R: Bayesian Generalized Linear Models with Time-Varying Coefficients

# Bayesian Generalized Linear Models with Time-Varying Coefficients

## Documentation for package ‘walker’ version 1.0.10

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package README

## Help Pages

as.data.frame.walker_fit | Coerce Posterior Samples of walker Fit to a Data Frame
coef.walker_fit | Extract Coeffients of Walker Fit
fitted.walker_fit | Extract Fitted Values of Walker Fit
lfo | Leave-Future-Out Cross-Validation
plot_coefs | Posterior predictive check for walker object
plot_fit | Plot the fitted values and sample quantiles for a walker object
plot_predict | Prediction intervals for walker object
pp_check.walker_fit | Posterior predictive check for walker object
predict.walker_fit | Predictions for walker object
predict_counterfactual | Predictions for walker object
print.walker_fit | Print Summary of walker_fit Object
rw1 | Construct a first-order random walk component
rw2 | Construct a second-order random walk component
summary.walker_fit | Summary of walker_fit Object
walker | Bayesian regression with random walk coefficients
walker_glm | Bayesian generalized linear model with time-varying coefficients
walker_rw1 | Comparison of naive and state space implementation of RW1 regression model