Search results for "QA273-280"

showing 9 items of 9 documents

The Raising Factor, That Great Unknown. A Guided Activity for Undergraduate Students

2020

In the first years of their economics degree programs, students will face many problems successfully dealing with a range of subjects with quantitative content. Specifically, in the field of statistics, difficulties to reach some basic academic achievements have been observed. Hence, a continuing challenge for statistics teachers is how to make this subject more appealing for students through the design and implementation of new teaching methodologies. The latter tend to follow two main approaches. On the one hand, it is useful for the learning process to propose practical activities that can connect theoretical concepts with real applications in the economic context. On the other hand, we …

Statistics and ProbabilityEconomics educationFace (sociological concept)Economia01 natural sciencesstatistical literacy010104 statistics & probabilityapplications and case studiesComputer softwareMathematics education0101 mathematicsStatistics educationMathematics instructioneducationlcsh:LC8-6691lcsh:Special aspects of education05 social sciences050301 educationexploratory data analysiseconomicsRaising (linguistics)Active learningStatistics Probability and Uncertaintylcsh:Probabilities. Mathematical statisticsPsychologylcsh:QA273-2800503 education
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Wardowski conditions to the coincidence problem

2015

In this article we first discuss the existence and uniqueness of a solution for the coincidence problem: Find p ∈ X such that Tp = Sp, where X is a nonempty set, Y is a complete metric space, and T, S:X → Y are two mappings satisfying a Wardowski type condition of contractivity. Later on, we will state the convergence of the Picard-Juncgk iteration process to the above coincidence problem as well as a rate of convergence for this iteration scheme. Finally, we shall apply our results to study the existence and uniqueness of a solution as well as the convergence of the Picard-Juncgk iteration process toward the solution of a second order differential equation. Ministerio de Economía y Competi…

Statistics and ProbabilityIterative methodsIterative methodCoincidence pointsComplete metric space54H25common fixed pointsConvergence (routing)Applied mathematicsUniquenessMathematicsApplied Mathematics and Statistics47J25lcsh:T57-57.97Applied MathematicsMathematical analysisOrder (ring theory)State (functional analysis)Rate of convergencecoincidence pointsRate of convergenceordinary differential equationsOrdinary differential equationlcsh:Applied mathematics. Quantitative methodsCommon fixed pointsiterative methodslcsh:Probabilities. Mathematical statisticslcsh:QA273-280rate of convergenceFrontiers in Applied Mathematics and Statistics
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A New Nonparametric Estimate of the Risk-Neutral Density with Applications to Variance Swaps

2021

We develop a new nonparametric approach for estimating the risk-neutral density of asset prices and reformulate its estimation into a double-constrained optimization problem. We evaluate our approach using the S\&P 500 market option prices from 1996 to 2015. A comprehensive cross-validation study shows that our approach outperforms the existing nonparametric quartic B-spline and cubic spline methods, as well as the parametric method based on the Normal Inverse Gaussian distribution. As an application, we use the proposed density estimator to price long-term variance swaps, and the model-implied prices match reasonably well with those of the variance future downloaded from the CBOE websi…

FOS: Computer and information sciencesStatistics and ProbabilityVariance swapOptimization problemvariance swapStatistics - ApplicationsFOS: Economics and businessNormal-inverse Gaussian distributiondouble-constrained optimizationpricingEconometricsApplications (stat.AP)Asset (economics)normal inverse Gaussian distributionMathematicsParametric statisticslcsh:T57-57.97Applied MathematicsNonparametric statisticsEstimatorVariance (accounting)lcsh:Applied mathematics. Quantitative methodsPricing of Securities (q-fin.PR)risk-neutral densitylcsh:Probabilities. Mathematical statisticslcsh:QA273-280Quantitative Finance - Pricing of Securities
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Dimension reduction for time series in a blind source separation context using r

2021

Funding Information: The work of KN was supported by the CRoNoS COST Action IC1408 and the Austrian Science Fund P31881-N32. The work of ST was supported by the CRoNoS COST Action IC1408. The work of JV was supported by Academy of Finland (grant 321883). We would like to thank the anonymous reviewers for their comments which improved the paper and package considerably. Publisher Copyright: © 2021, American Statistical Association. All rights reserved. Multivariate time series observations are increasingly common in multiple fields of science but the complex dependencies of such data often translate into intractable models with large number of parameters. An alternative is given by first red…

Statistics and ProbabilitySeries (mathematics)Stochastic volatilityComputer scienceblind source separation; supervised dimension reduction; RsignaalinkäsittelyDimensionality reductionRsignaalianalyysiContext (language use)CovarianceBlind signal separationQA273-280aikasarja-analyysiR-kieliDimension (vector space)monimuuttujamenetelmätBlind source separationStatistics Probability and UncertaintyTime seriesAlgorithmSoftwareSupervised dimension reduction
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On Independent Component Analysis with Stochastic Volatility Models

2017

Consider a multivariate time series where each component series is assumed to be a linear mixture of latent mutually independent stationary time series. Classical independent component analysis (ICA) tools, such as fastICA, are often used to extract latent series, but they don't utilize any information on temporal dependence. Also financial time series often have periods of low and high volatility. In such settings second order source separation methods, such as SOBI, fail. We review here some classical methods used for time series with stochastic volatility, and suggest modifications of them by proposing a family of vSOBI estimators. These estimators use different nonlinearity functions to…

Statistics and ProbabilityAutoregressive conditional heteroskedasticity01 natural sciencesQA273-280GARCH model010104 statistics & probabilityblind source separation0502 economics and businessSource separationEconometricsApplied mathematics0101 mathematics050205 econometrics MathematicsStochastic volatilitymultivariate time seriesApplied MathematicsStatistics05 social sciencesAutocorrelationEstimatorIndependent component analysisHA1-4737nonlinear autocorrelationFastICAStatistics Probability and UncertaintyVolatility (finance)Probabilities. Mathematical statistics
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Tripled Fixed Point Results for T-Contractions on Abstract Metric Spaces

2014

In this paper we introduce the notion of T-contraction for tripled fi xed points in abstract metric spaces and obtain some tripled fi xed point theorems which extend and generalize well-known comparable results in the literature. To support our results, we present an example and an application to integral equations.

QA299.6-433Tripled fixed pointSequentially convergentlcsh:QA299.6-433lcsh:AnalysisSubsequentially convergent.QA273-280T-contractionAbstract metric spaceSettore MAT/05 - Analisi Matematicalcsh:Probabilities. Mathematical statisticslcsh:QA273-280Probabilities. Mathematical statisticsAnalysisInternational Journal of Analysis and Applications
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Existence, uniqueness and comparison results for BSDEs with Lévy jumps in an extended monotonic generator setting

2018

We show existence of a unique solution and a comparison theorem for a one-dimensional backward stochastic differential equation with jumps that emerge from a L\'evy process. The considered generators obey a time-dependent extended monotonicity condition in the y-variable and have linear time-dependent growth. Within this setting, the results generalize those of Royer (2006), Yin and Mao (2008) and, in the $L^2$-case with linear growth, those of Kruse and Popier (2016). Moreover, we introduce an approximation technique: Given a BSDE driven by Brownian motion and Poisson random measure, we consider BSDEs where the Poisson random measure admits only jumps of size larger than $1/n$. We show con…

Comparison theorembackward stochastic differential equationMonotonic function01 natural sciencesLévy processlcsh:QA75.5-76.95010104 statistics & probabilityMathematics::ProbabilityApplied mathematicsUniqueness0101 mathematicsBrownian motionstokastiset prosessitMathematicsLévy processResearch010102 general mathematicsComparison resultsPoisson random measureBackward stochastic differential equationlcsh:Electronic computers. Computer science60H10lcsh:Probabilities. Mathematical statisticscomparison theoremlcsh:QA273-280differentiaaliyhtälötMathematics - ProbabilityGenerator (mathematics)existence and uniquenessProbability, Uncertainty and Quantitative Risk
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Causal Effect Identification from Multiple Incomplete Data Sources: A General Search-Based Approach

2021

Causal effect identification considers whether an interventional probability distribution can be uniquely determined without parametric assumptions from measured source distributions and structural knowledge on the generating system. While complete graphical criteria and procedures exist for many identification problems, there are still challenging but important extensions that have not been considered in the literature. To tackle these new settings, we present a search algorithm directly over the rules of do-calculus. Due to generality of do-calculus, the search is capable of taking more advanced data-generating mechanisms into account along with an arbitrary type of both observational and…

FOS: Computer and information sciencesStatistics and ProbabilityComputer Science - Machine LearningcausalityComputer Science - Artificial IntelligenceHeuristic (computer science)Computer scienceeducationMachine Learning (stat.ML)transportabilitycomputer.software_genre01 natural sciencesMachine Learning (cs.LG)R-kielimissing dataQA76.75-76.765; QA273-280010104 statistics & probabilitydo-calculuscausality; do-calculus; selection bias; transportability; missing data; case-control design; meta-analysisStatistics - Machine LearningSearch algorithmselection bias0101 mathematicsParametric statisticspäättelymeta-analyysicase-control designhakualgoritmit113 Computer and information sciencesMissing datameta-analysisIdentification (information)Artificial Intelligence (cs.AI)Causal inferencekausaliteettiIdentifiabilityProbability distributionData miningStatistics Probability and UncertaintycomputerSoftwareJournal of Statistical Software
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Collective Cell Migration in a Fibrous Environment: A Hybrid Multiscale Modelling Approach

2021

International audience; The specific structure of the extracellular matrix (ECM), and in particular the density and orientation of collagen fibres, plays an important role in the evolution of solid cancers. While many experimental studies discussed the role of ECM in individual and collective cell migration, there are still unanswered questions about the impact of nonlocal cell sensing of other cells on the overall shape of tumour aggregation and its migration type. There are also unanswered questions about the migration and spread of tumour that arises at the boundary between different tissues with different collagen fibre orientations. To address these questions, in this study we develop …

0301 basic medicineStatistics and Probabilitymulti-scale hybrid mathematical modelMaterials sciencecell migration[SDV.CAN]Life Sciences [q-bio]/Cancercontinuous cell-extracellular matrix interactionsQA273-280Articlenumerical simulationsExtracellular matrix03 medical and health sciences0302 clinical medicineCollagen fibres[SDV.BC.IC]Life Sciences [q-bio]/Cellular Biology/Cell Behavior [q-bio.CB][NLIN]Nonlinear Sciences [physics][MATH]Mathematics [math]T57-57.97Applied mathematics. Quantitative methodsApplied MathematicsCollective cell migrationCell migrationTumour invasionCollagen fibre030104 developmental biologyorientation of extracellular matrix fibresagent based discrete cell-cell interactionsContinuous fieldBiological systemProbabilities. Mathematical statistics030217 neurology & neurosurgeryFrontiers in Applied Mathematics and Statistics
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