R: Computations Around Bayesian Predictive Power

# Computations Around Bayesian Predictive Power

## Documentation for package ‘bpp’ version 1.0.6

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

## Help Pages

bpp-package | Tools for Computation of Bayesian Predictive Power for a Normally Distributed Endpoint with Known Variance
basicPlot | Basic plot functions to illustrate prior and posterior densities when considering a time-to-event endpoint
bpp | Bayesian Predictive Power (BPP) for Normally Distributed Endpoint
bpp_1interim | Bayesian Predictive Power (BPP) for Normally Distributed Endpoint
bpp_1interim_binary | Bayesian Predictive Power (BPP) for Binary Endpoint
bpp_1interim_continuous | Bayesian Predictive Power (BPP) for Continuous Endpoint
bpp_1interim_t2e | Bayesian Predictive Power (BPP) for Time-to-Event Endpoint
bpp_2interim | Bayesian Predictive Power (BPP) for Normally Distributed Endpoint
bpp_binary | Bayesian Predictive Power (BPP) for Binary Endpoint
bpp_continuous | Bayesian Predictive Power (BPP) for Continuous Endpoint
bpp_t2e | Bayesian Predictive Power (BPP) for Time-To-Event Endpoint
ddcp | Tools for Computation of Bayesian Predictive Power for a Normally Distributed Endpoint with Known Variance
dUniformNormalTails | Density and CDF for Uniform Distribution with Normal tails
estimate_posterior | Posterior density conditional on known interim result
estimate_posterior_nominator | Posterior density conditional on interim result is proportional to the value of this function
estimate_toIntegrate | Product of posterior density and conditional power for known interim result
FlatNormalPosterior | Integrand to compute Bayesian Predictive Power when flat prior has been updated with likelihood
interval_posterior_nominator | Posterior density conditional on interim result, only known as interval, is proportional to the value of this function
interval_posterior_nominator2 | Posterior density conditional on two interim results, both only known as intervals, is proportional to the value of this function
interval_toIntegrate | Product of posterior density and conditional power for blinded interim result
interval_toIntegrate2 | Product of posterior density and conditional power for blinded interim result
NormalNormalPosterior | Normal-Normal Posterior in conjugate normal model, for known sigma
post_power | Conditional power conditioning on a blinded interim
pts | Tools for Computation of Bayesian Predictive Power for a Normally Distributed Endpoint with Known Variance
pUniformNormalTails | Density and CDF for Uniform Distribution with Normal tails