sdmTMB 0.6.0

• Pass several arguments to DHARMa::plotQQunif().

• Add silent option in simulate.sdmTMB(). Setting it to FALSE allows
  monitoring simulations from larger models.

• Fix bug in est_non_rf1 and est_non_rf2 columns when all the following
  conditions were true:

  • predicting on new data
  • using a delta model
  • including IID random intercepts or time-varying coefficients
    See #342. Thanks to @tom-peatman for the issue report.

• Fix delta-gamma binomial link printing for type = 'poisson-link' #340

• Add suggestion to use an optimized BLAS library to README.

• Add warning if it's detected that there were problems reloading (e.g., with
  readRDS()) a fitted model. Simultaneously revert the approach to
  how reloaded models are reattached.

• Move log_ratio_mix parameter to 2nd phase with starting value of -1 instead
  of 0 to improve convergence.

• Fix bugs for nbinom1() and nbinom2_mix() simulation.

• Allow profile argument in the control list to take a character vector of
  parameters. This move these parameters from the outer optimization problem to
  the inner problem (but omits from the from the Laplace approximation). See
  documentation in TMB. This can considerably speed up fitting models with many
  fixed effects.

• Add theoretical quantile residuals for the generalized gamma distribution.
  Thanks to J.C. Dunic. #333

• Add "poisson-link" option to delta-mixture lognormal.

• Fix bug in simulation from Poisson-link delta models.

• Simplify the internal treatment of extra time slices (extra_time). #329
  This is much less bug prone and also fixes a recently introduced bug. #335
  This can slightly affect model results compared to the previous approach if
  extra time was used along with smoothers since the 'fake' extra data
  previously used was included when mgcv determined knot locations for
  smoothers.

sdmTMB 0.5.0

• Overhaul residuals vignette ('article')
  https://pbs-assess.github.io/sdmTMB/articles/web_only/residual-checking.html
  including brief intros to randomized quantile residuals, simulation-based
  residuals, 'one-sample' residuals, and uniform vs. Gaussian residuals.

• Add check if prediction coordinates appear outside of fitted coordinates. #285

• Fix memory issue with Tweedie family on large datasets. #302

• Add experimental option to return standard normal residuals from
  dharma_residuals().

• Make simulate.sdmTMB() not include extra_time elements.

• Improved re-initialization of saved fitted model objects in new sessions.

• Fix important bug in simulate.sdmTMB() method for delta families where
  the positive linear predictor was only getting simulated for observations
  present in the fitted data.

• Add new "mle-mvn" type to residuals.sdmTMB() and make it the default.
  This is a fast option for evaluating goodness of fit that should be better
  than the previous default. See the details section in ?residuals.sdmTMB
  for details. The previous default is now called "mvn-eb" but is not
  recommended.

• Bring dharma_residuals() back over from sdmTMBextra to sdmTMB. Add a new
  option in the type argument ("mle-mvn") that should make the
  simulation residuals consistent with the expected distribution.
  See the same new documentation in ?residuals.sdmTMB. The examples
  in ?dharma_residuals illustrate suggested use.

• Fix bug in sanity() where gradient checks were missing abs() such that
  large negative gradients weren't getting caught. #324

• Return offset vector in fitted object as an element. Ensure any extra time
  rows of data in the data element of the fitted object do not include the
  extra time slices.

• Add experimental residuals option "mle-mvn" where a single approximate
  posterior sample of the random effects is drawn and these are combined
  with the MLE fixed effects to produce residuals. This may become the
  default option.

• Add the generalized gamma distribution (thanks to J.T. Thorson with additional
  work by J.C. Dunic.) See gengamma(). This distribution is still in a testing
  phase and is not recommended for applied use yet. #286

• Detect possible issue with factor(time) in formula if same column name is used
  for time and extra_time is specified. #320

• Improve sanity() check output when there are NA fixed effect standard
  errors.

• Set intern = FALSE within index bias correction, which seems to be
  considerably faster when testing with most models.

sdmTMB 0.4.3

• Fix a bug likely introduced in July 2023 that caused issues when
  extra_time was specified. This is an important bug and models fit with
  extra_time between that date (if using the GitHub version) and v0.4.2.9004
  (2024-02-24) should be checked against a current version of sdmTMB
  (v0.4.2.9005 or greater). On CRAN, this affected v0.4.0 (2023-10-20) to
  v0.4.2. Details:

  • The essence of the bug was that extra_time works by padding the data
    with a fake row of data for every extra time element (using the first row of
    data as the template). This is supposed to then be omitted from the
    likelihood so it has no impact on model fitting beyond spacing
    time-series processes appropriately and setting up internal structures for
    forecasting. Unfortunately, a bug was introduced that caused these fake data
    (1 per extra time element) to be included in the likelihood.

• Issue error if time column has NAs. #298 #299

• Fix bug in get_cog(..., format = "wide") where the time column was
  hardcoded to "year" by accident.

• Poisson-link delta models now use a type argument in delta_gamma() and
  delta_lognormal(). delta_poisson_link_gamma() and
  delta_poisson_link_lognormal() are deprecated. #290

• Delta families can now pass links that are different from the default
  "logit" and "log". #290

sdmTMB 0.4.2

• Force rebuild of CRAN binaries to fix issue with breaking Matrix ABI change
  causing NaN gradient errors. #288 #287

• Fix crash in if sdmTMB(..., do_index = TRUE) and extra_time supplied along
  with predict_args = list(newdata = ...) that lacked extra_time elements.

• Allow get_index() to work with missing time elements.

• Add the ability to pass a custom randomized quantile function qres_func
  to residuals.sdmTMB().

• Add check for factor random intercept columns in newdata to avoid a crash.
  #278 #280

• Improve warnings/errors around use of do_index = TRUE and get_index()
  if newdata = NULL. #276

• Fix prediction with offset when newdata is NULL but offset is
  specified. #274

• Fix prediction failure when both offset and nsim are provided and
  model includes extra_time. #273

sdmTMB 0.4.1

• Fix memory issues detected by CRAN 'Additional issues' clang-UBSAN, valgrind.

• Fix a bug predicting on new data with a specified offset and extra_time.
  #270

• Add warning around non-factor handling of the spatial_varying formula. #269

• Add experimental set_delta_model() for plotting delta models with
  ggeffects::ggpredict() (GitHub version only until next CRAN version).

sdmTMB 0.4.0

• Move add_barrier_mesh() to sdmTMBextra to avoid final INLA dependency.
  https://github.com/pbs-assess/sdmTMBextra

• Switch to using the new fmesher package for all mesh/SPDE calculations. INLA
  is no longer a dependency.

• Switch to diagonal.penalty = FALSE in mgcv::smoothCon().
  This changes the scale of the linear component of the smoother, but
  should result in the same model.
  glmmTMB/glmmTMB#928 (comment)

• Implement cross validation for delta models #239

• Remove ELPD from cross validation output. Use sum_loglik instead. #235

• Turn on Newton optimization by default. #182

• print() now checks sanity() and issues a warning if there may be issues. #176

• Poisson-link delta models and censored likelihood distributions have been made
  considerably more robust. #186

• Standard errors are now available on SD parameters etc. in tidy() #240

• Fix bug in print()/tidy() for delta-model positive model component sigma_E.
  A recently introduce bug was causing sigma_E for the 2nd model to be reported
  as the 1st model component sigma_E.

• Add new anisotropy plotting function.

• Add anisotropic range printing. #149 by @jdunic

sdmTMB 0.3.0

• Create the sdmTMBextra package to remove rstan/tmbstan helpers, which
  were causing memory sanitizer errors on CRAN.
  https://github.com/pbs-assess/sdmTMBextra

• The following functions are affected:

  • predict.sdmTMB() now takes mcmc_samples, which is output from
    sdmTMBextra::extract_mcmc().
  • simulate.sdmTMB() now takes mcmc_samples, which is output from
    sdmTMBextra::extract_mcmc().
  • residuals.sdmTMB() now takes mcmc_samples, which is output
    sdmTMBextra::predict_mle_mcmc(). This only affects
    residuals(..., type = "mle-mcmc").

• Move dharma_residuals() to
  sdmTMBextra to reduce heavy
  dependencies.

• See examples in the Bayesian and residuals vignettes or in the help files for
  those functions within sdmTMBextra.

• Various fixes to pass CRAN checks. #158

• Fix memory issue highlighted by Additional issues CRAN checks. #158

• 'offset' argument can now be a character value indicating a column name. This
  is the preferred way of using an offset with parallel cross validation. #165

• Fix parallel cross validation when using an offset vector. #165

• Add leave-future-out cross validation functionality. #156

• Example data qcs_grid is no longer replicated by year to save package
  space. #158

• Add message with tidy(fit, "ran_pars") about why SEs are NA.

• Add anisotropy to print() #157

• Fix predict(..., type = "response", se_fit = TRUE), which involves issuing
  a warning and sticking to link space. #140