Introduction to age $\times$ size classified models | Mathematical overview | Model parameterization | Further analyses
Package: ipmr 0.0.7
Sam Levin
ipmr: Integral Projection Models
Flexibly implements Integral Projection Models using a mathematical(ish) syntax. This package will not help with the vital rate modeling process, but will help convert those regression models into an IPM. 'ipmr' handles density dependence and environmental stochasticity, with a couple of options for implementing the latter. In addition, provides functions to avoid unintentional eviction of individuals from models. Additionally, provides model diagnostic tools, plotting functionality, stochastic/deterministic simulations, and analysis tools. Integral projection models are described in depth by Easterling et al. (2000) <doi:10.1890/0012-9658(2000)081[0694:SSSAAN]2.0.CO;2>, Merow et al. (2013) <doi:10.1111/2041-210X.12146>, Rees et al. (2014) <doi:10.1111/1365-2656.12178>, and Metcalf et al. (2015) <doi:10.1111/2041-210X.12405>. Williams et al. (2012) <doi:10.1890/11-2147.1> discuss the problem of unintentional eviction.
Authors:
ipmr_0.0.7.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
ipmr/json (API)
| # Install 'ipmr' in R: |
| install.packages('ipmr', repos = c('https://padrinodb.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/padrinodb/ipmr/issues
Pkgdown/docs site:https://padrinodb.github.io
Datasets:
- gen_di_det_ex - A general deterministic IPM example
- iceplant_ex - Raw demographic data to construct an example IPM
- monocarp_proto - A 'proto_ipm' for a monocarpic perennial
- sim_di_det_ex - Simple deterministic IPM example
demographyintegral-projection-modelscpp
Last updated from:7e1faad413. Checks:11 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | NOTE | 218 | ||
| linux-devel-x86_64 | NOTE | 243 | ||
| source / vignettes | OK | 235 | ||
| linux-release-arm64 | NOTE | 224 | ||
| linux-release-x86_64 | NOTE | 205 | ||
| macos-release-arm64 | NOTE | 178 | ||
| macos-release-x86_64 | NOTE | 311 | ||
| macos-oldrel-arm64 | NOTE | 239 | ||
| macos-oldrel-x86_64 | NOTE | 372 | ||
| windows-devel | NOTE | 194 | ||
| windows-release | NOTE | 191 | ||
| windows-oldrel | NOTE | 224 | ||
| wasm-release | OK | 152 |
Exports:.data%^%%>%collapse_pop_stateconv_plotdefine_domainsdefine_env_statedefine_impldefine_kerneldefine_pop_statediscrete_extremadiscretize_pop_vectordomainsenexprenexprsenquoenquosensymensymsexprformat_mega_kernelinit_ipmint_meshipm_to_dfis_conv_to_asymptotickernel_formulaekernel_formulae<-lambdaleft_evleft_multmake_impl_args_listmake_ipmmake_ipm_reportmake_ipm_report_bodymake_iter_kernelmat_powermean_kernelnew_fun_formparametersparameters<-pop_statequoquo_namequosright_evright_multsymsymstruncated_distributionsuse_vr_modelvital_rate_exprsvital_rate_exprs<-vital_rate_funs
Age-Size IPMs
Last update: 2022-11-29
Started: 2020-06-26
General IPMs
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
Last update: 2022-11-29
Started: 2020-01-13
Introduction to ipmr
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
Last update: 2022-11-29
Started: 2019-02-05
Index Notation in ipmr
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
Last update: 2022-02-09
Started: 2021-05-18
Density Dependent IPMs
Density dependent models | Example of a simple, stochastic, kernel-resampled model with density dependence
Last update: 2021-05-18
Started: 2020-10-16
proto_ipm Data Structure
Scope and motivation | The actual details | Additional information | flat_protect attribute
Last update: 2021-05-18
Started: 2019-07-12
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Raise a matrix to a power | %^% mat_power |
| Convert to bare matrices | as.matrix.ipmr_ipm as.matrix.ipmr_matrix |
| Extract threshold based population size information | collapse_pop_state |
| Helpers for IPM construction | define_domains define_env_state define_impl define_pop_state discretize_pop_vector make_impl_args_list |
| Functions to initialize and define IPM kernels | define_kernel |
| Accessor functions for (proto_)ipm objects | domains domains.default domains.proto_ipm int_mesh int_mesh.ipmr_ipm kernel_formulae kernel_formulae.default kernel_formulae.proto_ipm kernel_formulae<- kernel_formulae<-.proto_ipm new_fun_form parameters parameters.default parameters.proto_ipm parameters<- parameters<-.proto_ipm pop_state pop_state.default pop_state.proto_ipm vital_rate_exprs vital_rate_exprs.default vital_rate_exprs.proto_ipm vital_rate_exprs<- vital_rate_exprs<-.proto_ipm vital_rate_funs vital_rate_funs.ipmr_ipm |
| Create iteration kernels from an IPM object | format_mega_kernel format_mega_kernel.age_x_size_ipm format_mega_kernel.default make_iter_kernel |
| A general deterministic IPM example | gen_di_det_ex |
| Raw demographic data to construct an example IPM | iceplant_ex |
| Initialize an IPM | init_ipm |
| Convert ipmr matrix to long data frame | ipm_to_df ipm_to_df.array ipm_to_df.default |
| Check for model convergence to asymptotic dynamics | conv_plot conv_plot.ipmr_ipm is_conv_to_asymptotic is_conv_to_asymptotic.ipmr_ipm |
| Compute the per-capita growth rate for an IPM object | lambda lambda.general_dd_det_ipm lambda.general_dd_stoch_kern_ipm lambda.general_dd_stoch_param_ipm lambda.general_di_det_ipm lambda.general_di_stoch_kern_ipm lambda.general_di_stoch_param_ipm lambda.simple_dd_det_ipm lambda.simple_dd_stoch_kern_ipm lambda.simple_dd_stoch_param_ipm lambda.simple_di_det_ipm lambda.simple_di_stoch_kern_ipm lambda.simple_di_stoch_param_ipm |
| Methods to implement an IPM | make_ipm make_ipm.general_dd_det make_ipm.general_dd_stoch_kern make_ipm.general_dd_stoch_param make_ipm.general_di_det make_ipm.general_di_stoch_kern make_ipm.general_di_stoch_param make_ipm.simple_dd_det make_ipm.simple_dd_stoch_kern make_ipm.simple_dd_stoch_param make_ipm.simple_di_det make_ipm.simple_di_stoch_kern make_ipm.simple_di_stoch_param |
| Generate an RMarkdown file with IPM metadata | make_ipm_report make_ipm_report.default make_ipm_report.ipmr_ipm make_ipm_report_body |
| Mean kernels for stochastic models | mean_kernel |
| A 'proto_ipm' for a monocarpic perennial | monocarp_proto |
| Plot a matrix or an *_ipm object | plot.general_di_det_ipm plot.ipmr_matrix plot.simple_di_det_ipm plot.simple_di_stoch_kern_ipm plot.simple_di_stoch_param_ipm |
| Print proto_ipms or *_ipm objects | print.general_dd_det_ipm print.general_dd_stoch_kern_ipm print.general_dd_stoch_param_ipm print.general_di_det_ipm print.general_di_stoch_kern_ipm print.general_di_stoch_param_ipm print.proto_ipm print.simple_dd_det_ipm print.simple_dd_stoch_kern_ipm print.simple_dd_stoch_param_ipm print.simple_di_det_ipm print.simple_di_stoch_kern_ipm print.simple_di_stoch_param_ipm |
| Compute the standardized left and right eigenvectors via iteration | left_ev left_ev.general_di_det_ipm left_ev.general_di_stoch_kern_ipm left_ev.general_di_stoch_param_ipm left_ev.simple_di_det_ipm left_ev.simple_di_stoch_kern_ipm left_ev.simple_di_stoch_param_ipm right_ev right_ev.general_di_det_ipm right_ev.general_di_stoch_kern_ipm right_ev.general_di_stoch_param_ipm right_ev.simple_di_det_ipm right_ev.simple_di_stoch_kern_ipm right_ev.simple_di_stoch_param_ipm |
| Right/left multiplication | left_mult right_mult |
| Simple deterministic IPM example | sim_di_det_ex |
| Eviction correction | discrete_extrema truncated_distributions |
| Predict methods in ipmr | use_vr_model |
