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

5.68 score 3 stars 7 scripts 289 downloads 54 exports 5 dependencies

Last updated from:2ce8ae26c6. Checks:14 OK, 1 ERROR. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK178
linux-devel-x86_64OK234
source / vignettesERROR280
linux-release-arm64OK169
linux-release-x86_64OK196
macos-release-arm64OK219
macos-release-x86_64OK454
macos-oldrel-arm64OK186
macos-oldrel-x86_64OK397
windows-devel-arm64OK332
windows-devel-x86_64OK272
windows-release-arm64OK343
windows-release-x86_64OK278
windows-oldrel-x86_64OK230
wasm-releaseOK126

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_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_fp_jacobiansim_is_bipartitesim_iterationssim_listsim_logssim_potentialsim_runsstatic_blvimterminals

Dependencies:clicollapseRcppRcppArmadillorlang

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: 2026-05-21
Started: 2025-06-06

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: 2025-12-26
Started: 2025-10-11

Readme and manuals

Help Manual

Help pageTopics
Coerce to a Data Frameas.data.frame.sim_list
Extract the attractivenesses from a spatial interaction model objectattractiveness
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 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 this modelcosts
Extract the common cost matrix from a collection of spatial interaction modelscosts.sim_list
Compute the flows incoming 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
French cities distancesfrench_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 status from a collection of spatial interaction modelsgrid_is_terminal
Reports the convergence statuses of a collection of spatial interaction modelsgrid_sim_converged
Returns the number of iterations used to produce of a collection of spatial interaction modelsgrid_sim_iterations
Returns potential 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 this modelinverse_cost
Report whether locations are terminal sites or notis_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 this modelreturn_to_scale
Sample points from a weighted simplexsample_weighted_simplex
Get the collection of spatial interaction models from a SIM data framesim_column
Reports whether the spatial interaction model construction convergedsim_converged
Returns 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
Returns 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
Compute the Jacobian of the fixed-point map Gsim_fp_jacobian
Reports whether the spatial interaction model is bipartitesim_is_bipartite
Returns the number of iterations used to produce this spatial interaction modelsim_iterations
Create a sim_list object from a list of spatial interaction objectssim_list
Extract summaries of individual algorithm runssim_logs
Compute the potential of a spatial interaction modelsim_potential
Extract spatial interaction models produced by individual runssim_runs
Compute flows between origin and destination locationsstatic_blvim
Summary of a collection of spatial interaction modelsprint.summary_sim_list summary.sim_list
Compute terminals for a spatial interaction modelterminals