Package: quadVAR 0.1.2

quadVAR: Quadratic Vector Autoregression

Estimate quadratic vector autoregression models with the strong hierarchy using the Regularization Algorithm under Marginality Principle (RAMP) by Hao et al. (2018) <doi:10.1080/01621459.2016.1264956>, compare the performance with linear models, and construct networks with partial derivatives.

Authors:Jingmeng Cui [aut, cre]

quadVAR_0.1.2.tar.gz
quadVAR_0.1.2.zip(r-4.7)quadVAR_0.1.2.zip(r-4.6)quadVAR_0.1.2.zip(r-4.5)
quadVAR_0.1.2.tgz(r-4.6-any)quadVAR_0.1.2.tgz(r-4.5-any)
quadVAR_0.1.2.tar.gz(r-4.7-any)quadVAR_0.1.2.tar.gz(r-4.6-any)
quadVAR_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
quadVAR/json (API)

# Install 'quadVAR' in R:

install.packages('quadVAR', repos = c('https://sciurus365.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/sciurus365/quadvar/issues

Pkgdown/docs site:https://sciurus365.github.io

On CRAN:

2.70 score 3 scripts 239 downloads 10 exports 99 dependencies

Last updated from:8f8207c6fe. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	146
source / vignettes	OK	204
linux-release-x86_64	OK	146
macos-release-arm64	OK	77
macos-oldrel-arm64	OK	106
windows-devel	OK	86
windows-release	OK	93
windows-oldrel	OK	94
wasm-release	OK	137

Exports:%>%block_cv compare_4_emo linear_quadVAR_network partial_plot quadVAR quadVAR_to_dyn_eqns sim_4_emo true_model_4_emo tune.fit

Dependencies:abind backports base64enc bslib cachem checkmate cli cluster colorspace commonmark corpcor cpp11 data.table digest dplyr evaluate farver fastmap fdrtool fontawesome foreign Formula fs generics ggplot2 glasso glue GPArotation gridExtra gtable gtools highr Hmisc htmlTable htmltools htmlwidgets httpuv igraph isoband jpeg jquerylib jsonlite knitr labeling later lattice lavaan lifecycle magrittr MASS Matrix memoise mime mnormt ncvreg nlme nnet numDeriv otel pbapply pbivnorm pillar pkgconfig plyr png promises psych purrr qgraph quadprog R6 RAMP rappdirs RColorBrewer Rcpp reshape2 rlang rmarkdown rpart rstudioapi S7 sass scales shiny shinythemes sourcetools stringi stringr tibble tidyr tidyselect tinytex utf8 vctrs viridisLite withr xfun xtable yaml

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Use Block Cross-Validation to Evaluate Models	block_cv
Compare estimated model with true model for 4-emotion model	compare_4_emo
Find index of data that satisfies certain conditions	find_index
Extract the adjacency matrix from a quadVAR object.	get_adj_mat
Linearize a quadVAR object to produce a network.	linear_quadVAR_network plot.linear_quadVAR_network
Make a partial plot of a variable in a model This function takes a quadVAR model as input, and returns a plot of the partial effect of a variable on the dependent variable (controlling all other variables and the intercept), for higher and lower levels of the moderator variable split by the median.	partial_plot
Predict the values of the dependent variables using the quadVAR model	predict.quadVAR
Estimate lag-1 quadratic vector autoregression models	coef.quadVAR plot.quadVAR print.coef_quadVAR print.quadVAR quadVAR summary.quadVAR
Transform a quadVAR object to a list of dynamic equations.	quadVAR_to_dyn_eqns
Simulate a 4-emotion model	sim_4_emo
True model for 4-emotion model	coef.true_model_4_emo print.true_model_4_emo true_model_4_emo
Using the glmnet and ncvreg packages, fits a Generalized Linear Model or Cox Proportional Hazards Model using various methods for choosing the regularization parameter lambda	tune.fit