# Pumas version 0.14.0 (Pumas Beta v1.0) released

**URL:** <https://discourse.pumas.ai/t/pumas-version-0-14-0-pumas-beta-v1-0-released/370>\
**Category:** Announcements\
**Created:** [July 14, 2020, 2:58am UTC](https://discourse.pumas.ai/t/pumas-version-0-14-0-pumas-beta-v1-0-released/370 "2020-07-14T02:58:34Z")\
**Posts on this page:** 1\
**Page:** 1

<div class="post-metadata">

**Author:** ![vijay](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pumas.ai/vijay/32/96_2.png) [@vijay](https://discourse.pumas.ai/u/vijay)\
**Post date:** [July 14, 2020, 2:58am UTC](https://discourse.pumas.ai/t/pumas-version-0-14-0-pumas-beta-v1-0-released/370/1 "2020-07-14T02:58:34Z")

</div>

A new release of Pumas is now available in the JuliaProRegistry. You can upgrade your current installation of Pumas by simply running `] up Pumas` at the command prompt in JuliaPro.  
The new release is a beta release, and this means that we have a so-called feature freeze. This means that all breaking changes and all feature additions have been made for what will become Pumas v1.0. This also means that we have included some final breaking changes, so please consult the release notes below if code that used to work no longer works.

### Release Notes for Pumas v0.14.0

#### Features and improvements

- Add VPC for continuous outcomes
- Add Time-to-event distribution type to allow single and repeated time to event analysis
- Add support for continuous-time Markov models using the functional interface
- Change ordering of internal operations in variance-covarinace matrix, `vcov(::FittedPumasModel)`, calculations.
- Check that all elements of the `@param` block are present in the input parameter `NamedTuple` in `fit`, `simobs` and `solve` for `Population`s
- Use automatic differentiation for `NaivePooled` and `FO`
- Introduce a check for gradient elements that are exactly zero as these indicate bad starting values or problems with identifiability
- Add a method to `cond` so it can be called on a `FittedPumasModel` to get the condition number of the variance-covariance matrix
- Support `evid=3` and `evid=4` in `read_pumas`
- Add explicit check that all required variables are present in `@pre` when using analytical solutions
- Add likelihood ratio test (`lrtest` and `pvalue`)
- Allow mixed number of doses in a population in NCA analysis
- Add parallelization in `simobs` when simulating for several parameter inputs at once
- Add convenience methods to `predict` to predict from a `FittedPumasModel` onto a new dataset
- Add `probstable` that returns the probabilities of discrete observed outcomes. Can be converted to a DataFrame.
- Add `paralellization` to simulated diagnostic functions
- Improve DosageRegimen docstring
- Improve error messages in NCA
- Introduce `icoef` to extract subject-specific variables. Can be converted to a DataFrame.
- Make bootstrap output a FittedPumasModelInference struct
- Add `liftunits2header` as post-processing of `NCAReport`

#### Deprecations

- Unexport `ConstDomain` usage in `@param`. Use `constantcoef` in `fit` instead.
- Use `η=0` for population predictions and `η=η*` for individual predictions
- Rename keywords `obs` and `dvs` to `observations`, `cvs` to `covariates`, `evs` to `events`, and `times` to `time`

#### Bugfixes

- Fix behavior in mixed (analytical and numerical) models due to changes in RecursiveArrayTools
- Fix order of rows in `NCAReport` to be sorted by (`id`, `group`)
- Superposition fixes
- Keep `id` when creating a `Subject` from a `SimulatedObservations`
- Require that input covariates are `NamedTuple`s in the `Subject` to avoid a common mistake of omitting a comma (an assignment`(a=1)` vs a `NamedTuple` `(a=1,)`)
- Correctly pass the option to show progress information to internal functions when doing Bayesian inference.
- Fix bug in handling of multiple dosage regimens in models with analytical solutions
- Fix bug in `ϵshrinkage` when subjects don’t have the same number of observations
- Fix bug in `bic` when there are multiple dependent variables and dependent variables with missing values
- Fix various bugs in the DataFrame constructor for `Subject`. This includes cases with time-varying covariates, no observations, and no events.
- Allow for placebo subjects (no events) in analytical models
- Fix issues of proper extraction of dependent variables when constructing a `Subject` from a `SimulatedSubject`
- Fix alignment of output in printing `Vector{<:FittedPumasModels}`
- Fix bug in `Central1Peripheral1Metab1`

#### Compatability

- RecursiveArrayTools versions 2.x are now supported
- DataInterpolations version 3.0 is now supported
- Optim versions 0.21, 0.22 now supported
- DataFrames 0.21. is now supported
- CSV version 0.7 now supported
- MCMCChains v4.0 now supported
- We now require Roots (v1.0)
- Remove GLM dependency