Search results for "least squares"
showing 10 items of 268 documents
Fourier transform infrared spectrometric strategies for the determination of Buprofezin in pesticide formulations
2002
Abstract Two different strategies for Buprofezin determination, an off-line extraction and stopped-flow determination and an automated procedure, based on the on-line extraction of Buprofezin samples with chloroform and flowing action analysis–fourier transform infrared (FIA–FT-IR) spectrometric measurement of the extracts, have been developed. For the treatment of the off-line extraction mode, data a three-factor partial least squares (PLSs) calibration was developed, using the region from 1465.7 to 1342.3 cm−1 with a single point baseline defined at 2051.9 cm−1 and based on the use of chloroform solutions of Buprofezin. The method provides a R.S.D. On the other hand, the recommended FIA m…
Chemical Element Levels as a Methodological Tool in Forensic Science
2014
The aim of the present study was to define a methodological strategy for understanding how post- mortem degradation in bones caused by the environment affects different skeletal parts and for selecting better preserved bone samples, employing rare earth elements (REEs) analysis and multivariate statistics. To test our methodological proposal the samples selected belong to adult and young individuals and were obtained from the Late Roman Necropolis of c/Virgen de la Misericordia located in Valencia city centre (Comunidad Valenciana, Spain). Therefore, a method for the determination of major elements, trace elements and REEs in bone remains has been developed employing Inductively-Coupled Pla…
Is R&D Enough to Take Advantage From External Knowledge?: Focusing on Coordination Mechanisms
2014
The purpose of this paper is to analyze the role of research and development (R&D) and coordination mechanisms (such as decentralization in decision-making and formalization of organizational processes) in the transformation of external knowledge into innovation results. We use survey data for performing standard ordinary least squares regressions in a representative sample of firms from the Spanish Ceramic Tile Industry. The results suggest that R&D is an important moderator influencing the relationship between acquiring external knowledge and innovation outcomes. Second, formalization tends to have a detrimental effect in the transformation of external knowledge into innovation outputs. 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.
Emerging Economies’ Institutional Quality and International Competitiveness: A PLS-SEM Approach
2021
The home country’s institutional framework determines the capacity to compete in the global arena. This paper discusses the linkage between institutional quality (IQ) and international competitiveness (IC). We measured institutions’ quality in emerging economies through the use of selected indicators between 2007–2017. To evaluate the proposed IQ constructs and their relationship with IC, we applied partial least squares – structural equation modeling (PLS-SEM) analysis. The model outcomes suggest that political and lack of systemic conditions have a significant and negative effect on international competitiveness, while science, technology, engineering and mathematics (STEM) resource condi…
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…
Weighted-average least squares estimation of generalized linear models
2018
The weighted-average least squares (WALS) approach, introduced by Magnus et al. (2010) in the context of Gaussian linear models, has been shown to enjoy important advantages over other strictly Bayesian and strictly frequentist model averaging estimators when accounting for problems of uncertainty in the choice of the regressors. In this paper we extend the WALS approach to deal with uncertainty about the specification of the linear predictor in the wider class of generalized linear models (GLMs). We study the large-sample properties of the WALS estimator for GLMs under a local misspecification framework that allows the development of asymptotic model averaging theory. We also investigate t…
Semisupervised nonlinear feature extraction for image classification
2012
Feature extraction is of paramount importance for an accurate classification of remote sensing images. Techniques based on data transformations are widely used in this context. However, linear feature extraction algorithms, such as the principal component analysis and partial least squares, can address this problem in a suboptimal way because the data relations are often nonlinear. Kernel methods may alleviate this problem only when the structure of the data manifold is properly captured. However, this is difficult to achieve when small-size training sets are available. In these cases, exploiting the information contained in unlabeled samples together with the available training data can si…
Comparative Study of Several Machine Learning Algorithms for Classification of Unifloral Honeys
2021
Unifloral honeys are highly demanded by honey consumers, especially in Europe. To ensure that a honey belongs to a very appreciated botanical class, the classical methodology is palynological analysis to identify and count pollen grains. Highly trained personnel are needed to perform this task, which complicates the characterization of honey botanical origins. Organoleptic assessment of honey by expert personnel helps to confirm such classification. In this study, the ability of different machine learning (ML) algorithms to correctly classify seven types of Spanish honeys of single botanical origins (rosemary, citrus, lavender, sunflower, eucalyptus, heather and forest honeydew) was investi…
Detecting crop water status in mature olive orchards using vegetation spectral measurements.
2014
Full spectral measurements (350–2500 nm) at tree canopy and leaf levels and the corresponding leaf water potentials (LWP) were acquired in an olive grove of Sicily, at different hours of the day, during summer season 2011. The main objective of the work was to assess, on the basis of the experimental data-set, two different approaches to detect crop water status in terms of LWP. Specifically, using existing families of Vegetation Indices (VIs) and applying Partial Least Squares Regression (PLSR) were optimised and tested. The results indicated that a satisfactory estimation of LWP at tree canopy and leaf levels can be obtained using vegetation indices based on the near infrared–shortwave in…