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Inference on high-dimensional implicit dynamic models using a guided intermediate resampling filter

Statistics and Computing(2020)10.1007/s11222-020-09957-3Source: DataRank Database

Inference on high-dimensional implicit dynamic models using a guided intermediate resampling filter is a research paper published in Statistics and Computing (2020). On theSindex it has a DataRank of 0. It has been cited 3 times.

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Open Access3 citations

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (12 grants)Impact (FWCI 0.40)OA: greenTopics (35)IDs (PubMed, PMC, OpenAlex)

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Findable (1/2)

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Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (2)

Edward L. Ionides ORCID,Joonha Park ORCID

Live enrichment

PubMed:35664372 PMC:PMC9164307 OpenAlex:https://openalex.org/W2971009506

National Science Foundation

Grant: DMS-1308919

National Science Foundation

Grant: DMS-1761603

National Science Foundation

Grant: DMS-1513040

National Institutes of Health

Grant: 1-U54-GM111274

National Institutes of Health

Grant: 1-U01-GM110712

NIGMS NIH HHS

Grant: U54 GM111274

NIGMS NIH HHS

Grant: U01 GM110712

National Institutes of Health

Grant: 5U54GM111274-02

Understanding Transmission with Integrated Genetic and Epidemiologic Inference

National Science Foundation

Grant: 1761603

Collaborative Research: Urban Vector-Borne Disease Transmission Demands Advances in Spatiotemporal Statistical Inference

National Science Foundation

Grant: 1308919

Iterated filtering: New theory, algorithms and applications

National Institutes of Health

Grant: 5U01GM110712-03

Modeling the Effects of the Environment on Enteric Pathogen Dynamics

National Science Foundation

Grant: 1513040

High-Dimensional Bayesian Computations: The Moreau-Yosida Posterior Approximation

FWCI

0.40

Citation Percentile

0.7%

Influential Citations

Citation Trend

2021

2022

greenLicense: Springer TDM

repositoryhttps://arxiv.org/pdf/1708.08543

GREENhttps://arxiv.org/pdf/1708.08543

repositoryhttps://arxiv.org/pdf/1708.08543

publisherhttps://link.springer.com/content/pdf/10.1007/s11222-020-09957-3.pdf

publisherhttps://link.springer.com/article/10.1007/s11222-020-09957-3/fulltext.html

Fields of Study

Gaussian Processes and Bayesian InferenceClimate variability and modelsTarget Tracking and Data Fusion in Sensor NetworksMedicineComputer ScienceMathematics01 natural sciences0101 mathematics

Keywords

Particle filterCurse of dimensionalityComputer scienceInferenceNonlinear systemGaussian processExtended Kalman filterAlgorithmKalman filterEnsemble Kalman filterGaussianApplied mathematicsMathematicsArtificial intelligencePhysicsSequential Monte CarloImplicit ModelsPlug-And-Play PropertySpatiotemporal InferenceFOS: Computer and information sciencesMonte Carlo methodsInference from stochastic processes and predictionApplications of statistics to biology and medical sciences; meta analysisMethodology (stat.ME)Sequential estimationDirectional data; spatial statisticsStatistics - Methodology