Effective Sample Size with the Bivariate Gaussian Common Component Model
, Luciana Pagliosa Carvalho Guedes, Miguel Angel Uribe-Opazo * and Tamara Cantu MaltauroRound 1
Reviewer 1 Report (Previous Reviewer 1)
Comment on: stats-2658272
"EFFECTIVE SAMPLE SIZE WITH THE BIVARIATE GAUSSIAN COMMON COMPONENT MODEL"
The authors took pains to respond to previous comments, which led to significant improvement of the manuscript. The manuscript is very interesting in terms of content and can be published in the Journal of Stats with the current version of the manuscript after modifying some simple comments.
1. Line 24-26. " One problem that several researchers have been discussing and seeking solutions to is to determine the equivalent number of independent observations contained in n [16, 17, 32 - 34]. " should be changed to "One problem that several researchers have been discussing and seeking solutions to is determining the equivalent number of independent observations in [16, 17, 32 -- 34]".
2. Try to improve Figures 3 and 4 more clearly.
3. There are still some typos and syntax issues, and it is necessary to make grammatical changes.
Comments for author File: 
Comments.pdf
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Reviewer 2 Report (Previous Reviewer 2)
I see that the authors have addressed comments from the reviewers. The manuscript has been improved and can be published in Stats.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.
Round 1
Reviewer 1 Report
The manuscript is very interesting in terms of content and can be published in the Journal of Stats with the current version of the manuscript after modifying some minor comments.
1. In the abstract, lines 1,2 and 3 " The Effective Sample Size (ESS) is based on the premise that as spatial autocorrelation between georeferenced data increases, the amount of duplicate information also rises. ESS utilizes the effects of spatial autocorrelation to calculate the number of independent observations, representing the new sample size." should be deleted. These are self-evident statements. The authors should craft stronger statements that will attract readers to the manuscript.
2. In the introduction section, all references are old, except for [5],[6],[7],[19], [29], [30], and [32] references. There are no references in 2022 at all.
3. Line 57. The paper was divided into two stages. Firstly, it really exists and secondly, it does not exist. I think this paragraph must be rewritten well.
4. Line 87. Random field S₀ is common to variables Y₁ and Y₂. Why?
5. Make sure to formulate Equation (5).
6. The authors could strengthen their argument with regard to the scientific novelty and also justify the need to develop an integrated assessment framework (Including Comparison and analysis). I would like to request the authors to emphasize the contributions practically and academically in the comparison and analysis session.
7. In addition to the fantastic Conclusion and Discussion section, I think it would be better to include the most notable results as bright spots at the end of the section.
8. Partial rewriting and careful proofreading of the entire paper are required, as many typos and drafting problems often occur, and grammatical changes are necessary.
Comments for author File: Comments.pdf
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Reviewer 2 Report
Please find attached.
Comments for author File: Comments.pdf
Minor edits required.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Round 2
Reviewer 2 Report
While the authors' reply to the revision letter is a bit messy, the revision of the article is prefunctory. The explanations are not convincing, nor the revision is in place for publication.
N.A.
