Search results for " functional data analysis"

showing 6 items of 6 documents

Common functional component modelling

2005

Functional data analysis (FDA) has become a popular technique in applied statistics. In particular, this methodology has received considerable attention in recent studies in empirical finance. In this talk we discuss selected topics of functional principal components analysis that are motivated by financial data.

nonparametric risk management generalized hyperbolic distribution functional data analysisjel:G19jel:C13
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Detecting clusters in spatially correlated waveforms

2017

Seismic networks often record signals characterized by similar shapes that provide important information according to their geographic positions. We propose an approach to identify homogeneous clusters of seismic waves, combining analysis of waveforms with metadata and spectrogram information. In waveforms clustering, cross-correlation measures between signals may presents some limitations, so we refer to more recent contributes relating data-depth based clustering analysis. The mechanism for alignment is also an important topic of the analysis: warping (or aligning) procedures identify nuisance effects in phase variation, that, if ignored, may result in a possible loss of information and t…

spatial clusteringfast fourier transform.Seismic waveformfunctional data analysiSettore SECS-S/01 - StatisticaSeismic waveforms; spatial clustering; functional data analysis; fast fourier transform.
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A PCA-based clustering algorithm for the identification of stratiform and convective precipitation at the event scale: an application to the sub-hour…

2021

AbstractUnderstanding the structure of precipitation and its separation into stratiform and convective components is still today one of the important and interesting challenges for the scientific community. Despite this interest and the advances made in this field, the classification of rainfall into convective and stratiform components is still today not trivial. This study applies a novel criterion based on a clustering approach to analyze a high temporal resolution precipitation dataset collected for the period 2002–2018 over the Sicily (Italy). Starting from the rainfall events obtained from this dataset, the developed methodology makes it possible to classify the rainfall events into f…

ConvectionEnvironmental Engineering010504 meteorology & atmospheric sciencesFunctional data analysis01 natural sciencesExtreme rainfall Convective and stratiform precipitation Functional data analysis PCA-based clustering analysis010104 statistics & probabilityIdentification (information)HyetographClimatologyTemporal resolutionEnvironmental ChemistryPrecipitation0101 mathematicsSafety Risk Reliability and QualityCluster analysisGeology0105 earth and related environmental sciencesGeneral Environmental ScienceWater Science and TechnologyConvective precipitation
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Functional Principal Component Analysis for the explorative analysis of multisite-multivariate air pollution time series with long gaps

2013

The knowledge of the urban air quality represents the first step to face air pollution issues. For the last decades many cities can rely on a network of monitoring stations recording concentration values for the main pollutants. This paper focuses on functional principal component analysis (FPCA) to investigate multiple pollutant datasets measured over time at multiple sites within a given urban area. Our purpose is to extend what has been proposed in the literature to data that are multisite and multivariate at the same time. The approach results to be effective to highlight some relevant statistical features of the time series, giving the opportunity to identify significant pollutants and…

Statistics and ProbabilityPollutantFunctional principal component analysisgeographyMultivariate statisticsgeography.geographical_feature_categorySeries (mathematics)Computer scienceAir pollutionFunctional data analysiscomputer.software_genreUrban areamedicine.disease_causeAir quality Functional Data Analysis Three mode FPCA EOFmedicineData miningStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaAir quality indexcomputer
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Clusters of effects curves in quantile regression models

2018

In this paper, we propose a new method for finding similarity of effects based on quantile regression models. Clustering of effects curves (CEC) techniques are applied to quantile regression coefficients, which are one-to-one functions of the order of the quantile. We adopt the quantile regression coefficients modeling (QRCM) framework to describe the functional form of the coefficient functions by means of parametric models. The proposed method can be utilized to cluster the effect of covariates with a univariate response variable, or to cluster a multivariate outcome. We report simulation results, comparing our approach with the existing techniques. The idea of combining CEC with QRCM per…

Statistics and ProbabilityStatistics::TheoryMultivariate statistics05 social sciencesUnivariateFunctional data analysis01 natural sciencesQuantile regressionQuantile regression coefficients modeling Multivariate analysis Functional data analysis Curves clustering Variable selection010104 statistics & probabilityComputational Mathematics0502 economics and businessParametric modelCovariateStatistics::MethodologyApplied mathematics0101 mathematicsStatistics Probability and UncertaintyCluster analysisSettore SECS-S/01 - Statistica050205 econometrics MathematicsQuantile
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Misalignment of Spectral Data: Constrained Optimization in a Functional Data Analysis Framework

2022

Across several branches of sciences, a large number of applications involves data represented as functions and curves, for which functional data analysis can play a central role in solving a variety of problem formulations. With some thecnologies, the obtained data are spectra containing a vast amount of information concerning the composition of a sample: in order to infer the chemical composition of the materials from spectra, functional data analysis offers a valuable mean for characterizing the spectral response through identification of peaks position and intensity. The collection of data from different measurement may exhibit similar peak pattern but display misalignment in their peaks…

multple alignment functional data analysis constrained registrationSettore SECS-S/01 - Statistica
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