Introduction | Computing the log-concave estimator | Characterization and properties of the estimator | Smoothing the log-concave density estimator | Implementation and main functions | Sampling from the different estimators | Illustration of main functions on simulated example | Exemplary analysis of reliability dataset | Smooth two-sample permutation test | Final remarks | Density, distribution and quantile function | The integral of F at an arbitrary x0 | The smoothed log-concave density estimator | The smoothed log-concave CDF estimator | Computation of the two-sample test statistic

Acknowledgments | Purpose | Resources and how to cite eventTrack | Challenge | Methodology | Example: simulating data and detailed prediction | Simulating an illustrative dataset | Estimate $S$ | Prediction of the timepoint of the FA | Using parametric Weibull instead of hybrid exponential estimate | Example: minimal analysis | Possible extensions | Strategic context | Other approaches | gestate | Info | References

Purpose | Setup | Define the prior distributions | Computation of all quantities in Table 1, and all the figures | Interesting probabilities | BPP at the beginning of the trial | Update the prior distribution with external information | Update the prior distribution after not stopping at an interim analysis | Posterior densities | Table 1 in @rufibach_14 | Update of BPP when not stopping the trial in two blinded interim analyses | Info | References

About this document | Introduction | Stanford heart transplantation data | Descriptive statistics for heart transplantation data | Conclusions | Acknowledgments