Superposition of artificial experimental error onto calculated time series: Construction of in-silico data sets

The data and complementary information presented here are related to the research in the article of “https://doi.org/10.1016/j.cej.2018.01.027; Chem. Eng. J., 342, 41–51 (2018)”, where sets of in-silico data are constructed to show a novel method for parameter estimation in biodiesel production from...

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Autores principales: Heynderickx, Philippe M., Roelant, Raf
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Engineering
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6100261/
https://www.ncbi.nlm.nih.gov/pubmed/30131967
http://dx.doi.org/10.1016/j.dib.2018.05.073
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author Heynderickx, Philippe M.
Roelant, Raf
author_facet Heynderickx, Philippe M.
Roelant, Raf
author_sort Heynderickx, Philippe M.
collection PubMed
description The data and complementary information presented here are related to the research in the article of “https://doi.org/10.1016/j.cej.2018.01.027; Chem. Eng. J., 342, 41–51 (2018)”, where sets of in-silico data are constructed to show a novel method for parameter estimation in biodiesel production from triglycerides (Heynderickx et al., 2018) [1]. In this paper, the method for the used error superposition is explained and in order to ensure a ready reproduction by the reader, this work presents the basic steps for superposition of a normally distributed error via a simple Excel® datasheet file.
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spelling pubmed-61002612018-08-21 Superposition of artificial experimental error onto calculated time series: Construction of in-silico data sets Heynderickx, Philippe M. Roelant, Raf Data Brief Engineering The data and complementary information presented here are related to the research in the article of “https://doi.org/10.1016/j.cej.2018.01.027; Chem. Eng. J., 342, 41–51 (2018)”, where sets of in-silico data are constructed to show a novel method for parameter estimation in biodiesel production from triglycerides (Heynderickx et al., 2018) [1]. In this paper, the method for the used error superposition is explained and in order to ensure a ready reproduction by the reader, this work presents the basic steps for superposition of a normally distributed error via a simple Excel® datasheet file. Elsevier 2018-05-18 /pmc/articles/PMC6100261/ /pubmed/30131967 http://dx.doi.org/10.1016/j.dib.2018.05.073 Text en © 2018 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Engineering
Heynderickx, Philippe M.
Roelant, Raf
Superposition of artificial experimental error onto calculated time series: Construction of in-silico data sets
title Superposition of artificial experimental error onto calculated time series: Construction of in-silico data sets
title_full Superposition of artificial experimental error onto calculated time series: Construction of in-silico data sets
title_fullStr Superposition of artificial experimental error onto calculated time series: Construction of in-silico data sets
title_full_unstemmed Superposition of artificial experimental error onto calculated time series: Construction of in-silico data sets
title_short Superposition of artificial experimental error onto calculated time series: Construction of in-silico data sets
title_sort superposition of artificial experimental error onto calculated time series: construction of in-silico data sets
topic Engineering
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6100261/
https://www.ncbi.nlm.nih.gov/pubmed/30131967
http://dx.doi.org/10.1016/j.dib.2018.05.073
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