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Open AccessJournal ArticleDOI

Kernel density estimation via diffusion

TLDR
A new adaptive kernel density estimator based on linear diffusion processes that builds on existing ideas for adaptive smoothing by incorporating information from a pilot density estimate and a new plug-in bandwidth selection method that is free from the arbitrary normal reference rules used by existing methods.
Abstract
We present a new adaptive kernel density estimator based on linear diffusion processes. The proposed estimator builds on existing ideas for adaptive smoothing by incorporating information from a pilot density estimate. In addition, we propose a new plug-in bandwidth selection method that is free from the arbitrary normal reference rules used by existing methods. We present simulation examples in which the proposed approach outperforms existing methods in terms of accuracy and reliability.

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Citations
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Journal ArticleDOI

IsoplotR: A free and open toolbox for geochronology

TL;DR: The basic principles of radiometric geochronology as implemented in a new software package called IsoplotR, which was designed to be free, flexible and future-proof, are reviewed.
Journal ArticleDOI

On the visualisation of detrital age distributions

TL;DR: In this paper, the authors proposed Kernel Density Estimation (KDE), a more robust alternative to the Probability Density Plot (PDP), which also involves summing a set of Gaussian distributions, but does not explicitly take into account the analytical uncertainties.
Journal ArticleDOI

Methods for Summarizing Radiocarbon Datasets

TL;DR: Three different approaches are compared: “Sum” distributions, postulated undated events, and kernel density approaches and their suitability for visualizing the results from chronological and geographic analyses considered for cases with and without useful prior information.
Journal ArticleDOI

CaImAn an open source tool for scalable calcium imaging data analysis

TL;DR: CaImAn provides automatic and scalable methods to address problems common to pre-processing, including motion correction, neural activity identification, and registration across different sessions of data collection, while requiring minimal user intervention.
References
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BookDOI

Density estimation for statistics and data analysis

TL;DR: The Kernel Method for Multivariate Data: Three Important Methods and Density Estimation in Action.
Book

Linear and Quasilinear Equations of Parabolic Type

TL;DR: In this article, the authors considered a hyperbolic parabolic singular perturbation problem for a quasilinear equation of kirchhoff type and obtained parameter dependent time decay estimates of the difference between the solutions of the solution of a quasi-linear parabolic equation and the corresponding linear parabolic equations.
BookDOI

Sequential Monte Carlo methods in practice

TL;DR: This book presents the first comprehensive treatment of Monte Carlo techniques, including convergence results and applications to tracking, guidance, automated target recognition, aircraft navigation, robot navigation, econometrics, financial modeling, neural networks, optimal control, optimal filtering, communications, reinforcement learning, signal enhancement, model averaging and selection.
Book

Numerical Solution of Stochastic Differential Equations

TL;DR: In this article, a time-discrete approximation of deterministic Differential Equations is proposed for the stochastic calculus, based on Strong Taylor Expansions and Strong Taylor Approximations.
Book

Markov Processes: Characterization and Convergence

TL;DR: In this paper, the authors present a flowchart of generator and Markov Processes, and show that the flowchart can be viewed as a branching process of a generator.
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