Semiparametric Bayesian Regression Analysis


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Documentation for package ‘SeBR’ version 1.1.0

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all_subsets Compute all subsets of a set
bb Bayesian bootstrap posterior sampler for the CDF
bgp_bc Bayesian Gaussian processes with a Box-Cox transformation
blm_bc Bayesian linear model with a Box-Cox transformation
blm_bc_hs Bayesian linear model with a Box-Cox transformation and a horseshoe prior
bqr Bayesian quantile regression
bsm_bc Bayesian spline model with a Box-Cox transformation
computeTimeRemaining Estimate the remaining time in the algorithm
concen_hbb Posterior sampling algorithm for the HBB concentration hyperparameters
contract_grid Grid contraction
Fz_fun Compute the latent data CDF
g_bc Box-Cox transformation
g_fun Compute the transformation
g_inv_approx Approximate inverse transformation
g_inv_bc Inverse Box-Cox transformation
hbb Hierarchical Bayesian bootstrap posterior sampler
plot_pptest Plot point and interval predictions on testing data
rank_approx Rank-based estimation of the linear regression coefficients
sampleFastGaussian Sample a Gaussian vector using Bhattacharya et al. (2016)
sbgp Semiparametric Bayesian Gaussian processes
sblm Semiparametric Bayesian linear model
sblm_hs Semiparametric Bayesian linear model with horseshoe priors for high-dimensional data
sblm_modelsel Model selection for semiparametric Bayesian linear regression
sblm_ssvs Semiparametric Bayesian linear model with stochastic search variable selection
sbqr Semiparametric Bayesian quantile regression
sbsm Semiparametric Bayesian spline model
simulate_tlm Simulate a transformed linear model
sir_adjust Post-processing with importance sampling
square_stabilize Numerically stabilize the squared elements
SSR_gprior Compute the sum-squared-residuals term under Zellner's g-prior
uni.slice Univariate Slice Sampler from Neal (2008)