Function reference • countSTAR

Classical STAR Regression

Methods for STAR models estimated using EM algorithm

lm_star(): Fitting frequentist STAR linear model via EM algorithm

confint(<lmstar>): Compute asymptotic confidence intervals for STAR linear regression

predict(<lmstar>): Predict method for response in STAR linear model

pvals(): Compute coefficient p-values for STAR linear regression using likelihood ratio test

randomForest_star(): Fit Random Forest STAR with EM algorithm

gbm_star(): Fitting STAR Gradient Boosting Machines via EM algorithm

genEM_star(): Generalized EM estimation for STAR

Bayesian STAR Regression

Methods for STAR models estimated using Bayesian methods (either Gibbs sampling or exact Monte Carlo estimation in certain scenarios)

blm_star(): STAR Bayesian Linear Regression

bam_star(): Fit Bayesian Additive STAR Model with MCMC

bart_star(): MCMC Algorithm for BART-STAR

spline_star(): Estimation for Bayesian STAR spline regression

genMCMC_star(): Generalized MCMC Algorithm for STAR

init_lm_gprior(): Initialize linear regression parameters assuming a g-prior

sample_lm_gprior(): Sample the linear regression parameters assuming a g-prior

WarpDLMs (Count Time Series Modeling)

Methods for warped Dynamic Linear Models to perform Bayesian inference and forecasting for count-valued time series

warpDLM(): Posterior Inference for warpDLM model with latent structural DLM

Helper Functions

Transformation and Rounding Functions

a_j(): Inverse rounding function

round_floor(): Rounding function

g_bc(): Box-Cox transformation

g_bnp(): Bayesian bootstrap-based transformation

g_cdf(): Cumulative distribution function (CDF)-based transformation

g_inv_approx(): Approximate inverse transformation

g_inv_bc(): Inverse Box-Cox transformation

Simulation and Visualization

simulate_nb_friedman(): Simulate count data from Friedman's nonlinear regression

simulate_nb_lm(): Simulate count data from a linear regression

plot_coef(): Plot the estimated regression coefficients and credible intervals

plot_fitted(): Plot the fitted values and the data

plot_pmf(): Plot the empirical and model-based probability mass functions

simBaS(): Compute Simultaneous Band Scores (SimBaS)

credBands(): Compute Simultaneous Credible Bands

getEffSize(): Summarize of effective sample size

ergMean(): Compute the ergodic (running) mean.

roaches: Data on the efficacy of a pest management system at reducing the number of roaches in urban apartments.