Parameter Estimation and Statistical Methods

Ros, Simoní Da; Schwaab, Marcio; Pinto, José Carlos

doi:10.1016/b978-0-12-409547-2.13918-6

Cited by 11 publications

(19 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This test determines whether there is a significant difference between the models when the confidence is 95% and (NP -N pars ) degrees of freedom are considered. If the F value is within the maximum and minimum limits of Fisher's F distribution (F max and F min ), the hypothesis of statistical equality between the models is supported [37].…”

Section: Classificationmentioning

confidence: 99%

Characterization and use of a lignin sample extracted from Eucalyptus grandis sawdust for the removal of methylene blue dye

Cemin

Ferrarini

Poletto

et al. 2021

International Journal of Biological Macromolecules

View full text Add to dashboard Cite

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

show abstract

Section: Classificationmentioning

confidence: 99%

Characterization and use of a lignin sample extracted from Eucalyptus grandis sawdust for the removal of methylene blue dye

Cemin

Ferrarini

Poletto

et al. 2021

International Journal of Biological Macromolecules

View full text Add to dashboard Cite

show abstract

“…(2.8) was performed using a hybrid optimisation method implemented in Fortran 90, in which the Particle Swarm Optimization algorithm [36] is used in the initial phase of minimisation [37,38]. The best estimate of the point of the minimum is used as an initial guess for a second estimation round, using the Gauss-Newton method [31,39].…”

Section: Parameter Estimationmentioning

confidence: 99%

“…The fitting of this model to the thermograms obtained at the different heating rates also resulted in high linear correlation coefficients between experimental data and model predictions, always higher than 0.99, indicating a good fit. However, the comparison of the model prediction variance between the different models, that is, the model containing one degradation step and the model containing two consecutive degradation steps, with the help of the standard test-F [31,39,40], indicates a significant loss of quality fit when only one degradation step is considered. Thus, the modelling approach involving two consecutive reaction steps seems to be the most promising to represent the pyrolysis of EGDMA crosslinked PMMA.…”

Section: The One Degradation Step Modelmentioning

confidence: 99%

“…However, the crosslinking effect on the PMMA depolymerisation kinetics has not been fully characterised, although some studies indicate a higher thermal stability associated to crosslinked PMMA [25]. In addition, it is important to note that even though TGA experiments are a powerful tool for kinetic characterisation of chemical reactions [29], kinetics parameters and the evaluation of their statistical significance are scarcely reported [7,25,28], impairing the discrimination among reaction mechanisms [30,31].…”

Section: Introductionmentioning

confidence: 99%

“…The evaluation of the model adequacy was performed by comparing models prediction variance, m  , as defined in accordance to Eq. (2.9), with the help of the standard F-test[31,40]. In Eq.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Modelling the chemical recycling of crosslinked poly (methyl methacrylate): Kinetics of depolymerisation

Ros

Braido

Castro

et al. 2019

Journal of Analytical and Applied Pyrolysis

Self Cite

View full text Add to dashboard Cite

Whereas increasing plastic solid waste production constitutes one of the main challenges of modern society, mainly due to the lack of suitable recycling technologies, chemical recycling represents an attractive solution for the conversion of plastic solid waste into valuable chemical intermediates. Herein, a kinetic model for the pyrolysis of a dental industry waste, ethylene glycol dimethacrylate (EGDMA) crosslinked poly (methyl methacrylate) (PMMA), is presented for the first time. Kinetics parameters and their statistical significance have been estimated from eight non-isothermal thermogravimetric analysis (TGA) experiments with heating rates varying between 5 and 50 °C•min-1 by using nonlinear regression. Our analysis indicates that the mechanism of depolymerisation of EGDMA crosslinked PMMA is likely to involve a consecutive reaction pathway involving two steps. The developed kinetic modelcontaining five kinetic parameters only-was able to predict well all non-isothermal TGA runs, and was validated against isothermal TGA experiments at 400 °C.

show abstract

Sparse multivariate regression with missing values and its application to the prediction of material properties

Teramoto

Hirose

2021

Numerical Meth Engineering

View full text Add to dashboard Cite

In the field of materials science and engineering, statistical analysis and machine learning techniques have recently been used to predict multiple material properties from an experimental design. These material properties correspond to response variables in the multivariate regression model. In this study, we conduct a penalized maximum likelihood procedure to estimate model parameters, including the regression coefficients and covariance matrix of response variables. In particular, we employ l 1 -regularization to achieve a sparse estimation of The regression coefficients and inverse covariance matrix of response variables.In some cases, there may be a relatively large number of missing values in the response variables, owing to the difficulty of collecting data on material properties. We therefore propose a method that incorporates a correlation structure among the response variables into a statistical model to improve the prediction accuracy under the situation with missing values. The expectation maximization algorithm is also constructed, which enables application to a dataset with missing values in the responses. We apply our proposed procedure to real data consisting of 22 material properties.

show abstract

Parameter Estimation and Statistical Methods

Cited by 11 publications

References 43 publications

Characterization and use of a lignin sample extracted from Eucalyptus grandis sawdust for the removal of methylene blue dye

Characterization and use of a lignin sample extracted from Eucalyptus grandis sawdust for the removal of methylene blue dye

Modelling the chemical recycling of crosslinked poly (methyl methacrylate): Kinetics of depolymerisation

Sparse multivariate regression with missing values and its application to the prediction of material properties

Contact Info

Product

Resources

About