References
- Annals of the Institute of Statistical Mathematics v.44 Bayesian inference for the power law process Bar-Lev, S. K.; Lavi, I.; Reiser, B. https://doi.org/10.1007/BF00053394
- Journal of the American Statistical Association v.84 Estimating a product of means : Bayesian analysis with reference priors Berger, J. O.; Bernardo, J. M. https://doi.org/10.2307/2289864
- In Bayesian Statistics 4 On the development of reference priors (with discussion) Berger, J. O.; Bernardo, J. M.; J. M. Bernardo(ed.); J. O. Berger(ed.); A. P. Dawid(ed.); A. F. M. Smith(ed.)
- Bayesian Analysis in Statistics and Econometrics Reference priors in a variance components problem Berger, J. O.; Bernardo, J. M.
- Journal of the Royal Statistical Society v.B41 Reference posterior distributions for Bayesian inference (with discussion) Bernardo, J. M.
- Bayesian Inference in Statistical Analysis Box, G. E. P.; Tiao, G. C.
- Biometrika v.83 On priors providing frequentist validity for Bayesian inference for multiple parametric function Datta, G. S. https://doi.org/10.1093/biomet/83.2.287
- Biometrika v.82 On priors providing frequentist validity for Bayesian inference Datta, G. S.; Ghosh, J. K. https://doi.org/10.1093/biomet/82.1.37
- Journal of the American Statistical Association v.90 Some remarks on noninformative priors Datta, G. S.; Ghosh, M. https://doi.org/10.2307/2291526
- The Annals of Statistics v.24 On the invariance of noninformative priors Datta, G. S.; Ghosh, M. https://doi.org/10.1214/aos/1033066203
- Technometrics v.20 Prediction intervals for the Weibull process Engelhardt, M.; Bain, L. J. https://doi.org/10.2307/1268709
- Canadian Journal of Statistics v.21 On priors that match posterior and frequentist distribution functions Ghosh, J. K.; Mukerjee, R. https://doi.org/10.2307/3315661
- IEEE Transactions on Reliability v.38 Bayes inference for a nonhomogeneous Poisson process with power intensity law Guida, M.; Calabria, R.; Pulcini, G. https://doi.org/10.1109/24.46489
- Computer Science and Statistics : Proceedings of the Sixteenth Symposium on the Interface Bayesian inference for the Weibull process with applications to assessing software reliability growth and predicting software failures Kyparisis, J.; Singpurwalla, N. D.
- Technometrics v.20 Some results on inference for the Weibull process Lee, L.; Lee, K. https://doi.org/10.2307/1268160
- Annals of the Institute of Statistical Mathematics v.49 Testing hypotheses about the power law process under failure truncation using intrinsic Bayes factors Lingham, R.; Sivagamesan, S. https://doi.org/10.1023/A:1003218410136
- Biometrika v.80 Frequentist validity of posterior quantiles in the presence of a nuisance parameter : higher order asymptotics Mukerjee, R.; Dey, D. K. https://doi.org/10.1093/biomet/80.3.499
- Biometrika v.84 Second order probability matching priors Mukerjee, R.; Ghosh, M. https://doi.org/10.1093/biomet/84.4.970
- Journal of the Royal Statistical Society v.B27 On confidence sets and Bayesian probability points in the case of several parameters Peers, H. W.
- Journal of Quality Technology v.21 The power law process : a model for the reliability of repairable systems Rigdon, S. E.; Basu, A. P.
- Sequential Methods in Statistics v.16 On coverage probability of confidence sets based on a prior distribution Stein, C.
- Biometrika v.76 Noninformative priors for one parameter of many Tibshirani, R. https://doi.org/10.1093/biomet/76.3.604
- Journal of the Royal Statistical Society v.B35 On formula for confidence points based on integrals of weighted likelihood Welch, B. N.; Peers, B.