Search results for "multivariate"
showing 10 items of 1520 documents
Characterization of the alcoholic fraction of vegetable oils by derivatization with diphenic anhydride followed by high-performance liquid chromatogr…
2008
Abstract Aliphatic and triterpene alcohols present in vegetable oils have been identified and determined by HPLC using UV–vis and MS detection after previous derivatization with diphenic anhydride. The alcoholic fraction was obtained by saponification, extraction and TLC (according to the European Union official procedure). Derivatization was performed in tetrahydrofuran in the presence of suspended grinded urea, which increases the reaction rate and yield. Derivatized extracts were chromatographed on a C8 column using gradient elution with acetonitrile/water mixtures containing 0.1% acetic acid, with UV–vis followed by negative-ion mode MS detection. Using linear discriminant analysis of t…
Multivariate statistical analysis for water demand modelling: implementation, performance analysis, and comparison with the PRP model
2015
Water demand is the driving force behind hydraulic dynamics in water distribution systems. Consequently, it is crucial to accurately estimate the actual water use to develop reliable simulation models. In this study, copula-based multivariate analysis was proposed and used for demand prediction for a given return period. The analysis was applied to water consumption data collected in the water distribution network of Palermo (Italy). The approach produced consistent demand patterns and could be a powerful tool when coupled with water distribution network models for design or analysis problems. The results were compared with those obtained using a classical water demand model, the Poisson re…
Multivariate Statistical Analysis for Water Demand Modeling
2014
The actual level of water demand is the driving force behind the hydraulic dynamics in water distribution systems. Consequently, it is crucial to estimate it as accurately as possible in order to result in reliable simulation models. In this paper, a copula-based multivariate analysis has been proposed and used for demand prediction for given return period. The analysis is applied to water consumption data collected in the water distribution network of Palermo (Italy). The approach showed to produce consisted demand patterns and to be a powerful tool to be coupled with water distribution network models for design or analysis problems. (C) 2014 Published by Elsevier Ltd.
A Multivariate Analysis of HIV-1 Protease Inhibitors and Resistance Induced by Mutation
2005
This paper describes the use of the multivariate statistical procedure principal component analysis as a tool to explore the inhibitory activity of classes of protease inhibitors (PIs) against HIV-1 viruses (wild type and more-frequent single mutants, V82A, V82F, and I84V) and against protease enzymes. The analysis of correlations between biological activity and molecular descriptors or similarity indexes allowed a reliable classification of the 51 derivatives considered in this study. The best results were obtained in the case of the I84V mutant for which a high number of predictions was achieved. On this basis, this statistical approach is proposed as a reliable method for the prediction …
“Anti-Bayesian” flat and hierarchical clustering using symmetric quantiloids
2017
A myriad of works has been published for achieving data clustering based on the Bayesian paradigm, where the clustering sometimes resorts to Naive-Bayes decisions. Within the domain of clustering, the Bayesian principle corresponds to assigning the unlabelled samples to the cluster whose mean (or centroid) is the closest. Recently, Oommen and his co-authors have proposed a novel, counter-intuitive and pioneering PR scheme that is radically opposed to the Bayesian principle. The rational for this paradigm, referred to as the “Anti-Bayesian” (AB) paradigm, involves classification based on the non-central quantiles of the distributions. The first-reported work to achieve clustering using the A…
The Multilevel Model in the Computer-Generated Appraisal: A Case in Palermo
2017
The construction of a mass appraisal model requires the preliminary study of the real estate market, the sampling of sold properties, the development of a forecasting model and the verification of the appraisal results. They are generally computerised methods, that work with geo-referenced data. This experimental work has proceeded to build a mass appraisal model, collecting a data sample of sales of apartments in the city of Palermo, in the five years 2008–2012, using a multivariate statistical model (multilevel), testing the results and providing the operating applications in a scheme of online real estate valuations.
Statistical validation of simulation models of observable systems
2003
In this paper, for validating computer simulation models of real, observable systems, an uniformly most powerful invariant (UMPI) test is developed from the generalized maximum likelihood ratio (GMLR). This test can be considered as a result of a new approach to solving the Behrens‐Fisher problem when covariance matrices of two multivariate normal populations (compared with respect to their means) are different and unknown. The test is based on invariant statistic whose distribution, under the null hypothesis, does not depend on the unknown (nuisance) parameters. The sample size and threshold of the UMPI test are determined from minimization of the weighted sum of the model builder's risk a…
Preadolescent EFL learners’ self-efficacy expectancies before and after completion of a grammar task: Multivariate analyses of grade level, gender, a…
2020
Learners’ task-specific self-efficacy expectancies have gained increased attention in the EFL context. Across various competence areas they have been demonstrated to substantially affect learners’ motivation, learning approach, and performance. However, certain research gaps still exist – particularly concerning younger learners’ grammar self-efficacy. Furthermore, though conceptually assumed to play an essential role in learners’ self-efficacy formation and calibration accuracy, little is empirically known about task completion effects. The same applies to the role of grade level and gender differences in lower secondary EFL classrooms. Against this background, the present study addressed …
The Hydrothermal System of Solfatara Crater (Campi Flegrei, Italy) Inferred From Machine Learning Algorithms
2019
Two machine learning algorithms were applied to three multivariate datasets acquired at Solfatara volcano. Our aim was to find an unbiased and coherent synthesis among the large amount of data acquired within the crater and along two orthogonal vertical NNE- and WNW-trending cross-sections. The first algorithm includes a new approach for a soft K-means clustering based on the use of the silhouette index to control the color palette of the clusters. The second algorithm which uses the self-organizing maps incorporates an alternative method for choosing the number of nodes of the neural network which aims to avoid the need for downstream clustering of the results of the classification. Both m…
Muscle Cross-Sectional Area and Structural Bone Strength Share Genetic and Environmental Effects in Older Women
2009
The purpose of this study was to estimate to what extent muscle cross-sectional area of the lower leg (mCSA) and tibial structural strength are influenced by common and trait-specific genetic and environmental factors. pQCT scans were obtained from both members of 102 monozygotic (MZ) and 113 dizygotic (DZ) 63- to 76-yr-old female twin pairs to estimate the mCSA of the lower leg, structural bending strength of the tibial shaft (BSIbend), and compressive strength of the distal tibia (BSIcomp). Quantitative genetic models were used to decompose the phenotypic variances into common and trait-specific additive genetic (A), shared environmental (C), and individual environmental (E) effects. The …