Search results for "piecewise constant model"

showing 3 items of 3 documents

A heuristic, iterative algorithm for change-point detection in abrupt change models

2017

Change-point detection in abrupt change models is a very challenging research topic in many fields of both methodological and applied Statistics. Due to strong irregularities, discontinuity and non-smootheness, likelihood based procedures are awkward; for instance, usual optimization methods do not work, and grid search algorithms represent the most used approach for estimation. In this paper a heuristic, iterative algorithm for approximate maximum likelihood estimation is introduced for change-point detection in piecewise constant regression models. The algorithm is based on iterative fitting of simple linear models, and appears to extend easily to more general frameworks, such as models i…

0301 basic medicineStatistics and ProbabilityMathematical optimizationIterative methodHeuristic (computer science)Linear model01 natural sciencesPiecewise constant model Approximate maximum likelihood Model linearization Grid search limitations010104 statistics & probability03 medical and health sciencesComputational MathematicsDiscontinuity (linguistics)030104 developmental biologyHyperparameter optimizationCovariatePiecewise0101 mathematicsStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaChange detectionMathematics
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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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A new picking algorithm based on the variance piecewise constant models

2022

AbstractIn this paper, we propose a novel picking algorithm for the automatic P- and S-waves onset time determination. Our algorithm is based on the variance piecewise constant models of the earthquake waveforms. The effectiveness and robustness of our picking algorithm are tested both on synthetic seismograms and real data. We simulate seismic events with different magnitudes (between 2 and 5) recorded at different epicentral distances (between 10 and 250 km). For the application to real data, we analyse waveforms from the seismic sequence of L’Aquila (Italy), in 2009. The obtained results are compared with those obtained by the application of the classic STA/LTA picking algorithm. Althoug…

variance piecewise constant modelEnvironmental EngineeringEarthquake Early WarningArrival timesChange-pointEnvironmental ChemistrySettore SECS-S/01 - StatisticaSafety Risk Reliability and QualityPickingGeneral Environmental ScienceWater Science and TechnologyStochastic Environmental Research and Risk Assessment
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