R: Quadratic Vector Autoregression

# Quadratic Vector Autoregression

## Documentation for package ‘quadVAR’ version 0.1.2

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

block_cv | Use Block Cross-Validation to Evaluate Models
coef.quadVAR | Estimate lag-1 quadratic vector autoregression models
coef.true_model_4_emo | True model for 4-emotion model
compare_4_emo | Compare estimated model with true model for 4-emotion model
find_index | Find index of data that satisfies certain conditions
get_adj_mat | Extract the adjacency matrix from a quadVAR object.
linear_quadVAR_network | Linearize a quadVAR object to produce a network.
partial_plot | 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.
plot.linear_quadVAR_network | Linearize a quadVAR object to produce a network.
plot.quadVAR | Estimate lag-1 quadratic vector autoregression models
predict.quadVAR | Predict the values of the dependent variables using the quadVAR model
print.coef_quadVAR | Estimate lag-1 quadratic vector autoregression models
print.quadVAR | Estimate lag-1 quadratic vector autoregression models
print.true_model_4_emo | True model for 4-emotion model
quadVAR | Estimate lag-1 quadratic vector autoregression models
quadVAR_to_dyn_eqns | Transform a quadVAR object to a list of dynamic equations.
sim_4_emo | Simulate a 4-emotion model
summary.quadVAR | Estimate lag-1 quadratic vector autoregression models
true_model_4_emo | True model for 4-emotion model
tune.fit | 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