Search results for "least square"

showing 10 items of 286 documents

Valuing American Options with Implementation

2017

Master's thesis Business Administration BE501 - University of Agder 2017 This master thesis aims to value American put options by using di erent numerical methods. Three valuation methods for valuing an American put option will be pre- sented and analyzed; the binomial method, the implicit nite di erence method and the least squares Monte Carlo approach (LSM). Due to the opportunity of early exercise of American option contracts, our goal is to nd the optimal exercise strategy which maximizes the payo by using numerical methods. We provide examples of how to implement each algorithm in di erent types of software. A comparison of the methods are given at the end.

VDP::Samfunnsvitenskap: 200::Økonomi: 210Binomial MethodAmerican OptionsVDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420::Algoritmer og beregnbarhetsteori: 422BE501Implicit Finite Dfference MethodLeast Square Monte Carlo
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Feature Selection Approach based on Mutual Information and Partial Least Squares

2014

Feature selection technology can improve the modeling accuracy and reduce model’s complexity, especially for the high dimensional spectral data. Aim at this problem, feature selection approach based on mutual information (MI) and partial least square (PLS) is proposed in this paper. MI values between features and responsible variable are calculated, and the threshold value using to select final features is optimal selected based on PLS algorithm. The numbers of the latent values of the PLS and the threshold value of MI are selected according the modeling performance simultaneously. The experimental results based on the near-infrared spectrum show that the proposed approach has better perfor…

Variable (computer science)Threshold limit valuebusiness.industryPartial least squares regressionGeneral EngineeringPattern recognitionFeature selectionHigh dimensionalArtificial intelligenceMutual informationSpectral databusinessMathematicsAdvanced Materials Research
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Evaluation of the effect of chance correlations on variable selection using Partial Least Squares -Discriminant Analysis

2013

Variable subset selection is often mandatory in high throughput metabolomics and proteomics. However, depending on the variable to sample ratio there is a significant susceptibility of variable selection towards chance correlations. The evaluation of the predictive capabilities of PLSDA models estimated by cross-validation after feature selection provides overly optimistic results if the selection is performed on the entire set and no external validation set is available. In this work, a simulation of the statistical null hypothesis is proposed to test whether the discrimination capability of a PLSDA model after variable selection estimated by cross-validation is statistically higher than t…

Variable selectionESTADISTICA E INVESTIGACION OPERATIVAFeature selectionChance correlationsAnalytical ChemistrySet (abstract data type)ResamplingPartial least squares regressionStatisticsHumansMetabolomicsLeast-Squares AnalysisSelection (genetic algorithm)ProbabilityGaucher DiseaseModels StatisticalChemistryDiscriminant AnalysisReproducibility of ResultsPartial Least Squares-Discriminant Analysis (PLSDA)Linear discriminant analysisVariable (computer science)Null hypothesisAlgorithmsSoftware
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An approach to identify new antihypertensive agents using Thermolysin as model: In silico study based on QSARINS and docking

2019

Thermolysin is a bacterial proteolytic enzyme, considered by many authors as a pharmacological and biological model of other mammalian enzymes, with similar structural characteristics, such as angiotensin converting enzyme and neutral endopeptidase. Inhibitors of these enzymes are considered therapeutic targets for common diseases, such as hypertension and heart failure. In this report, a mathematical model of Multiple Linear Regression, for ordinary least squares, and genetic algorithm, for selection of variables, are developed and implemented in QSARINS software, with appropriate parameters for its fitting. The model is extensively validated according to OECD standards, so that its robust…

Virtual screeningChemistry(all)StereochemistryGeneral Chemical EngineeringIn silicoThermolysinComputational biology01 natural sciencesDockinglcsh:ChemistryThermolysinLinear regressionVirtual screening010405 organic chemistryChemistryProteolytic enzymesGeneral Chemistry0104 chemical sciences010404 medicinal & biomolecular chemistrylcsh:QD1-999Docking (molecular)Multiple Linear RegressionQSARINSOrdinary least squaresOutlierChemical Engineering(all)AntihypertensiveArabian Journal of Chemistry
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Partial least squares-near infrared determination of pesticides in commercial formulations

2007

Abstract A solvent free, fast and environmentally friendly near infrared-based methodology (NIR) was developed for pesticide determination in commercially available formulations. This methodology was based on the direct measurement of the diffuse reflectance spectra of solid samples and a multivariate calibration model (partial least squares, PLS) to determine the active principle concentration in commercial formulations. The PLS calibration set was built on using the spiked samples by mixing different amounts of pesticide standards and powdered samples. Buprofezin, Diuron and Daminozide were used as test analytes. Concentration of Buprofezin in the samples was calculated employing a 4-fact…

Waste generationRoot mean squareAnalytechemistry.chemical_compoundChromatographyChemistryPartial least squares regressionNear-infrared spectroscopyCalibrationAnalytical chemistryDaminozidePesticideSpectroscopyVibrational Spectroscopy
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Quantitative Transfer Function Approaches in Palaeoclimatic Reconstruction Using Quaternary Ostracods

2012

Abstract Quantifying (palaeo-)environmental changes is a key challenge for aquatic biological proxies, but the number of published transfer functions is increasing rapidly for the main palaeoecologically relevant groups such as diatoms and chironomids, and several transfer functions have also been developed during the past decades based on ostracod findings. The main environmental variables influencing the species assemblage composition in ostracod training sets are specific ion concentrations or ratios, salinity, water temperature and/or water depth. The available transfer functions and training sets are globally scattered, but often regionally restricted in their application. The most com…

Water depthPaleontologybiologyCalibration (statistics)Water temperatureOstracodPartial least squares regressionQuaternarybiology.organism_classificationTransfer functionGeology
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Fast nonstationary preconditioned iterative methods for ill-posed problems, with application to image deblurring

2013

We introduce a new iterative scheme for solving linear ill-posed problems, similar to nonstationary iterated Tikhonov regularization, but with an approximation of the underlying operator to be used for the Tikhonov equations. For image deblurring problems, such an approximation can be a discrete deconvolution that operates entirely in the Fourier domain. We provide a theoretical analysis of the new scheme, using regularization parameters that are chosen by a certain adaptive strategy. The numerical performance of this method turns out to be superior to state-of-the-art iterative methods, including the conjugate gradient iteration for the normal equation, with and without additional precondi…

Well-posed problemDeblurringMathematical optimizationIterative methodApplied MathematicsRegularization (mathematics)Computer Science ApplicationsTheoretical Computer ScienceTikhonov regularizationConjugate gradient methodSignal ProcessingApplied mathematicsDeconvolutionMathematical PhysicsLinear least squaresMathematics
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Multivariate Methods Based Soft Measurement for Wine Quality Evaluation

2014

Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2014/740754 Open Access Soft measurement is a new, developing, and promising industry technology and has been widely used in the industry nowadays. This technology plays a significant role especially in the case where some key variables are difficult to be measured by traditional measurement methods. In this paper, the quality of the wine is evaluated given the wine physicochemical indexes according to multivariate methods based soft measurement. The multivariate methods used in this paper include ordinary least squares regression (OLSR), principal c…

WineMeasurement methodMultivariate statisticsArticle Subjectlcsh:MathematicsApplied Mathematicsmedia_common.quotation_subjectAnalysis; Applied Mathematicslcsh:QA1-939VDP::Mathematics and natural science: 400::Mathematics: 410::Analysis: 411Ordinary least squaresPartial least squares regressionEconometricsPrincipal component regressionQuality (business)Multivariate statisticalAnalysisMathematicsmedia_commonAbstract and Applied Analysis
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Experimental determination of mode I fracture parameters in orthotropic materials by means of Digital Image Correlation

2020

Abstract The mode I fracture parameters for an orthotropic body are directly calculated from full-field deformation measurements provided by Digital Image Correlation (DIC). Three complementary and direct approaches are evaluated and compared: (i) the determination of the Stress Intensity Factor (SIF) by fitting the displacement field using the analytical expression proposed by Lekhnitskii; (ii) the determination of the J-Integral by using the Energy Domain Integral (EDI) formulation on the raw DIC data; and (iii) the calculation of the J-Integral using the EDI approach on the displacement data fitted using Lekhnitskii’s formulation. A comparative experimental study is performed by testing …

Work (thermodynamics)Digital image correlationMaterials scienceLeast squares fitting/dk/atira/pure/subjectarea/asjc/2600/2604Digital image correlation Energy domain integral J-integral Least squares fitting Stress intensity factorOrthotropic materialDisplacement (vector)Settore ING-IND/14 - Progettazione Meccanica E Costruzione Di MacchineMaterials Science(all)General Materials ScienceStress intensity factorStress intensity factorJ-integralDeformation (mechanics)Applied MathematicsMechanical Engineering/dk/atira/pure/subjectarea/asjc/3100/3104Mathematical analysisDigital image correlationCondensed Matter PhysicsEnergy domain integral/dk/atira/pure/subjectarea/asjc/2500Displacement fieldFracture (geology)/dk/atira/pure/subjectarea/asjc/2200/2210
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Engagement with Travel Web Sites and the Influence of Online Comparative Behaviour

2015

We propose a Web site engagement measurement, and study the influence of potential antecedents and consequences. Utilising partial least squares path modeling, we contrast a model with data obtained from respondents choosing a holiday in the Seychelles, on a Web site capable of tracing online within-page and within-site behaviour.

World Wide WebComputer sciencePartial least squares path modelingContrast (statistics)Consumer researchTracingWeb site
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