From b7f8e410a93cb222e82c65058c43beb6a75669c9 Mon Sep 17 00:00:00 2001 From: "Mark A. Jensen" Date: Sat, 3 Apr 2021 18:45:59 -0400 Subject: [PATCH] JOSS Ed.: tweak --- osspaper/paper.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/osspaper/paper.md b/osspaper/paper.md index 861682f..8b95041 100644 --- a/osspaper/paper.md +++ b/osspaper/paper.md @@ -71,9 +71,9 @@ illustrates the power of the nlogistic-sigmoid neural pipeline. \linebreak `NLSI or predictions on the cumulative growth of an ongoing growth phenomena, whose source is both uncertain and complex to encode in current mathematical models [@christopoulosEfficientIdentificationInflection2016;@matthewWhyModelingSpread2020], this software package makes projections by means of: -- two-dimensional perspective metrics: Y-to-Inflection Ratio (YIR, here Y = Infections or Deaths); X-to-Inflection Ratio (XIR, here X = Time in Days) for robust monitoring of the growth-process being modelled in an area or locale of interest. +- two-dimensional perspective metrics: Y-to-Inflection Ratio (YIR, here Y = Infections or Deaths); X-to-Inflection Ratio (XIR, here X = Time in Days) for robust monitoring of the growth-process being modelled in an area or locale of interest, and -- adaptation of the Dvoretzky–Kiefer–Wolfowitz (DKW) inequality for the Kolmogorov–Smirnov (KS) test to construct a non-parametric confidence interval of uncertainty on the nlogistic-sigmoid model with a 99% probability ($\alpha=0.01$) by default. +- an adaptation of the Dvoretzky–Kiefer–Wolfowitz (DKW) inequality for the Kolmogorov–Smirnov (KS) test to construct a non-parametric confidence interval of uncertainty on the nlogistic-sigmoid model with a 99% probability ($\alpha=0.01$) by default. `NLSIG-COVID19Lab` is useful as a quick real-time monitoring tool for the COVID-19 pandemic. It was designed to be used by humans: both researchers and non-researchers.