The latest release of the MSEtool package is available on CRAN.

- Bugs in (1) likelihood weights, and (2) indexing for initial biomass calcs have been fixed.
- Absolute indices, i.e., indices where q = 1, age-specific indices, and abundance/biomass-based indices can now be accommodated.
- The lognormal likelihood for composition data is now available as an alternative to the multinomial.
- When conditioned on catch, fishing mortality is estimated as deviations from the F in the middle of the time series (instead of all independent parameters) for more stability.
- Markdown reporting now includes likelihood weights. Slight changes in color schemes are included for consistency among plots.
`compare_SRA`

is a function that compares output and fits from multiple SRA objects with identical model structures in slot`SRA@mean_fit`

but different data weightings, omissions, multipliers, etc.

- Fixed error in Solaris build.

- Revised function arguments. Data inputs are in a single list in order to keep function calls tidy. The function should be backwards compatible for the most part.
- Mean weight-at-age is now used to calculate biomass and catch in order to match calculations in
`DLMtool::runMSE`

. Depletion calculations also match those in`DLMtool::runMSE`

. - Survey selectivity can now be estimated if age or length compositions for the survey are provided. See help file for setup.
- New plots have been added to the markdown report, include those that compare the outputs from the SRA and the updated operating model.
- A vignette for
`SRA_scope`

has now been added.

- Extensive revisions to
`SS2OM`

have been added. The function also generates a markdown report to compare operating model output to Stock Synthesis outputs, e.g., recruitment, catch, spawning biomass time series. - A log-Jacobian transform has been added for the r prior in
`SP`

and`SP_SS`

(surplus production models). This is needed because FMSY is estimated rate parameter rather than r. By default, the minimum CV on the r-prior is 0.1 to allow the model to update r. It is assumed n is fixed in the model. - Re-organize TMB files.

- Defaults for
`SRA_scope`

are now more robust (set maximum F in model, higher std. dev. for likelihood of mean lengths). - Users can choose to use
`SRA_scope`

conditioned on either observed catch or observed effort. `SRA_scope`

returns an S4 object of class`SRA`

with a`plot()`

method that generates a markdown report of model fits.

- A prior for r is now possible with
`SP`

and`SP_SS`

using life history information (priors in natural mortality and steepness, as well as maturity/weight at age). To use this feature, set argument`use_r_prior = TRUE`

. - Default process error standard deviation for
`SP_SS`

is reduced to 0.1. `cDD`

and`cDD_SS`

are more robust when catch is very, very small (F is set to 0). This is important for management procedures that shut down fishing.- Minor updates to simplify TMB code.
- Minor revision to
`make_MP`

.

- Vignette links are now available through the MSEtool help page. Type
`?MSEtool`

into the console. - Minor fixes to
`multiMSE`

. `SS2OM`

now has an option for selecting male or female life history parameters.

- Fixed error in Solaris build.

For the new features described below, DLMtool version 5.3.1 is recommended.

- The initial release for multi-fleet and multi-stock operating models and MSEs are released in this version, with
`multiMSE`

being the core function. The multiMSE vignette will be quite useful and can be accessed at`browseVignettes("MSEtool")`

.

Quite a few additions and changes have been made to the Assessment models. See the help manual and vignettes for descriptions of these new Assessment functions.

- The continuous delay-differential model with deterministic and stochastic recruitment (
`cDD`

and`cDD_SS`

, respectively) have been added as new Assessment models to the package. The continuous formulation should be more stable in high F situations. - A virtual population analysis
`VPA`

model has also been added to the package. - The surplus production model
`SP`

assumes continuous production and estimates continuous F’s, similar to ASPIC. This formulation will be more stable in high F situations. The Fox model can be implemented by setting the production function exponent`n = 1`

. - A wrapper function for
`spict`

(state-space surplus production model) has been written and is available in the`DLMextra`

package (located on Github). While reporting functions are available in MSEtool, the output of the wrapper function can still be used with the diagnostic functions in the spict package. `SCA`

and`SCA2`

estimate annual F’s and include a likelihood function for the catch. In previous versions,`SCA`

matched the predicted catch to observed catch. This feature has been transfered over to the`SCA_Pope`

function.- Summary of assessment results can be obtained by the
`plot`

function which now generates a markdown report. This will be useful for diagnosing model fits and evaluating parameter estimates.

- A scoping function
`SRA_scope`

fits an assessment model to catch, indices, and age/length comps to inform historical effort, recruitment deviations, and depletion for data-moderate operating models. Multiple fits are done based on the different life history parameters assumed in the operating model. This function is intended to be an alternative to`DLMtool::StochasticSRA`

. `profile`

and`retrospective`

functions for profiling the likelihood and retrospective analyses, respectively, of assessment models are now improved.- The
`compare_models`

function has been added to compare time series estimates, e.g. B/BMSY and F/FMSY, among different assessment models. - Manual starting values (the
`start`

argument) for parameters of assessment models can be expressions and subsequently evaluated in the assessment function. This can be very helpful when passing starting values in the`make_MP`

function. - The
`CASAL2OM`

function can be used to generate an operating model from CASAL assessments. - The
`SS2OM`

and`SS2Data`

functions are updated for the latest versions of r4ss on Github. - More options are provided to increase flexibility for ramped harvest control rules (
`HCR_ramp`

).

- Re-parameterization of dome selectivity in SCA so that estimated parameters are age-based after transformation.
- Additional argument in SCA for lognormal distribution for age comps.
- A more efficient method is used to report convergence diagnostics of assessment models when running in closed-loop simulation.

- By default, steepness is now fixed in the SCA and SCA2 assessment functions.
- By default, nine data-rich MPs are now included in the package. See the help documentation: ?
`Data-rich-MP`

- A generic function for ramped harvest control rules (
`HCR_ramp`

) is now included. Users can input the desired limit and target reference points. `make_MP`

adds dependencies to the MP so that`DLMtool::Required`

returns the appropriate dependencies. Dependencies are dynamic based on the configuration of the assessment model. For example,`Data@steep`

is a dependency for a SCA-based model only if steepness is fixed.

- Initial CRAN release.
- Assessment models: Delay-Difference (DD_TMB, DD_SS); Surplus Production (SP, SP_SS); Statistical Catch-at-Age (SCA, SCA2)
- Harvest control rules: HCR_MSY, HCR40_10, HCR60_20
`simmov`

function for multiple-area movement models (age-independent)- Functions for converting Stock Synthesis and iSCAM assessments to OM and Data objects (classes inherited from DLMtool)