Bayesian Dynamic Borrowing with Flexible Baseline Hazard Function

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Documentation for package ‘BayesFBHborrow’ version 2.0.1

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.beta.MH.RW.glm Beta MH RW sampler from freq PEM fit
.beta_MH_MALA Proposal beta with a Metropolis Adjusted Langevin (MALA)
.beta_MH_NR Newton Raphson MH move
.beta_MH_RW Beta Metropolis-Hastings Random walk move
.beta_mom Mean for MALA using derivative for beta proposal
.beta_mom.NR.fun First and second derivative of target for mode and variance of proposal
.birth_move Birth move in RJMCMC
.dataframe_fun Create data.frame for piecewise exponential models
.death_move Death move in RJMCMC
.glmFit Fit frequentist piecewise exponential model for MLE and information matrix of beta
.ICAR_calc Calculate covariance matrix in the MVN-ICAR
.input_check Input checker
.J_RJMCMC RJMCMC (with Bayesian Borrowing)
.J_RJMCMC_NoBorrow RJMCMC (without Bayesian Borrowing)
.lambda_0_MH_cp Lambda_0 MH step, proposal from conditional conjugate posterior
.lambda_0_MH_cp_NoBorrow Lambda_0 MH step, proposal from conditional conjugate posterior
.lambda_conj_prop Propose lambda from a gamma conditional conjugate posterior proposal
.lambda_MH_cp Lambda MH step, proposal from conditional conjugate posterior
.lgamma_ratio Calculate log gamma ratio for two different parameter values
.llikelihood_ratio_beta Loglikelihood ratio calculation for beta parameters
.llikelihood_ratio_lambda Log likelihood for lambda / lambda_0 update
.logsumexp Computes the logarithmic sum of an exponential
.log_likelihood Log likelihood function
.lprop.dens.beta.NR log Gaussian proposal density for Newton Raphson proposal
.lprop_density_beta Log density of proposal for MALA
.ltau_dprior Calculate log density tau prior
.mu_update Calculate mu posterior update
.normalize_prob Normalize a set of probability to one, using the the log-sum-exp trick
.nu_sigma_update Calculates nu and sigma2 for the Gaussian Markov random field prior, for a given split point j
.plot_hist Plot histogram from MCMC samples
.plot_matrix Plot smoothed baseline hazards
.plot_trace Plot MCMC trace
.predictive_hazard Predictive hazard from BayesFBHborrow object
.predictive_hazard_ratio Predictive hazard ratio (HR) from BayesFBHborrow object
.predictive_survival Predictive survival from BayesFBHborrow object
.set_hyperparameters Set tuning parameters
.set_tuning_parameters Set tuning parameters
.shuffle_split_point_location Metropolis Hastings step: shuffle the split point locations (with Bayesian borrowing)
.shuffle_split_point_location_NoBorrow Metropolis Hastings step: shuffle the split point locations (without Bayesian borrowing)
.sigma2_update Calculate sigma2 posterior update
.smooth_hazard Smoothed hazard function
.smooth_survival Smoothed survival curve
.tau_update Sample tau from posterior distribution
BayesFBHborrow BayesFBHborrow: Run MCMC for a piecewise exponential model
BayesFBHborrow.NoBorrow Run the MCMC sampler without Bayesian Borrowing
BayesFBHborrow.WBorrow Run the MCMC sampler with Bayesian Borrowing
coef.BayesFBHborrow Extract mean posterior values
GibbsMH S3 generic, calls the correct GibbsMH sampler
GibbsMH.NoBorrow GibbsMH sampler, without Bayesian Borrowing
GibbsMH.WBorrow GibbsMH sampler, with Bayesian Borrowing
group_summary Create group level data
init_lambda_hyperparameters Initialize lambda hyperparameters
piecewise_exp_cc Example data, simulated from a piecewise exponential model.
piecewise_exp_hist Example data, simulated from a piecewise exponential model.
plot.BayesFBHborrow Plot the MCMC results
summary.BayesFBHborrow Summarize fixed MCMC results
weibull_cc Example data, simulated from a Weibull distribution.
weibull_hist Example data, simulated from a Weibull distribution