A log-Gaussian Cox process with sequential Monte Carlo for line narrowing in spectroscopy
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Publication:6194412
DOI10.3934/fods.2023008arXiv2202.13120OpenAlexW4383164269MaRDI QIDQ6194412
Matthew T. Moores, Emma Hannula, Erik Vartiainen, Lassi Roininen, Teemu Härkönen
Publication date: 14 February 2024
Published in: Foundations of Data Science (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2202.13120
Poisson processBayesian inferencestatistical signal processingpeak detectionparticle filtering and smoothingFourier self-deconvolution
Bayesian inference (62F15) Sequential estimation (62L12) Monte Carlo methods applied to problems in optics and electromagnetic theory (78M31)
Cites Work
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- Bayesian inference for Hawkes processes
- An adaptive sequential Monte Carlo method for approximate Bayesian computation
- On the limited memory BFGS method for large scale optimization
- Space and circular time log Gaussian Cox processes with application to crime event data
- Estimation and information in stationary time series
- Fourier Transforms in Spectroscopy
- Introduction to Time Series and Forecasting
- Sequential Monte Carlo Samplers
- An Introduction to Sequential Monte Carlo
- Lectures on the Poisson Process
- Waste-Free Sequential Monte Carlo
- Spatial and spatio-temporal log-Gaussian Cox processes: extending the geostatistical paradigm
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