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Peer-Review Record

Probabilistic Pairwise Model Comparisons Based on Bootstrap Estimators of the Kullback–Leibler Discrepancy

Entropy 2022, 24(10), 1483; https://doi.org/10.3390/e24101483
by Andres Dajles *,† and Joseph Cavanaugh †
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Entropy 2022, 24(10), 1483; https://doi.org/10.3390/e24101483
Submission received: 27 September 2022 / Revised: 15 October 2022 / Accepted: 16 October 2022 / Published: 18 October 2022
(This article belongs to the Special Issue Information and Divergence Measures)

Round 1

Reviewer 1 Report

Authors in this paper use a bootstrap approximation of the Kullback-Leibler discrepancy to estimate the probability of fitting the model.They propose correction of the bias.

In the simulation studies they used a maximum likelihood estimators and they conduct testing.

Next for n = 25, 50, 100 and 500 they give a mean and median for all used methods.

Finaly they give results of expected value for bootstrap estimate and bias of the corrected bootstrap.

Then they discuss the simulation and give applications.

The obtained results show that the authors managed to introduce a model that functions better than the previous ones.

Therefore I recommend the paper by Dajles A. and Cavanaugh J. entitled Probabilistic Pairwise Model Comparisons Based on Bootstrap Estimators of the Kullback-Leibler Discrepancy” for publication in “Entropy” journal.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

See the attached report.

Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

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