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# Review Checklist
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# Review Checklist
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* [ ] Formalism described in [LIGO-P2000216](https://dcc.ligo.org/LIGO-P2000216) / [arXiv:2007.01372](https://arxiv.org/abs/2007.01372) is correct
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* [X] Formalism described in [LIGO-P2000216](https://dcc.ligo.org/LIGO-P2000216) / [arXiv:2007.01372](https://arxiv.org/abs/2007.01372) is correct
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* [ ] Monte-Carlo point-estimates and error estimates derived in [monte-carlo-derivations.pdf](uploads/06f0131a22f824afdf9acebd5460981a/monte-carlo-derivations.pdf) are correct
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* [X] Monte-Carlo point-estimates and error estimates derived in [monte-carlo-derivations.pdf](uploads/06f0131a22f824afdf9acebd5460981a/monte-carlo-derivations.pdf) are correct
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* *Note!* Reed found smally typos in the error estimates published on arXiv (v1 and v2) associated with covariance between "f" and "g", etc. The attached notes correct this (and it has been corrected in the code).
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* *Note!* Reed found smally typos in the error estimates published on arXiv (v1 and v2) associated with covariance between "f" and "g", etc. The attached notes correct this (and it has been corrected in the code).
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* The attached notes also provide explicit formulas for the estimation of the bayes factor, which are only suggested in the arxiv versions. The code implements what is shown in the attached notes.
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* The attached notes also provide explicit formulas for the estimation of the bayes factor, which are only suggested in the arxiv versions. The code implements what is shown in the attached notes.
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* The Bayes factor estimates are not yet reviewed but everything else in the attached notes is.
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* [ ] Monte-Carlo algorithms are correctly implemented within calls to [utils.prob_odds](https://git.ligo.org/reed.essick/mmax-model-selection/-/blob/master/mmax_model_selection/utils.py#L434) (or [utils.post_prior_bayes](https://git.ligo.org/reed.essick/mmax-model-selection/-/blob/master/mmax_model_selection/utils.py#L476) as appropriate).
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* [ ] Monte-Carlo algorithms are correctly implemented within calls to [utils.prob_odds](https://git.ligo.org/reed.essick/mmax-model-selection/-/blob/master/mmax_model_selection/utils.py#L434) (or [utils.post_prior_bayes](https://git.ligo.org/reed.essick/mmax-model-selection/-/blob/master/mmax_model_selection/utils.py#L476) as appropriate).
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* [ ] population priors are correctly implemented within calls to [utils.population_weights](https://git.ligo.org/reed.essick/mmax-model-selection/-/blob/master/mmax_model_selection/utils.py#L107)
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* [ ] population priors are correctly implemented within calls to [utils.population_weights](https://git.ligo.org/reed.essick/mmax-model-selection/-/blob/master/mmax_model_selection/utils.py#L107)
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* [ ] reweighting of single-event posterior samples is by population priors is correctly done within the [mmax-model-selection executable](https://git.ligo.org/reed.essick/mmax-model-selection/-/blob/master/bin/mmax-model-selection#L153)
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* [ ] reweighting of single-event posterior samples is by population priors is correctly done within the [mmax-model-selection executable](https://git.ligo.org/reed.essick/mmax-model-selection/-/blob/master/bin/mmax-model-selection#L153)
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