run_daisie_ml()
(#34).run_daisie_ml()
.Inf
from being passed to the relaxed rate model in run_daisie_ml()
(#33)run_daisie_ml()
)run_daisie_ml()
and setup_model()
:
par_upper_bound
, which sets the upper limit of the integration of a relaxed
parameter. This defaults to Inf
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).run_daisie_2type_ml()
and
adjacent function setup_2type_model()
. Similarly add required R
run_daisie_2type_ml.R
script and shell scripts submit_run_daisie_2type_ml.sh
and submit_run_daisie_2type_ml_long.sh
to run said analyses in an HPCC.res
to change resolution in DAISIE::DAISIE_ML_CS()
.
Default values allows for backwards compatibility in functions and job scripts
for Peregrine.nonoceanic
in relevant functions)..zenodo.json
for automatic release and archiving on Zenodo.tempdir()
.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 folder results/
in the root of the working directory.is_daisie_data()
as it was incomplete and seldom used. May be ported
from other packages in the future.create_output_folder()
to only handle directory creation.
The file path generation is now handled by create_results_dir_path()
assuming
previous functionality with new added flexibility via the results_dir
argument
as described above.run_daisie_ml()
and setup model to
allow certain datasets to be begin estimation from valid parameters.data
to daisie_data
for consistency with more recent
DAISIE related packages and to avoid conflicts with base R's data()
.plot_bootstrap_results()
, summarize_bootstrap_results()
adding to plot_sim_metrics()
which now is split into calc_sim_metrics()
.setup_std_pars2()
to generate common pars2
, useful for development
within 'DAISIE'.run_daisie_ml()
can now return it's output to session rather than saving
to file by setting results_dir
to NA
.run_daisie_ml()
uses lsodes
as default methode
, in line with 'DAISIE'.upload_results.R
and upload_results.sh
to upload to Google drive
directly from Peregrine..zenodo.json
with metadata for automatic Zenodo releases.choose_best_model()
correctly handles results where no model was estimated successfully, and returns NA
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 base DAISIE
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.
print_main_header()
.default_params_doc.R
to document package.README.md
stub.NEWS.md
file to track changes to the package.Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.