On proportional volume sampling for experimental design in general spaces
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Publication:2677908
DOI10.1007/s11222-022-10115-0zbMath1502.62022arXiv2011.04562OpenAlexW3101242998MaRDI QIDQ2677908
Publication date: 9 January 2023
Published in: Statistics and Computing (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2011.04562
Computational methods for problems pertaining to statistics (62-08) Linear regression; mixed models (62J05) Optimal statistical designs (62K05) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)
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Cites Work
- spatstat
- DPPy
- Optimal designs for spline wavelet regression models
- Determinantal processes and independence
- Approximate optimal designs for multivariate polynomial regression
- \(D\)-optimal designs for trigonometric regression models on a partial circle
- Design of experiments in nonlinear models. Asymptotic normality, optimality criteria and small-sample properties
- Geometric characterization of \(D\)-optimal designs for random coefficient regression models
- Determinantal Point Processes for Machine Learning
- Course 1 Random matrices and determinantal processes
- The coincidence approach to stochastic point processes
- Bayesian D-Optimal and Model Robust Designs in Linear Regression Models
- An Introduction to the Theory of Point Processes
- Determinantal Point Processes in Randomized Numerical Linear Algebra
- Proportional Volume Sampling and Approximation Algorithms for A-Optimal Design
- Optimal Design of Experiments
- On largest volume simplices and sub-determinants
- Determinantal Point Process Models and Statistical Inference
- Topics in optimal design
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