Package: tsnet 0.2.0

tsnet: Fitting, Comparing, and Visualizing Networks Based on Time Series Data

Fit, compare, and visualize Bayesian graphical vector autoregressive (GVAR) network models using 'Stan'. These models are commonly used in psychology to represent temporal and contemporaneous relationships between multiple variables in intensive longitudinal data. Fitted models can be compared with a test based on matrix norm differences of posterior point estimates to quantify the differences between two estimated networks. See also Siepe, Kloft & Heck (2024) <doi:10.31234/osf.io/uwfjc>.

Authors:Björn S. Siepe [aut, cre, cph], Matthias Kloft [aut], Daniel W. Heck [ctb]

tsnet_0.2.0.tar.gz
tsnet_0.2.0.zip(r-4.7-x86_64)tsnet_0.2.0.zip(r-4.7-arm64)tsnet_0.2.0.zip(r-4.6-x86_64)tsnet_0.2.0.zip(r-4.6-arm64)tsnet_0.2.0.zip(r-4.5-x86_64)
tsnet_0.2.0.tgz(r-4.6-x86_64)tsnet_0.2.0.tgz(r-4.6-arm64)tsnet_0.2.0.tgz(r-4.5-x86_64)tsnet_0.2.0.tgz(r-4.5-arm64)
tsnet_0.2.0.tar.gz(r-4.7-arm64)tsnet_0.2.0.tar.gz(r-4.7-x86_64)tsnet_0.2.0.tar.gz(r-4.6-arm64)tsnet_0.2.0.tar.gz(r-4.6-x86_64)
tsnet_0.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
tsnet/json (API)

# Install 'tsnet' in R:

install.packages('tsnet', repos = c('https://bsiepe.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/bsiepe/tsnet/issues

Uses libs:

onetbb– Parallelism library for C++
c++– GNU Standard C++ Library v3

Datasets:

fit_data - Example Posterior Samples
ts_data - Simulated Time Series Dataset

On CRAN:

onetbb cpp

3.23 score 2 stars 17 scripts 336 downloads 8 exports 58 dependencies

Last updated from:534711df6f. Checks:15 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	402
linux-devel-x86_64	OK	463
source / vignettes	OK	426
linux-release-arm64	OK	373
linux-release-x86_64	OK	411
macos-release-arm64	OK	434
macos-release-x86_64	OK	900
macos-oldrel-arm64	OK	506
macos-oldrel-x86_64	OK	950
windows-devel-arm64	OK	676
windows-devel-x86_64	OK	471
windows-release-arm64	OK	675
windows-release-x86_64	OK	617
windows-oldrel-x86_64	OK	505
wasm-release	OK	283

Exports:check_eigen compare_gvar get_centrality plot_centrality post_distance_within posterior_plot stan_fit_convert stan_gvar

Dependencies:abind backports BH callr checkmate cli cowplot cpp11 desc distributional dplyr farver generics ggdist ggokabeito ggplot2 glue gridExtra gtable inline isoband labeling lifecycle loo magrittr matrixStats numDeriv otel pillar pkgbuild pkgconfig posterior processx ps purrr quadprog QuickJSR R6 RColorBrewer Rcpp RcppEigen RcppParallel rlang rstan rstantools S7 scales StanHeaders stringi stringr tensorA tibble tidyr tidyselect utf8 vctrs viridisLite withr

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
The 'tsnet' package	tsnet-package tsnet
Check Eigenvalues of Bayesian GVAR object	check_eigen
Compare two Bayesian GVAR models	compare_gvar
Example Posterior Samples	fit_data
Compute Centrality Measures	get_centrality
Plot Centrality Measures	plot_centrality
Plot compare_gvar	plot.compare_gvar
Calculates distances between pairs of posterior samples using the posterior samples or posterior predictive draws	post_distance_within
posterior_plot	posterior_plot
Print method for compare_gvar objects	print.compare_gvar
Print method for tsnet_fit objects	print.tsnet_fit
Convert Stan Fit to Array of Samples	stan_fit_convert
Fit Bayesian Graphical Vector Autoregressive (GVAR) Models with Stan	stan_gvar
Simulated Time Series Dataset	ts_data