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In Section 7, in simulations, using this signal, we have sketched the range-velocity plot to visualize the results of detection and ROC plot to verify the advantages of our work compared to IPCP.
We plotted residuals versus fitted values and constructed a quantile probability plot to verify that the residual distribution was normal.
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The reaction rate versus xylan concentration was plotted to verify whether the reaction mode conformed to the Michaelis Menten equation.
We used the Kolmogorov Smirnov test and stratified the distribution plots to verify the distribution normality of the continuous variables.
We inspected residual plots to verify linearity, normality, and homoscedasticity assumptions and ensured that multicollinearity between covariates was generally low based on variance inflation factors.
In Northern and Central Androy (areas II and III in Figure 1) we used 20×20 m plots to verify the classes of dense stable forest and increasing forest cover.
The ROC curve was also plotted to verify the accuracy of CFH for composite outcome prediction.
Melting curves were plotted to verify the specificity of the amplified products.
We used figures plots to verify that relationships, if any, between biomarkers and 25(OH D concentrations were linear.
We used a Kolmogorov-Smirnov test and stratified distribution plots to verify the normality of distribution of continuous variables.
The residuals from the linear mixed model were plotted to verify that they were approximately normally distributed and to confirm that there were no influential outliers.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com