Changes in version 0.1.1                        

Bug fixes

  - From version 2.10.0, loo::loo_compare() gives the compared models in
    a column rather than as row names. A test and the vignette
    "Comparing and averaging models" read the row names; both now read
    the models from either place. The functions of the package are
    unchanged.

Other changes

  - The package has a DOI, given by citation("rTFT") and the README.
  - The package is checked on Linux, macOS and Windows with each push.
  - The package can be installed from R-universe.
  - The website has a page title and description for search engines.

                        Changes in version 0.1.0                        

First release.

Fitting

  - build_hazard_data() builds the table of intervals at risk from
    failure times that are known-time, interval-censored or a mixture of
    both, under any temperature trajectory. ramp_path() builds the
    trajectory of a linear ramp, and assess_ramp_linearity() compares a
    logged ramp with a straight line.
  - fit_hazard() fits the model using Bayesian inference in Stan through
    brms, with a choice of functions for the failure rate (M_catalogue)
    and for the baseline (h0_catalogue). The failure rate may depend on
    covariates and on group-level effects.
  - costressor() declares a co-stressor (e.g., dissolved oxygen), with
    its main effect and, when asked for, its interaction with
    temperature. A model may have more than one co-stressor.
  - build_hazard_prior() shows and sets the priors.

Checking a fitted model

  - check_survival() and plot_check() compare the proportion of
    individuals observed to survive with the proportions simulated from
    the model.
  - hazard_residuals() and plot_residuals() give one randomised residual
    per individual.

Derived quantities

  - derive_tdt_ttl() derives the static critical thermal maximum, the
    thermal death time curves and the thermal tolerance landscape, and
    derive_dctmax() the dynamic critical thermal maximum under a ramp,
    each with its posterior uncertainty.
  - plot_tdt(), plot_ttl() and plot_ttl_3d() draw them.
  - M_draws() returns the posterior draws of the failure rate across
    temperatures.

Comparing and averaging models

  - loo_hazard() and kfold_hazard() compare models by cross-validation
    that leaves out whole individuals or trials.
  - hazard_weights() gives the weights of the models, and
    average_tdt_ttl(), average_dctmax() and average_survival() average
    the derived quantities and the predictions.

Predicting survival

  - predict_survival() predicts survival along a record of temperature
    (and of any co-stressors recorded with it), and reports how much of
    the record and of the predicted risk lies outside the temperatures
    and exposure times of the assay. plot_survival() and plot_risk()
    draw the prediction.

Data

  - static_assay, ramp_assay and stream_record are simulated datasets
    used in the help pages and the vignettes.