Contains small tweaks, bug fixes, and new feature additions. There shouldn’t be any breaking changes to the API.

Adds

`log`

argument to`lambda`

so users can choose which scale to return. The default is`TRUE`

for stochastic models and`FALSE`

for deterministic models.Allows named expressions in

`define_env_state()`

such that the names of the expressions may be used in`define_kernel()`

. Before, the name of the expression didn’t matter, only the names of the outputted list. Now, this will also work as well.

```
define_env_state(proto_ipm,
temp = rnorm(1, 20, 3),
precip = rgamma(1, 400, 2),
data_list = list())
```

More unit tests for parameter resampled models.

Removed innocuous warning messages. Added warnings for

`NA`

values in a few`define_*`

functions and errors when they’re produced in sub-kernels.Added the

`ipmr_ipm`

class so that most functions can tell the difference between a`PADRINO`

object and an`ipmr`

object.Changes argument

`tol`

to`tolerance`

in`is_conv_to_asymptotic()`

for consistency with other function/argument names.

corrects a bug where functions in the

`define_env_state`

`data_list`

argument weren’t recognized.corrects bug in

`left_ev()`

and`right_ev()`

where parameter set indices were ignored for deterministic models .

Contains a some tweaks and bug fixes, and a few new features:

Implements

`right_ev()`

and`left_ev()`

methods for stochastic models.Adds a new function,

`conv_plot()`

, to graphically check for convergence to asymptotic dynamics in deterministic models.Adds a new function,

`discretize_pop_vector()`

, to compute the empirical density function for a population trait distribution given a set of observed trait values.Adds print methods for density dependent models.

Adds

`log`

argument for`lambda`

.

Corrects bug where

`tol`

argument was ignored in`is_conv_to_asymptotic()`

.Gives output from

`lambda()`

names. Before, outputs from deterministic models with many parameter sets became hard to follow.

Contains a some tweaks and bug fixes. There is one major API change that renames parameters in `define_kernel`

.

Renames function arguments

`hier_effs`

->`par_sets`

,`levels_ages`

/`levels_hier_effs`

->`age_indices`

/`par_set_indices`

. The idea was to shift from thinking about these IPMs as resulting from multilevel/hierarchical regresssion models to IPMs constructed from parameter sets (which can be derived from any number of other methods).Corrects some bugs that caused

`vital_rate_funs()`

to break for`stoch_param`

and density dependent models.Updates the age X size model interface so that

`max_age`

kernels can be specified separately if they have different functional forms from their non-`max_age`

versions.`make_iter_kernel`

can handle computations passed into`mega_mat`

(e.g.`mega_mat = c(P + F, 0, I, C))`

.Makes

`plot.ipmr_matrix`

more flexible, which is now the recommended default`plot`

method for`ipm`

objects.Changes to internal code that won’t affect user experience.

This is the first version of `ipmr`

. It contains methods for constructing a variety of IPMs as well as methods for basic analysis. Complete documentation is in the vignettes and on the package website.