Search results for "INDEX"

showing 10 items of 5395 documents

Comparative Evaluation of Community Detection Algorithms: A Topological Approach

2012

International audience; Community detection is one of the most active fields in complex networks analysis, due to its potential value in practical applications. Many works inspired by different paradigms are devoted to the development of algorithmic solutions allowing to reveal the network structure in such cohesive subgroups. Comparative studies reported in the literature usually rely on a performance measure considering the community structure as a partition (Rand Index, Normalized Mutual information, etc.). However, this type of comparison neglects the topological properties of the communities. In this article, we present a comprehensive comparative study of a representative set of commu…

Statistics and ProbabilityFOS: Computer and information sciencesPhysics - Physics and SocietyComputer science[INFO.INFO-OH]Computer Science [cs]/Other [cs.OH]Rand indexFOS: Physical sciences02 engineering and technologyPhysics and Society (physics.soc-ph)Topology01 natural sciencesMeasure (mathematics)010305 fluids & plasmasSet (abstract data type)Development (topology)0103 physical sciences0202 electrical engineering electronic engineering information engineeringEquivalence (measure theory)Random graphSocial and Information Networks (cs.SI)Computer Science - Social and Information NetworksStatistical and Nonlinear PhysicsNetwork dynamicsPartition (database)[ INFO.INFO-OH ] Computer Science [cs]/Other [cs.OH]020201 artificial intelligence & image processingStatistics Probability and Uncertainty
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Fitting generalized linear models with unspecified link function: A P-spline approach

2008

Generalized linear models (GLMs) outline a wide class of regression models where the effect of the explanatory variables on the mean of the response variable is modelled throughout the link function. The choice of the link function is typically overlooked in applications and the canonical link is commonly used. The estimation of GLMs with unspecified link function is discussed, where the linearity assumption between the link and the linear predictor is relaxed and the unspecified relationship is modelled flexibly by means of P-splines. An estimating algorithm is presented, alternating estimation of two working GLMs up to convergence. The method is applied to the analysis of quit behavior of…

Statistics and ProbabilityGeneralized linear modelCanonical link elementApplied MathematicsLogitLinear modelRegression analysisLinear predictionProbitComputational MathematicsSpline (mathematics)Computational Theory and MathematicsStatisticsApplied mathematicsSettore SECS-S/01 - StatisticaGLM P-splines link function single index modelsMathematics
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Empirical investigation of stock price dynamics in an emerging market

1999

Abstract We study the development of an emerging market – the Budapest Stock Exchange – by investigating the time evolution of some statistical properties of heavily traded stocks. Moving quarter by quarter over a period of two and a half years we analyze the scaling properties of the standard deviation of intra-day log-price changes. We observe scaling using both seconds and ticks as units of time. For the investigated stocks a Levy shape is a good approximation to the probability density function of tick-by-tick log-price changes in each quarter: the index of the distribution follows an increasing trend, suggesting it could be used as a measure of market efficiency.

Statistics and ProbabilityIndex (economics)EconophysicsStock exchangeEconometricsEconomicsCapitalization-weighted indexProbability density functionCondensed Matter PhysicsQuarter (United States coin)Emerging marketsStandard deviationPhysica A: Statistical Mechanics and its Applications
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Stock market dynamics and turbulence: parallel analysis of fluctuation phenomena

1997

Abstract We report analogies and differences between the fluctuations in an economic index and the fluctuations in velocity of a fluid in a fully turbulent state. Specifically, we systematically compare (i) the statistical properties of the S&P 500 cash index recorded during the period January 84–December 89 with (ii) the statistical properties of the velocity of turbulent air measured in the atmospheric surface layer about 6 m above a wheat canopy in the Connecticut Agricultural Research Station. We find non-Gaussian statistics, and intermittency, for both processes (i) and (ii) but the deviation from a Gaussian probability density function are different for stock market dynamics and turbu…

Statistics and ProbabilityIndex (economics)MeteorologyTurbulenceGaussianDynamics (mechanics)Probability density functionCondensed Matter Physicslaw.inventionPhysics::Fluid Dynamicssymbols.namesakelawIntermittencysymbolsStock marketSurface layerStatistical physicsMathematicsPhysica A: Statistical Mechanics and its Applications
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Accounting for previous events to model and predict traffic accidents at the road segment level: A study in Valencia (Spain)

2022

Abstract Predicting the occurrence of traffic accidents is essential for establishing preventive measures and reducing the impact of traffic accidents. In particular, it is fundamental to make predictions using fine spatio-temporal units. In this paper, the daily risk of traffic accident occurrence across the road network of Valencia (Spain) is modeled through logistic regression models. The spatio-temporal dependence between the observations is accounted for through the inclusion of lagged binary covariates representing the previous occurrence of a traffic accident within a spatio-temporal window centered at each combination of day and segment of the network. A temporal distance of 28 days…

Statistics and ProbabilityIndex (economics)Temporal distanceTraffic accidentNames of the days of the weekCovariateStatisticsStatistical and Nonlinear PhysicsMatthews correlation coefficientLogistic regressionMathematicsPhysica A: Statistical Mechanics and its Applications
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Weighting Elementary Prices in Consumer Price Index Construction Using Spatial Autocorrelation

2013

The Consumer Price Indexes (CPI) are used in current economic systems to measure inflation. When constructing CPIs, however, official institutions have systematically overlooked the spatial dimension of elementary prices. Ignoring the fact that prices are collected at geographical locations implicitly implies considering prices as spatially independent, when in fact they are not. To solve this problem, this article proposes to weight basic price data by taking into account the spatial correlation they display. The weighted geometric and arithmetic means suggested generalize and improve the simple geometric and arithmetic means currently in use.

Statistics and ProbabilityInflationComputer Science::Computer Science and Game TheorySpatial correlationmedia_common.quotation_subjectWeightingPrice indexStatisticsEconometricsConsumer price indexDimension (data warehouse)Spatial analysisArithmetic meanmedia_commonMathematicsCommunications in Statistics - Theory and Methods
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A more efficient second order blind identification method for separation of uncorrelated stationary time series

2016

The classical second order source separation methods use approximate joint diagonalization of autocovariance matrices with several lags to estimate the unmixing matrix. Based on recent asymptotic results, we propose a novel unmixing matrix estimator which selects the best lag set from a finite set of candidate sets specified by the user. The theory is illustrated by a simulation study.

Statistics and ProbabilityMathematical optimizationaffine equivarianceminimum distance indexasymptotic normalityAsymptotic distributionlinear process01 natural sciencesSet (abstract data type)010104 statistics & probabilityMatrix (mathematics)SOBIComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATION0502 economics and businessSource separationjoint diagonalization0101 mathematicsFinite set050205 econometrics Mathematicsta112Series (mathematics)05 social sciencesEstimatorAutocovarianceStatistics Probability and UncertaintyAlgorithmStatistics & Probability Letters
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A new measure for the attitude to mobility of Italian students and graduates: a topological data analysis approach

2022

AbstractStudents’ and graduates’ mobility is an interesting topic of discussion especially for the Italian education system and universities. The main reasons for migration and for the so called brain drain, can be found in the socio-economic context and in the famous North–South divide. Measuring mobility and understanding its dynamic over time and space are not trivial tasks. Most of the studies in the related literature focus on the determinants of such phenomenon, in this paper, instead, combining tools coming from graph theory and Topological Data Analysis we propose a new measure for the attitude to mobility. Each mobility trajectory is represented by a graph and the importance of the…

Statistics and ProbabilityMobility analysis Brain drain Mobility index Topological data analysis Graph Persistence diagramSettore SECS-S/05 - Statistica SocialeStatistics Probability and Uncertainty
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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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Value-at-Risk and Tsallis statistics: risk analysis of the aerospace sector

2004

In this study, we analyze the aerospace stocks prices in order to characterize the sector behavior. The data analyzed cover the period from January 1987 to April 1999. We present a new index for the aerospace sector and we investigate the statistical characteristics of this index. Our results show that this index is well described by Tsallis distribution. We explore this result and modify the standard Value-at-Risk (VaR), financial risk assessment methodology in order to reflect an asset which obeys Tsallis non-extensive statistics.

Statistics and ProbabilityRisk analysisIndex (economics)Actuarial scienceStatistical Finance (q-fin.ST)EconophysicsStatistical Mechanics (cond-mat.stat-mech)Financial riskTsallis statisticsFOS: Physical sciencesQuantitative Finance - Statistical FinanceDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksCondensed Matter PhysicsFOS: Economics and businessEconomicsEconometricsTsallis distributionAsset (economics)Value at riskCondensed Matter - Statistical Mechanics
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