Modifying the environment of a PADRINO IPM | Finding parameter-resampled IPMs | re-set environmental variables w/ pre-defined sequence of values | Create the proto_ipm's and find the stochastic parameter names | Create new stochastic parameter values | Write our sampling function | Remove the current environmental variation | Insert our environmental variation | Rebuild the models | Modifying parameter values | Identify parameter names | Changing distributions | Top-level function | Substituting functions

Package Overview | Usage | More complicated analyses | The dataset | Age-specific survival and fecundity | Mean and variance in lifespan | Correcting issues with data | Quick solution | Further reading

Introduction to age $\times$ size classified models | Mathematical overview | Model parameterization | Further analyses

Simple IPMs vs General IPMs | A general, density independent, deterministic IPM | Key differences between simple and general IPMs. | Mathematical overview of the example | Model code | Further analysis | General models for discretely varying environments | Model parameterization | General models with continuously varying environments | Mathematical overview | Model specification | A note on memory management | Code to construct mega-kernels

Overview | Terminology and IPM construction | Types of models in ipmr | Specifying a simple deterministic IPM without density dependence | Defining kernels | Defining the implementation arguments (impl_args) | Defining domains for state variables | Defining the initial population state | Implement the IPM | Using predict() methods in vital rate expressions | Defining more complicated models | Deterministic simulations from parameter sets | Defining a stochastic IPM in a discretely varying environment | Defining custom functions to pass to the building process | Simple IPMs for continuously varying environments | Defining initial conditions | define_env_state() | Vital rate models | The continuously varying IPM | A note on memory management | Pre-determined sequences of environmental covariates | Modeling the environment directly | Uncertainty in simple IPMs | General IPMs

Messages and warnings during proto_ipm construction from ipmr-level functions | Messages and warnings during proto_ipm construction from Rpadrino-level functions | Messages and warnings during IPM construction from ipmr-level functions | Messages and warnings during IPM construction from Rpadrino-level functions

Overview | Quick start guide | Notation guide | Models with a single indexed variable | IPMs from discrete parameter sets and continuously varying environments | Simulating parameters | Implementing the model

Introduction | Fundamental operators | Overview of the problem | Diagnosis | Fixing the problem

Density dependent models | Example of a simple, stochastic, kernel-resampled model with density dependence

Scope and motivation | The actual details | Additional information | flat_protect attribute