Search results for "R package"

showing 6 items of 26 documents

Including covariates in a space-time point process with application to seismicity

2020

AbstractThe paper proposes a spatio-temporal process that improves the assessment of events in space and time, considering a contagion model (branching process) within a regression-like framework to take covariates into account. The proposed approach develops the forward likelihood for prediction method for estimating the ETAS model, including covariates in the model specification of the epidemic component. A simulation study is carried out for analysing the misspecification model effect under several scenarios. Also an application to the Italian seismic catalogue is reported, together with the reference to the developed R package.

Statistics and ProbabilityMathematical optimization010504 meteorology & atmospheric sciencesSpacetimeComputer scienceSpace timeSpace-time point processes ETAS model R package for seismic datacovariatesProcess (computing)01 natural sciencesPoint process010104 statistics & probabilitySpecificationComponent (UML)Covariate0101 mathematicsStatistics Probability and Uncertainty0105 earth and related environmental sciencesBranching process
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Windowed Etas Models With Application To The Chilean Seismic Catalogs

2015

Abstract The seismicity in Chile is estimated using an ETAS (Epidemic Type Aftershock sequences) space–time point process through a semi-parametric technique to account for the estimation of parametric and nonparametric components simultaneously. The two components account for triggered and background seismicity respectively, and are estimated by alternating a ML estimation for the parametric part and a forward predictive likelihood technique for the nonparametric one. Given the geographic and seismological characteristics of Chile, the sensitivity of the technique with respect to different geographical areas is examined in overlapping successive windows with varying latitude. A different b…

Statistics and ProbabilityNonparametric statisticsManagement Monitoring Policy and LawInduced seismicityGeodesyPoint processPhysics::GeophysicsLatitudeSpace-time point processes ETAS model etasFLP R packagePredictive likelihoodStatisticsSensitivity (control systems)Computers in Earth SciencesAftershockGeologyParametric statistics
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Estimating growth charts via nonparametric quantile regression: a practical framework with application in ecology.

2013

We discuss a practical and effective framework to estimate reference growth charts via regression quantiles. Inequality constraints are used to ensure both monotonicity and non-crossing of the estimated quantile curves and penalized splines are employed to model the nonlinear growth patterns with respect to age. A companion R package is presented and relevant code discussed to favour spreading and application of the proposed methods.

Statistics and ProbabilitySettore BIO/07 - EcologiaStatistics::TheoryEcology (disciplines)Nonparametric statisticsMonotonic functionRegressionStatistics::ComputationQuantile regressionNonlinear systemR packageStatisticsEconometricsStatistics::MethodologyGrowth charts Nonparametric regression quantiles Penalized splines P. oceanica modelling R softwareStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaGeneral Environmental ScienceMathematicsQuantile
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Efficient change point detection in genomic sequences of continuous measurements

2010

Abstract Motivation: Knowing the exact locations of multiple change points in genomic sequences serves several biological needs, for instance when data represent aCGH profiles and it is of interest to identify possibly damaged genes involved in cancer and other diseases. Only a few of the currently available methods deal explicitly with estimation of the number and location of change points, and moreover these methods may be somewhat vulnerable to deviations of model assumptions usually employed. Results: We present a computationally efficient method to obtain estimates of the number and location of the change points. The method is based on a simple transformation of data and it provides re…

Statistics and Probabilitymodel selectionBreast Neoplasmscomputer.software_genreBiochemistryCell LineSimple (abstract algebra)Cell Line TumorHumansComputer Simulationpiecewise constant modelMolecular BiologyMathematicsOligonucleotide Array Sequence AnalysisSupplementary dataComparative Genomic HybridizationModels StatisticalSeries (mathematics)Model selectionGenomicsComputer Science ApplicationsComputational MathematicsR packageTransformation (function)Computational Theory and MathematicsChange pointsChangepointaCGH analysiFemaleData miningSettore SECS-S/01 - StatisticacomputerChange detection
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deaR-Shiny: An Interactive Web App for Data Envelopment Analysis

2021

In this paper, we describe an interactive web application (deaR-shiny) to measure efficiency and productivity using data envelopment analysis (DEA). deaR-shiny aims to fill the gap that currently exists in the availability of online DEA software offering practitioners and researchers free access to a very wide variety of DEA models (both conventional and fuzzy models). We illustrate how to use the web app by replicating the main results obtained by Carlucci, Cirà and Coccorese in 2018, who investigate the efficiency and economic sustainability of Italian regional airport by using two conventional DEA models, and the results given by Kao and Liu in their papers published in 2000 and 2003, wh…

fuzzy deaOperations researchComputer scienceGeography Planning and Development0211 other engineering and technologiesTJ807-83002 engineering and technologyManagement Monitoring Policy and LawTD194-195Fuzzy logic:CIENCIAS ECONÓMICAS [UNESCO]R softwareRenewable energy sourcesmalmquist indexSoftwareMalmquist indexDEA0202 electrical engineering electronic engineering information engineeringData envelopment analysisFuzzy numberWeb applicationGE1-350fuzzy DEAMeasure (data warehouse)021103 operations researchEnvironmental effects of industries and plantsRenewable Energy Sustainability and the Environmentbusiness.industryshinydear packageUNESCO::CIENCIAS ECONÓMICASMissing dataVariety (cybernetics)Environmental sciencesdeaefficiency020201 artificial intelligence & image processingdata envelopment analysisdeaR packagebusinessr softwareSustainability
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Space-Time Forecasting of Seismic Events in Chile

2017

The aim of this work is to study the seismicity in Chile using the ETAS (epidemic type aftershock sequences) space‐time approach. The proposed ETAS model is estimated using a semi‐parametric technique taking into account the parametric and nonparametric components corresponding to the triggered and background seismicity, respectively. The model is then used to predict the temporal and spatial intensity of events for some areas of Chile where recent large earthquakes (with magnitude greater than 8.0 M) occurred.

space‐time point processes conditional intensity function ETAS model etasFLP(R package) forecastSpace timeforecsting Chile esrthquakesSettore SECS-S/01 - StatisticaGeologySeismology
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