Search results for "linear regression"

Retrieval of coloured dissolved organic matter with machine learning methods

2017

The coloured dissolved organic matter (CDOM) concentration is the standard measure of humic substance in natural waters. CDOM measurements by remote sensing is calculated using the absorption coefficient (a) at a certain wavelength (e.g. 440nm). This paper presents a comparison of four machine learning methods for the retrieval of CDOM from remote sensing signals: regularized linear regression (RLR), random forest (RF), kernel ridge regression (KRR) and Gaussian process regression (GPR). Results are compared with the established polynomial regression algorithms. RLR is revealed as the simplest and most efficient method, followed closely by its nonlinear counterpart KRR.

Design Of Experiments for the optimization the process parameters of thixotropic aluminum alloy

2006

The success of the thixoforming process depends on the possibility to confer to material, when it is found in the semisolid state, a microstructure characterized by globular particles of solid phase surrounded by a continuous film of liquid phase; such microstructure is obtainable through particular thermo-mechanical treatments. In the present research, in order to optimize the influence of process parameters in the step in which the thixotropic properties are conferred to the AA7075 aluminum alloy, the statistic technique of the Design Of Experiments (DOE) has been used. The advantages in the application of such technique are expressible in terms of reduction the times of development of pr…

Determination of insolubles in diesel lubricating oil by FIA-visible spectrometry

2003

Insolubles determination is one of the parameters usually recommended to evaluate the residual life of oil because their presence at elevated levels in diesel lubricating oil changes the viscosity, prematurely clogs filters and is one of the major factors in causing abrasive engine wear. The proposed method employs visible spectrophotometric detection in association with flow injection analysis. The results obtained by this method were compared with the ones obtained by Fourier transform infrared spectrometry (FT-IR) since this is the most employed method for insolubles determination. The proposed method presented a linear response from 0 to 3% (w/w) of insolubles in pentane (ASTM D-893). T…

Functional linear regression with functional rensponse application to prediction of electricity consumption

2008

Functional linear regression model linking observations of a functional response variable with measurements of an explanatory functional variable is considered. The slope function is estimated with a tensor product splines. Some computational issues are addressed by means of a simulation study. This model serves to analyze a real data set concerning electricity consumption in Sardinia. The interest lies in predicting either incoming weekend or incoming weekdays consumption curves if actual weekdays consumption is known.

Applicability of the log MM - √D relationship to linear polyacrylamide gradient gel electrophoresis under a wide range of experimental conditions

1982

Recently we reported about a linear correlation between the logarithm of the size of native proteins (log mol mass or log Stokes' radius) and the square root of their migration distance (- √D) in linear polyacrylamide (PAA)-gradient gels (G. M. Rothe and H. Purkhanbaba, Electrophoresis 1982, 3, 33–42). The linearity between log MM and √D is not subject to time using homogeneous buffers in electrophoresis, no matter how the constants of the corresponding regression lines, slope and intercept change as a function of time. The realiability of this correlction has been re-examined with 0.7 mm thin gel plates and extending the time of electrophoresis under non-denaturating conditions from 2 to 9…

THE RELATIONSHIP BETWEEN CIVIC FACTORS AND THE MIDDLE PROFICIENCY LEVEL OF CIVIC KNOWLEDGE

2021

This study explores the relationship between civic and citizenship factors and the middle proficiency level of students’ civic knowledge in the Baltic countries: Estonia, Latvia and Lithuania. The study uses large scale data from the IEA’s International Civic and Citizenship Education Study (ICCS) 2016. According to ICCS 2016, 39% of students from the three Baltic countries and only 26% of students from the Nordic countries had a middle proficiency level of civic knowledge. This middle proficiency level is the largest group in comparison to other levels. Therefore, the study aims to recognise the differences between the highest and lowest achievements in the middle proficiency level of civi…

2014

Introduction: Many studies examine gene expression data that has been obtained under the influence of multiple factors, such as genetic background, environmental conditions, or exposure to diseases. The interplay of multiple factors may lead to effect modification and confounding. Higher order linear regression models can account for these effects. We present a new methodology for linear model selection and apply it to microarray data of bone marrow-derived macrophages. This experiment investigates the influence of three variable factors: the genetic background of the mice from which the macrophages were obtained, Yersinia enterocolitica infection (two strains, and a mock control),and treat…

Multivariate versus univariate calibration for nonlinear chemiluminescence data

2001

Abstract Multivariate calibration is tested as an alternative to model chromium(III) concentration versus chemiluminescence registers obtained from luminol-hydrogen peroxide reaction. The multivariate calibration approaches included have been: conventional linear methods (principal component regression (PCR) and partial least squares (PLS)), nonlinear methods (nonlinear variants and variants of locally weighted regression) and linear methods combined with variable selection performed in the original or in the transformed data (stepwise multiple linear regression procedure). Both the direct and inverse univariate approaches have been also tested. The use of a double logarithmic transformatio…

The Norm-P Estimation of Location, Scale and Simple Linear Regression Parameters

1989

A new formulation of the exponential power distributions is used as general error model to describe long-tailed and short -tailed distributed errors. The proposed estimators of the location, scale and structure parameters of this general model and of the simple linear regression parameters when the response variable is affected by errors coming from the previous model should be used instead of robust estimators and against the practice of rejecting outlying observations. Two Monte Carlo simulations prove the good properties of these norm-p estimators.

Model averaging estimation of generalized linear models with imputed covariates

2015

a b s t r a c t We address the problem of estimating generalized linear models when some covariate values are missing but imputations are available to fill-in the missing values. This situation generates a bias-precision trade- off in the estimation of the model parameters. Extending the generalized missing-indicator method proposed by Dardanoni et al. (2011) for linear regression, we handle this trade-off as a problem of model uncertainty using Bayesian averaging of classical maximum likelihood estimators (BAML). We also propose a block model averaging strategy that incorporates information on the missing-data patterns and is computationally simple. An empirical application illustrates our…