Search results for " Least squares"
showing 10 items of 223 documents
Identification of compounds responsible for the odorant properties of aromatic caramel
2012
Aromatic caramel results from the heat treatment of sugars under specific temperature conditions. Because of its richness in aroma compounds and its pleasant organoleptic properties, caramel is widely used in the food industry. However, the composition of the volatile odorant fraction has not been completely elucidated. The aim of this work was thus to identify the volatile odorant compounds responsible for caramel sensory properties using a multivariate statistical technique. Four aromatic caramels differing in terms of their carbohydrate composition and cooking process were chosen. Odorant compounds were screened by gas chromatography–olfactometry (GC-O) and identified by GC–mass spectrom…
Determination of lecithin and soybean oil in dietary supplements using partial least squares-Fourier transform infrared spectroscopy.
2008
Lecithin and soybean oil in dietary supplements were determined by Fourier transform infrared spectrometry transmission measurements in dichloromethane in combination with a partial least squares (PLS) regression. Two different PLS models were developed, using 16 synthetic mixtures of analytes in dichloromethane, making measurements in the spectral range from 931.8 to 1252.3 cm(-1) for lecithin and from 911.4 to 1246.9 cm(-1) and 1695.3 to 1774.5 cm(-1) for soybean oil. Seven products from the Spanish market with lecithin concentrations between 21.1% and 99.1% and soybean oil concentrations between 0% and 37.2% were analyzed by the proposed method and the data was compared to a chromatograp…
Simultaneous Kinetic Determination of Carbamate Pesticides after Derivatization withp-Aminophenol by Using Partial Least Squares
1996
Abstract A method has been developed for the fast spectrophotometric determination of propoxur, carbaryl, and ethiofencarb in water samples using injection analysis in the stopped-flow mode. The method is based on the reaction between p -aminophenol and the phenolic compounds obtained from the pesticides, after a previous hydrolysis with 0.05 M NaOH at room temperature for 15 min. The partial least-squares treatment of the spectrophotometry kinetic data provides a simultaneous determination of the three carbamate pesticides assayed with a relative accuracy error lower than 5% in complex mixtures also containing formetanate, which is only partially hydrolyzed under the experimental condition…
Prediction of soil texture distributions using VNIR-SWIR reflectance spectroscopy
2013
Abstract Reflectance spectroscopy provides an alternate method to non-destructively characterize key soil properties. Different approaches, including chemometrics techniques or specific absorption features, have been proposed to estimate soil properties from visible and near-infrared (VNIR, 400-1200 nm) and shortwave infrared (SWIR, 1200-2500 nm) reflectance domains. The main goal of this study was to test the performance of two distinct methods for soil texture estimation by VNIR-SWIR reflectance measurements: i) the Continuum Removal (CR) technique that was used to correlate specific spectral absorption features with clay, silt and sand content, and ii) the Partial Least-Squares Regressio…
Power estimation for non-standardized multisite studies
2016
A concern for researchers planning multisite studies is that scanner and T1-weighted sequence-related biases on regional volumes could overshadow true effects, especially for studies with a heterogeneous set of scanners and sequences. Current approaches attempt to harmonize data by standardizing hardware, pulse sequences, and protocols, or by calibrating across sites using phantom-based corrections to ensure the same raw image intensities. We propose to avoid harmonization and phantom-based correction entirely. We hypothesized that the bias of estimated regional volumes is scaled between sites due to the contrast and gradient distortion differences between scanners and sequences. Given this…
Missing Data
2009
In this chapter, we deal with the problem of missing data in principal component analysis (PCA) and partial least squares (PLS) methods. First, we review several statistical methods proposed in the literature for handling missing data. Both single and multiple imputation (MI) methods are studied and compared using simulated data. After this, we particularize the missing data problem for building and exploiting multivariate calibration models. Several approaches proposed in the literature are introduced and their performance compared based on several real data sets.
A Comparison of Advanced Regression Algorithms for Quantifying Urban Land Cover
2014
Quantitative methods for mapping sub-pixel land cover fractions are gaining increasing attention, particularly with regard to upcoming hyperspectral satellite missions. We evaluated five advanced regression algorithms combined with synthetically mixed training data for quantifying urban land cover from HyMap data at 3.6 and 9 m spatial resolution. Methods included support vector regression (SVR), kernel ridge regression (KRR), artificial neural networks (NN), random forest regression (RFR) and partial least squares regression (PLSR). Our experiments demonstrate that both kernel methods SVR and KRR yield high accuracies for mapping complex urban surface types, i.e., rooftops, pavements, gras…
Specifications of model development
2016
Chapter 4 goes into detail with the specifications of the model and model validation. Why Partial Least Squares (PLS), a structural equation modelling approach, is chosen as the method for model testing is explained in section 4.1, while 4.2 describes the survey conducted to collect data for model testing. Section 4.3 goes into detail with the PLS approach, its theoretical background and its application to the research question, before section 4.4 outlines the necessary operationalisation of the constructs introduced in chapter 3.
Fast Implementation of Double-coupled Nonnegative Canonical Polyadic Decomposition
2019
Real-world data exhibiting high order/dimensionality and various couplings are linked to each other since they share some common characteristics. Coupled tensor decomposition has become a popular technique for group analysis in recent years, especially for simultaneous analysis of multi-block tensor data with common information. To address the multiblock tensor data, we propose a fast double-coupled nonnegative Canonical Polyadic Decomposition (FDC-NCPD) algorithm in this study, based on the linked CP tensor decomposition (LCPTD) model and fast Hierarchical Alternating Least Squares (Fast-HALS) algorithm. The proposed FDCNCPD algorithm enables simultaneous extraction of common components, i…
Flexible Estimation of Heteroskedastic Stochastic Frontier Models via Two-step Iterative Nonlinear Least Squares
2019
Despite its importance, the monotonicity condition is typically overlooked in stochastic frontier analysis. This article illustrates a straightforward and useful method for the estimation of semiparametric stochastic frontier models imposing such constraint and incorporating exogenous inefficiency effects exploiting the scaling property. An iterative estimation algorithm based on nonlinear least squares is developed and the behavior of the proposed procedure is investigated through a set of Monte Carlo experiments comparing its finite sample properties with those of available alternatives. The simulation results highlight very good performance of the new algorithm which outperforms the comp…