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Journal of Computational and Graphical Statistics Volume 29, 2020 - Issue 3
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Computational Advances in Prediction, Estimation, and Inference

Density Deconvolution With Additive Measurement Errors Using Quadratic Programming

Ran YangDepartment of Industrial Engineering & Management Sciences, Northwestern University, Evanston, IL; View further author information
,
Daniel W. ApleyDepartment of Industrial Engineering & Management Sciences, Northwestern University, Evanston, IL; Correspondence[email protected]
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,
Jeremy StaumDepartment of Industrial Engineering & Management Sciences, Northwestern University, Evanston, IL; View further author information
&
David RuppertDepartment of Statistics and Data Science and School of Operations Research and Information Engineering, Cornell University, Ithaca, NYView further author information
Pages 580-591 | Received 27 Sep 2018, Accepted 06 Dec 2019, Published online: 22 Jan 2020

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Read on this site (2)

David Kent & David Ruppert. (2023) Smoothness-Penalized Deconvolution (SPeD) of a Density Estimate. Journal of the American Statistical Association 0:0, pages 1-11.
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Francesca R. Crucinio, Arnaud Doucet & Adam M. Johansen. (2023) A Particle Method for Solving Fredholm Equations of the First Kind. Journal of the American Statistical Association 118:542, pages 937-947.
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Articles from other publishers (2)

Chew-Seng Chee & Byungtae Seo. (2022) Density deconvolution under a k-monotonicity constraint. Statistics and Computing 32:5.
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Ran Yang, David Kent, Daniel W. Apley, Jeremy Staum & David Ruppert. (2021) Bias-corrected Estimation of the Density of a Conditional Expectation in Nested Simulation Problems. ACM Transactions on Modeling and Computer Simulation 31:4, pages 1-36.
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