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 |