Computations Around Bayesian Predictive Power


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Documentation for package ‘bpp’ version 1.0.1

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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_2interim Bayesian Predictive Power (BPP) for Normally Distributed 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