Exploring multivariate linear regression methods for the prediction of total phenolic content in standard American lager beers using synchronous fluorescence spectroscopy fused data

Rodrigues, Alexander de P.; Gois, Jefferson Santos de; Costa, Marina Araujo João Lopes da; Silva, Camila S. da; Xavier, Vinicius Layter; Luna, Aderval S.

doi:10.1016/j.chemolab.2020.104168

Cited by 5 publications

(1 citation statement)

References 28 publications

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“…The relative bias "BIAS", indicates the average trend of the simulated data to be greater or inferior than the observed data, reflecting the systematic predictive model for the under-or overestimation (Rodrigues et al, 2020) of the dependent variable. Zero values indicate a perfect fit, its calculation is obtained as (Büchele et al, 2019): (13) where:…”

Section: Linear Regression Model Validationmentioning

confidence: 99%

Empirical Model for Estimating the Ecological Footprint in Ecuador Based on Demographic, Economic and Environmental Indicators

Yupa¹,

Depablos²,

Cueva³

et al. 2021

J. Ecol. Eng.

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In this study, the existence of long-term trends in ecological footprint (EF), biocapacity, GDP, population and CO 2 emissions for the period of 1961-2016, and their effect on the demographic, economic and biocapacity indicators on Ecuador's EF were identified. The long-term trend analysis was performed by means of a Mann-Kendall, nonparametric test. The development of a multiple linear regression model of the EF considers the population, GDP, biocapacity and its logarithmic transformations as returners. A backward removal method was used, in conjunction with the Akaike criterion (AIC) to validate the most suitable model in terms of adjusted-R 2 , NSE, BIAS and RMSE, respectively. The results show significant changes (p<0.01) of the annual EF increase (0.015 hag), total population (216.375 inhabitants), GDP ($1.2 billion) and CO 2 emissions (718.6 kt). However, the biocapacity has been declining (0.086 hag) at a faster rate than the ecological footprint. In other words, in a few years, the country will be facing ecological deficits. As for the empirical model of EF, it can be observed that for every increase of inhabitant's units, the natural logarithm of biocapacity and GDP will increase EF by 1.68x10 -7 , 4.84 and 0.905 gha, respectively. Moreover, EF will be decreased by 0.6 gha each time the biocapacity increases by one gha unit. Finally, this robust and easy-to-interpret model allows accurate EF predictions that can be a tool to better forecast the environmental trends, allowing the development of sustainable projects in Ecuador.

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Section: Linear Regression Model Validationmentioning

confidence: 99%