gemlib.mcmc supplies composable kernel abstractions for Metropolis-within-Gibbs sampling via writer monads, allowing concise expression and reuse of complex MCMC algorithms for partially observed epidemic models.
Examples of Adaptive MCMC
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
SFB basis applied to eBOSS DR16 samples identifies evidence (p<0.005 vs EZMocks) of stellar contamination systematics at large scales in QSOs and unknown systematics at plate/imaging scales in both LRG and QSO samples via fNL inconsistencies.
citing papers explorer
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gemlib.mcmc: composable kernels for Metropolis-within-Gibbs sampling schemes
gemlib.mcmc supplies composable kernel abstractions for Metropolis-within-Gibbs sampling via writer monads, allowing concise expression and reuse of complex MCMC algorithms for partially observed epidemic models.
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Demonstrating the Use of the Spherical Fourier Bessel Basis for Large Scale Clustering Systematics Discovery and Mitigation with eBOSS
SFB basis applied to eBOSS DR16 samples identifies evidence (p<0.005 vs EZMocks) of stellar contamination systematics at large scales in QSOs and unknown systematics at plate/imaging scales in both LRG and QSO samples via fNL inconsistencies.