Quadratic Vector Autoregression


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Documentation for package ‘quadVAR’ version 0.1.2

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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