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| Question | Yes | Unsure | N/A | No |
|---|---|---|---|---|
| Are the findings novel? | 100% | 0% | 0% | 0% |
| Are the results likely to lead to future research? | 100% | 0% | 0% | 0% |
| Is sufficient detail provided to allow reproduction of the study? | 0% | 0% | 0% | 100% |
| Are the methods and statistics appropriate for the analysis? | 100% | 0% | 0% | 0% |
| Are the principal conclusions supported by the data and analysis? | 100% | 0% | 0% | 0% |
| Does the manuscript discuss limitations? | 100% | 0% | 0% | 0% |
| Have the authors adequately discussed ethical concerns? | 0% | 0% | 100% | 0% |
| Does the manuscript include new data? | 0% | 0% | 0% | 100% |
| Are the data used in the manuscript available? | 0% | 0% | 100% | 0% |
| Is the code used in the manuscript available? | 0% | 100% | 0% | 0% |
| Would you recommend this manuscript to others? | 100% | 0% | 0% | 0% |
| Do you recommend this manuscript for peer review? | 100% | 0% | 0% | 0% |
This paper gives a good overview on Bayesian inference for quantile distributions, covering the theoretical basis and practical methods. There are also plenty of useful examples. The paper also introduces novel methodology for some stages of the process. Overall I recommend the paper as an good…