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multivar
View on CRAN: Click
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Download and install multivar package within the R console
Install from CRAN:
install.packages("multivar")
Install from Github:
library("remotes")
install_github("cran/multivar") Install by package version:
library("remotes")
install_version("multivar", "1.4.0") Attach the package and use:
library("multivar")
Maintained by
Zachary Fisher
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[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-07-01
Latest Update: 2022-05-27
Description:
Functions for simulating, estimating and forecasting stationary Vector Autoregressive (VAR) models for multiple subject data using the penalized multi-VAR framework in Fisher, Kim and Pipiras (2020) .
How to cite:
Zachary Fisher (2020). multivar: Penalized Estimation of Multiple-Subject Vector Autoregressive Models. R package version 1.4.0, https://cran.r-project.org/web/packages/multivar. Accessed 03 Oct. 2026.
Previous versions and publish date:
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Complete documentation for multivar
Functions, R codes and Examples using
the multivar R package
Some associated functions: canonical.multivar-methods . constructModel . cv.multivar-methods . dat_multivar_sim . multivar-class . multivar-package . multivar_sim . plot_results . plot_sim . plot_transition_mat . show-methods .
Some associated R codes: RcppExports.R . breakup_transition.R . cv_admm.R . cv_blocked.R . cv_multivar.R . cv_rolling.R . data.R . est_base_weight_mat.R . extract_results.R . fit_canonical_var.R . lambda_grid.R . multivar.R . multivar.solver.R . multivarObjectClass.R . multivar_admm.R . multivar_bdiag.R . multivar_sim.R . plot_results.R . plot_sim.R . plot_transition_mat.R . setup_data.R . var_forecast.R . var_sim.R . wlasso.R . Full multivar package functions and examples
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