Package: aniSNA 1.2.1

Michael Salter-Townshend

aniSNA: Statistical Network Analysis of Animal Social Networks

Obtain network structures from animal GPS telemetry observations and statistically analyse them to assess their adequacy for social network analysis. Methods include pre-network data permutations, bootstrapping techniques to obtain confidence intervals for global and node-level network metrics, and correlation and regression analysis of the local network metrics.

Authors:Prabhleen Kaur [aut], Michael Salter-Townshend [ctb, cre]

aniSNA_1.2.1.tar.gz
aniSNA_1.2.1.zip(r-4.7-x86_64)aniSNA_1.2.1.zip(r-4.7-arm64)aniSNA_1.2.1.zip(r-4.6-x86_64)aniSNA_1.2.1.zip(r-4.6-arm64)
aniSNA_1.2.1.tar.gz(r-4.7-arm64)aniSNA_1.2.1.tar.gz(r-4.7-x86_64)aniSNA_1.2.1.tar.gz(r-4.6-arm64)aniSNA_1.2.1.tar.gz(r-4.6-x86_64)
aniSNA_1.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
aniSNA/json (API)

# Install 'aniSNA' in R:
install.packages('aniSNA', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

cpp

1.70 score 385 downloads 19 exports 54 dependencies

Last updated from:7ff243d555. Checks:10 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK133
linux-devel-x86_64OK150
source / vignettesOK199
linux-release-arm64OK130
linux-release-x86_64OK130
windows-devel-arm64OK255
windows-devel-x86_64OK201
windows-release-arm64OK248
windows-release-x86_64OK116
wasm-releaseOK110

Exports:bootstrapped_difference_pvaluescorrelation_analyzedistance_radian_coordinatesget_coordinates_in_radianget_interactionsget_network_summaryget_spatial_thresholdglobal_CIglobal_width_CIinteracting_pairsnetwork_from_interactionsnode_level_CIobtain_bootstrapped_samplesobtain_network_subsamplesobtain_permuted_network_versionsplot_networkregression_slope_analyzesubsampled_network_metricssubsampled_permuted_network_metrics

Dependencies:base64enccachemclicpp11dplyrfarverfastmapgenericsggforceggplot2ggraphggrepelgluegraphlayoutsgridExtragtableigraphisobandjsonlitelabelinglatticelifecyclelubridatemagrittrMASSMatrixmemoisepillarpkgconfigplyrpolyclippurrrR6RColorBrewerRcppRcppArmadilloreshaperlangS7scalesstringistringrsystemfontstibbletidygraphtidyrtidyselecttimechangetweenrutf8vctrsviridisviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
aniSNAaniSNA-package aniSNA
To obtain two non-overlapping bootstrapped versions and obtain p-values for the significance of difference between thembootstrapped_difference_pvalues
To perform correlation analysis for node-level network metricscorrelation_analyze
Calculate distance between two pairs of radian coordinatesdistance_radian_coordinates
A list of 100 igraph objects obtained by permuting the raw elk_data_2010 and obtaining network from thoseelk_2010_permutations
Dataset of all possible interactions from elk_data_2010elk_all_interactions_2010
Data to showcase functions in our packageelk_data_2010
Dataset of interactions from elk_data_2010 using first mode as the spatial thresholdelk_interactions_2010
An igraph object depicting the network obtained from elk_interactions_2010elk_network_2010
To convert latitude and longitude values from degrees to radiansget_coordinates_in_radian
To obtain interactions from raw GPS observationsget_interactions
Calculates and prints network summary statisticsget_network_summary
To obtain spatial threshold for calculating interactions from raw GPS observations. The threshold is obtained as the distance interval that captures maximum number of inter-individual interactions.get_spatial_threshold
To obtain confidence intervals around the observed global network statisticsglobal_CI
To obtain width of confidence intervals for global network metrics using bootstrapped versions at each level of sub-samplingglobal_width_CI
Function to obtain pairs of interacting animalsinteracting_pairs
Function to obtain a network structure from interactions dataframenetwork_from_interactions
To obtain confidence intervals for node-level network metricsnode_level_CI
To obtain bootstrapped versions of a network's adjacency matrixobtain_bootstrapped_samples
To obtain sub-networks of the observed networkobtain_network_subsamples
Function to obtain permuted networks from raw datastreamobtain_permuted_network_versions
Visualize Animal Networkplot_network
To plot the results obtained from bootstrapped_difference_pvalues functionplot.bootstrapped_pvalue_matrix
To plot correlation analysis resultsplot.list_correlation_matrices
To plot the results for node-level confidence intervalsplot.list_node_level_CI
Function to plot the network metrics distribution of permuted networksplot.list_permuted_networks
To plot regression analysis resultsplot.list_regression_matrices
To plot sub-sampling resultsplot.Subsampled_Network_Metrics
To plot sub-sampling results of the original network and permuted networksplot.Subsampled_Permuted_Network_Metrics
To plot the results obtained from width_CI functionplot.Width_CI_matrix
To perform regression analysis for local network metricsregression_slope_analyze
To generate subsamples and obtain network metrics of the subsamplessubsampled_network_metrics
To generate subsamples of the permuted networks and obtain network metrics of those subsamplessubsampled_permuted_network_metrics