pass user-defined bias argument to bootstrap estimations #260
+1
−1
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
in Bootstrap::run_em, EMAlgorithm::run is called with the fourth argument set to false, that is without bias estimation even if the user set the --bias option on command line. This causes in some cases major discrepancies between the intial EM estimate and bootstrap estimates, which renders the bootstrap estimates inadequate to estimate the uncertainty of the abundance ML estimates (see pachterlab#151 for an example).
|
ping @pmelsted |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
in Bootstrap::run_em, EMAlgorithm::run is called with the fourth
argument set to false, that is without bias estimation even if the
user set the --bias option on command line. This causes in some cases
major discrepancies between the intial EM estimate and bootstrap
estimates, which renders the bootstrap estimates inadequate to
estimate the uncertainty of the abundance ML estimates (see #151 for
an example).
I should add that this fix is probably naive, as the bias estimate is done repeatedly for each bootstrap iteration. I've not benchmarked it properly, but the runs with this fix seemed to have a longer execution time. I'm happy to try and improve the patch if it can help.