NLSIG-COVID19Lab: A modern logistic-growth tool (nlogistic-sigmoid) for descriptively modelling the dynamics of the COVID-19 pandemic process

Matlab Submitted 16 December 2020Published 06 April 2021
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Editor: @majensen (all papers)
Reviewers: @agahkarakuzu (all reviews), @kakearney (all reviews)

Authors

Oluwasegun A. Somefun (0000-0002-5171-8026), Kayode F. Akingbade, Folasade M. Dahunsi

Citation

Somefun et al., (2021). NLSIG-COVID19Lab: A modern logistic-growth tool (nlogistic-sigmoid) for descriptively modelling the dynamics of the COVID-19 pandemic process. Journal of Open Source Software, 6(60), 3002, https://doi.org/10.21105/joss.03002

@article{Somefun2021, doi = {10.21105/joss.03002}, url = {https://doi.org/10.21105/joss.03002}, year = {2021}, publisher = {The Open Journal}, volume = {6}, number = {60}, pages = {3002}, author = {Oluwasegun A. Somefun and Kayode F. Akingbade and Folasade M. Dahunsi}, title = {`NLSIG-COVID19Lab`: A modern logistic-growth tool (nlogistic-sigmoid) for descriptively modelling the dynamics of the COVID-19 pandemic process}, journal = {Journal of Open Source Software} }
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COVID-19 logistic function machine learning neural networks optimization regression epidemiology

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ISSN 2475-9066