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:Sam Levin [aut, cre], Aldo Compagnoni [aut], Dylan Childs [aut], Sanne Evers [aut], Roberto Salguero-Gomez [aut], Tiffany Knight [aut], Eric Scott [ctb]

ipmr_0.0.7.tar.gz
ipmr_0.0.7.zip(r-4.5)ipmr_0.0.7.zip(r-4.4)ipmr_0.0.7.zip(r-4.3)
ipmr_0.0.7.tgz(r-4.4-x86_64)ipmr_0.0.7.tgz(r-4.4-arm64)ipmr_0.0.7.tgz(r-4.3-x86_64)ipmr_0.0.7.tgz(r-4.3-arm64)
ipmr_0.0.7.tar.gz(r-4.5-noble)ipmr_0.0.7.tar.gz(r-4.4-noble)
ipmr_0.0.7.tgz(r-4.4-emscripten)ipmr_0.0.7.tgz(r-4.3-emscripten)
ipmr.pdf |ipmr.html
ipmr/json (API)
NEWS

# Install 'ipmr' in R:
install.packages('ipmr', repos = c('https://padrinodb.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/padrinodb/ipmr/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

demographyintegral-projection-models

6.92 score 7 stars 1 packages 66 scripts 298 downloads 53 exports 8 dependencies

Last updated 22 days agofrom:71915cd3cd. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 01 2024
R-4.5-win-x86_64NOTENov 01 2024
R-4.5-linux-x86_64NOTENov 01 2024
R-4.4-win-x86_64NOTENov 01 2024
R-4.4-mac-x86_64NOTENov 01 2024
R-4.4-mac-aarch64NOTENov 01 2024
R-4.3-win-x86_64NOTENov 01 2024
R-4.3-mac-x86_64NOTENov 01 2024
R-4.3-mac-aarch64NOTENov 01 2024

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

Dependencies:cligluelifecyclemagrittrpurrrRcpprlangvctrs

Age-Size IPMs

Rendered fromage_x_size.Rmdusingknitr::rmarkdownon Nov 01 2024.

Last update: 2022-11-29
Started: 2020-06-26

Density Dependent IPMs

Rendered fromdensity-dependence.Rmdusingknitr::rmarkdownon Nov 01 2024.

Last update: 2021-05-18
Started: 2020-10-16

General IPMs

Rendered fromgeneral-ipms.Rmdusingknitr::rmarkdownon Nov 01 2024.

Last update: 2022-11-29
Started: 2020-01-13

Index Notation in ipmr

Rendered fromindex-notation.Rmdusingknitr::rmarkdownon Nov 01 2024.

Last update: 2022-02-09
Started: 2021-05-18

Introduction to ipmr

Rendered fromipmr-introduction.Rmdusingknitr::rmarkdownon Nov 01 2024.

Last update: 2022-11-29
Started: 2019-02-05

proto_ipm Data Structure

Rendered fromproto-ipms.Rmdusingknitr::rmarkdownon Nov 01 2024.

Last update: 2021-05-18
Started: 2019-07-12

Readme and manuals

Help Manual

Help pageTopics
Raise a matrix to a power%^% mat_power
Convert to bare matricesas.matrix.ipmr_ipm as.matrix.ipmr_matrix
Extract threshold based population size informationcollapse_pop_state
Helpers for IPM constructiondefine_domains define_env_state define_impl define_pop_state discretize_pop_vector make_impl_args_list
Functions to initialize and define IPM kernelsdefine_kernel
Accessor functions for (proto_)ipm objectsdomains 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 objectformat_mega_kernel format_mega_kernel.age_x_size_ipm format_mega_kernel.default make_iter_kernel
A general deterministic IPM examplegen_di_det_ex
Raw demographic data to construct an example IPMiceplant_ex
Initialize an IPMinit_ipm
Convert ipmr matrix to long data frameipm_to_df ipm_to_df.array ipm_to_df.default
Check for model convergence to asymptotic dynamicsconv_plot conv_plot.ipmr_ipm is_conv_to_asymptotic is_conv_to_asymptotic.ipmr_ipm
Compute the per-capita growth rate for an IPM objectlambda 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 IPMmake_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 metadatamake_ipm_report make_ipm_report.default make_ipm_report.ipmr_ipm make_ipm_report_body
Mean kernels for stochastic modelsmean_kernel
A 'proto_ipm' for a monocarpic perennialmonocarp_proto
Plot a matrix or an *_ipm objectplot.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 objectsprint.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 iterationleft_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 multiplicationleft_mult right_mult
Simple deterministic IPM examplesim_di_det_ex
Eviction correctiondiscrete_extrema truncated_distributions
Predict methods in ipmruse_vr_model