relaxed parameter. This defaults toInf
in the R function and shell scripts, which is no upper bound of integration for the relaxed-rate DAISIE model. This parameter is ignored when using the standard constant-rate case (i.e., not relaxed-rate).
- This requires new a argument for
- Allow 2 type DAISIE ML analyses, handled by
run_daisie_2type_ml()
and adjacent functionsetup_2type_model()
. Similarly add required Rrun_daisie_2type_ml.R
script and shell scriptssubmit_run_daisie_2type_ml.sh
andsubmit_run_daisie_2type_ml_long.sh
to run said analyses in an HPCC. - Package depends on CRAN DAISIE release instead of GitHub repository. Now requires DAISIE >= v4.3.1 to ensure latest ML related bugfixes are used.
- Add new tests covering new cases.
- Add Rampal Etienne's details to zenodo release.
- Add new argument
res
to change resolution inDAISIE::DAISIE_ML_CS()
. Default values allows for backwards compatibility in functions and job scripts for Peregrine.
- Can now extract a single data set (or replicate) from a data set that stores several within the same list.
- Add support for non-oceanic models (which can be chosen in the relevant
functions and start with
nonoceanic
in relevant functions).
- Correct
.zenodo.json
for automatic release and archiving on Zenodo.
- Reworked all reference test file infrastructure to use
tempdir()
. - Added
results_dir
argument to functions that load and/or write to the file system to allow the user to specify a custom directory appropriate for their environment. The default,NULL
maintains previous behaviour, i.e., saves and loads from a folderresults/
in the root of the working directory. - Removed
is_daisie_data()
as it was incomplete and seldom used. May be ported from other packages in the future. - Rework
create_output_folder()
to only handle directory creation. The file path generation is now handled bycreate_results_dir_path()
assuming previous functionality with new added flexibility via theresults_dir
argument as described above. - Add alternative (lower) CES rates to
run_daisie_ml()
and setup model to allow certain datasets to be begin estimation from valid parameters. - Renamed argument
data
todaisie_data
for consistency with more recent DAISIE related packages and to avoid conflicts with base R'sdata()
. - Add functions to plot bootstrap results to check model
goodness of fit:
plot_bootstrap_results()
,summarize_bootstrap_results()
adding toplot_sim_metrics()
which now is split intocalc_sim_metrics()
. - Add
setup_std_pars2()
to generate commonpars2
, useful for development within 'DAISIE'. run_daisie_ml()
can now return it's output to session rather than saving to file by settingresults_dir
toNA
.run_daisie_ml()
useslsodes
as defaultmethode
, in line with 'DAISIE'.- Style entire package with 'styler'.
- Require 'DAISIE' v4.2.1.
- No longer depend on private packages, to ensure package can be accessed by more users.
- Due to new plot functions, depend on 'ggplot2'and 'cowplot'.
- Added
upload_results.R
andupload_results.sh
to upload to Google drive directly from Peregrine. - Added
.zenodo.json
with metadata for automatic Zenodo releases.
-
choose_best_model()
correctly handles results where no model was estimated successfully, and returnsNA
appropriately. -
sensitivity()
now works correctly regardless of the number of parameters used to estimate the chosen models. This means relaxed-rate models and any model fitting that returns results with more than the baseDAISIE
parameters is accommodated. -
sensitivity()
no longer saves to file and instead returns results to the environment. -
Improved
sensitivity()
documentation. -
Depend on and install
DAISIE
v4.0.2.
-
Complete overhaul of package.
-
Add
run_daisie_ml()
to fit DAISIE models on DAISIE datasets. Returns model fitting results and BIC value. -
Add
bootstrap_lr()
to conduct a likelihood ratio bootstrap test on two DAISIE models. -
Add
bootstrap()
to conduct goodness of fit bootstrapping test. -
Add
sensitivity()
to calculate the sensitivity of the model to two alternative data sets.
- Create package skeleton.
- Add
print_main_header()
. - Use
default_params_doc.R
to document package. - Write
README.md
stub. - Add tests and coverage.
- Added a
NEWS.md
file to track changes to the package.