Package: blvim 0.1.1.9000

blvim: Boltzmann–Lotka–Volterra Interaction Model

Estimates Boltzmann–Lotka–Volterra (BLV) interaction model efficiently. Enables programmatic and graphical exploration of the solution space of BLV models when parameters are varied. See Wilson, A. (2008) <dx.doi.org/10.1098/rsif.2007.1288>.

Authors:Fabrice Rossi [aut, cre, cph], Cyprien Gout [ctb]

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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
blvim/json (API)

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

Bug tracker:https://github.com/fabrice-rossi/blvim/issues

Pkgdown/docs site:https://fabrice-rossi.github.io

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:

On CRAN:

Conda:

boltzmann-lotka-volterraspatial-analysisspatial-interaction-modelingopenblascppopenmp

5.71 score 3 stars 7 scripts 229 downloads 56 exports 5 dependencies

Last updated from:b94b23e2a4. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK145
linux-devel-x86_64OK237
source / vignettesOK295
linux-release-arm64OK218
linux-release-x86_64OK230
macos-release-arm64OK233
macos-release-x86_64OK409
macos-oldrel-arm64OK176
macos-oldrel-x86_64OK459
windows-devel-arm64OK330
windows-devel-x86_64OK257
windows-release-arm64OK365
windows-release-x86_64OK258
windows-oldrel-x86_64OK254
wasm-releaseOK132

Exports:attractivenessblvimblvim_gradient_controlblvim_initialiseblvim_simplex_initialisecostsdestination_flowdestination_namesdestination_names<-destination_positionsdestination_positions<-diversityflowsflows_dfgrid_attractivenessgrid_autoplotgrid_blvimgrid_destination_flowgrid_diversitygrid_is_terminalgrid_sim_convergedgrid_sim_historygrid_sim_iterationsgrid_sim_potentialgrid_var_autoplotinitial_attractivenessinverse_costis_terminallocation_nameslocation_names<-location_positionslocation_positions<-nd_graphorigin_namesorigin_names<-origin_positionsorigin_positions<-productionreturn_to_scalesample_weighted_simplexsim_columnsim_convergedsim_conversionsim_dfsim_diagnosticsim_distancesim_historysim_is_bipartitesim_iterationssim_listsim_logssim_potentialsim_residual_jacobiansim_runsstatic_blvimterminals

Dependencies:clicollapseRcppRcppArmadillorlang

Systematic exploration of the BLV solution space
Locations and setup | Computing a collection of models | Exploring the results | Single model extraction | Variability plot | Statistics-oriented display | Organising the results | Clustering the models | Showing cluster variability | Finding representative models | Real-world examples | European cities | Models | Clustering | Medoids | French cities | Production effects
Rendered fromgrid.Rmdusingknitr::rmarkdown

Last update: 2026-10-24
Started: 2025-10-11

Theoretical Background
Static Models | Spatial Interaction Models | Constraints | Maximum Entropy Models | Dynamic Models | Harris and Wilson Equilibrium Values | A Dynamic Model: The Boltzmann–Lotka–Volterra Model | Diversity | Self-Exchange Configurations | Location Domination and Terminals | Domination Graphs | Potential Function from Osawa et al. (2025) | The Potential Function | Gradient of the Potential Function | Hessian of the Potential Function | The General Hessian | Simplification at an Interior Equilibrium | KKT Conditions and Equilibrium Structure | References
Rendered fromtheory.Rmdusingknitr::rmarkdown

Last update: 2026-10-24
Started: 2025-06-06

Readme and manuals

Help Manual

Help pageTopics
Coerce a collection of spatial interaction models to a data frameas.data.frame.sim_list
Extract the attractivenesses from a spatial interaction model objectattractiveness
Plot the iteration history of blvimautoplot.blvim_history
Plot the runs of a multiple start blvimautoplot.blvim_logs
Create a complete ggplot for a spatial interaction modelautoplot.sim
Create a complete ggplot for a spatial interaction models data frameautoplot.sim_df
Create a complete variability plot for a collection of spatial interaction modelsautoplot.sim_list
Compute an equilibrium solution of the Harris and Wilson modelblvim
Control parameters for the blvim gradient algorithmsblvim_gradient_control
Specify how initial attractivenesses are generatedblvim_initialise
Generate initial attractivenesses from the weighted simplexblvim_simplex_initialise
Combine multiple sim_list objects into a single onec.sim_list
Extract the cost matrix used to compute a modelcosts
Extract the common cost matrix from a collection of spatial interaction modelscosts.sim_list
Compute the incoming flow at each destination locationdestination_flow
Names of destination locations in a spatial interaction modeldestination_names destination_names<-
Positions of destination locations in a spatial interaction modeldestination_positions destination_positions<-
Compute the diversity of the destination locations in a spatial interaction modeldiversity diversity.sim diversity.sim_list
Extract the flow matrix from a spatial interaction model objectflows
Extract the flow matrix from a spatial interaction model object in data frame formatflows_df
Turn a spatial interaction model into a data framefortify.sim
Turn a collection of spatial interaction models into a data framefortify.sim_list
French citiesfrench_cities
Distances and travel times between French citiesfrench_cities_distances french_cities_times
French departmentsfrench_departments
French regionsfrench_regions
Extract all the attractivenesses from a collection of spatial interaction modelsgrid_attractiveness
Create a complete ggplot for spatial interaction models in a data framegrid_autoplot
Compute a collection of Boltzmann-Lotka-Volterra model solutionsgrid_blvim
Extract all the destination flows from a collection of spatial interaction modelsgrid_destination_flow
Compute diversities for a collection of spatial interaction modelsgrid_diversity
Extract all terminal statuses from a collection of spatial interaction modelsgrid_is_terminal
Report the convergence statuses of a collection of spatial interaction modelsgrid_sim_converged
Return the iteration histories of a collection of spatial interaction modelsgrid_sim_history
Return the numbers of iterations used to produce a collection of spatial interaction modelsgrid_sim_iterations
Compute the potentials of a collection of spatial interaction modelsgrid_sim_potential
Create a complete variability plot for spatial interaction models in a data framegrid_var_autoplot
Extract the initial attractivenesses from a spatial interaction model objectinitial_attractiveness
Extract the inverse cost scale parameter used to compute a modelinverse_cost
Report whether locations are terminalsis_terminal
Names of origin and destination locations in a spatial interaction modellocation_names location_names<-
Positions of origin and destination locations in a spatial interaction modellocation_positions location_positions<-
Compute the "median" of a collection of spatial interaction modelsmedian.sim_list
Set the column names of a SIM data framenames<-.sim_df
Compute the Nystuen and Dacey graph for a spatial interaction modelnd_graph nd_graph.sim
Names of origin locations in a spatial interaction modelorigin_names origin_names<-
Positions of origin locations in a spatial interaction modelorigin_positions origin_positions<-
Extract the production constraints from a spatial interaction model objectproduction
Compute quantiles of the flows in a collection of spatial interaction modelsquantile.sim_list
Extract the return to scale parameter used to compute a modelreturn_to_scale
Sample points from a weighted simplexsample_weighted_simplex
Get the collection of spatial interaction models from a SIM data framesim_column
Report whether the construction of a spatial interaction model convergedsim_converged
Return the conversion factors between attractivenesses and incoming flowssim_conversion
Create a spatial interaction models data frame from a collection of interaction modelssim_df
Extract or replace parts of a SIM data frame$<-.sim_df sim_df_extract [.sim_df [<-.sim_df [[<-.sim_df
Return a full diagnostic of the algorithm used to build a spatial interaction modelsim_diagnostic
Compute all pairwise distances between the spatial interaction models in a collectionsim_distance
Return the iteration history of the algorithm used to build a spatial interaction modelsim_history
Report whether a spatial interaction model is bipartitesim_is_bipartite
Return the number of iterations used to produce a spatial interaction modelsim_iterations
Create a sim_list object from a list of spatial interaction modelssim_list
Extract summaries of individual algorithm runssim_logs
Compute the potential of a spatial interaction modelsim_potential
Compute the Jacobian of the residual map Gsim_residual_jacobian
Extract spatial interaction models produced by individual runssim_runs
Compute flows between origin and destination locationsstatic_blvim
Summary of the iteration history of blvimprint.summary_blvim_history summary.blvim_history
Summary of the runs of a multiple start blvimprint.summary_blvim_logs summary.blvim_logs
Summary of a collection of spatial interaction modelsprint.summary_sim_list summary.sim_list
Compute terminals for a spatial interaction modelterminals