Update paper.md

joss_submission/paper.md

@@ -57,7 +57,6 @@ affiliations:
 bibliography: paper.bib
 aas-doi: "10.3847/xxxxx <- update this with the DOI from AAS once you know it."
 aas-journal: "Journal of Open Source Software"
-
 ---
 
 # Summary
@@ -73,7 +72,7 @@ The `MultiHazard` R package is designed to enable practitioners to estimate the
 
 # Statement of need
 
-The MultiHazard package was developed in collaberation with the South Florida Water Management District (SFWMD) to improve level of service assessments for coastal infrastructure affected by both inland and coastal drivers [@Jane:2020]. Initially, the package was created to implement the conditional sampling-copula theory approach. In two-sided conditional sampling a driver is conditioned to be extreme and paired with the maximum value of the other driver within a specified lag-time. The process is repeated with the drivers reversed yielding two conditional samples. The best fitting of 40 copulas are tested to model the dependence between drivers in each conditional sample. The isoline corresponding to a user specified return period is given by the outer envelope when overlaying the (conditional) contours from the copula model fit to each sample @Bender:2016, see Figure 1. To obtain a single design event, the probability of events on the isolines is calculated using an empirical density estimate, selecting the event with the highest probability. Some experts recommend sampling an ensemble of events from the isoline to account for uncertainty in design event selection which is also possible in the package. The conditional sampling – copula theory approach has continued to gain traction [@Kim:2023; @Maduwantha:2024] and in a review of the best-available, actionable science was highlighted as an approach that Federal agencies in the United States may wish to develop detailed technical guidance on how to use it meet their needs [@FFRMS:2023]. 
+The `MultiHazard` package was developed in collaberation with the South Florida Water Management District (SFWMD) to improve level of service assessments for coastal infrastructure affected by both inland and coastal drivers [@Jane:2020]. Initially, the package was created to implement the conditional sampling-copula theory approach. In two-sided conditional sampling a driver is conditioned to be extreme and paired with the maximum value of the other driver within a specified lag-time. The process is repeated with the drivers reversed yielding two conditional samples. The best fitting of 40 copulas are tested to model the dependence between drivers in each conditional sample. The isoline corresponding to a user specified return period is given by the outer envelope when overlaying the (conditional) contours from the copula model fit to each sample @Bender:2016, see Figure 1. To obtain a single design event, the probability of events on the isolines is calculated using an empirical density estimate, selecting the event with the highest probability. Some experts recommend sampling an ensemble of events from the isoline to account for uncertainty in design event selection which is also possible in the package. The conditional sampling – copula theory approach has continued to gain traction [@Kim:2023; @Maduwantha:2024] and in a review of the best-available, actionable science was highlighted as an approach that Federal agencies in the United States may wish to develop detailed technical guidance on how to use it meet their needs [@FFRMS:2023]. 
 
 ![Caption for example figure.\label{fig:isolines}](Figure_1.png)