Tag: Statistics and Probability
Continuous-time sampler handles unknown-dimensional Bayesian models
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in MathematicsWhat the study found The paper presents samsara, a continuous-time Markov chain Monte Carlo (CTMCMC) sampler designed for Bayesian inference when the number of parameters is unknown. The authors report that it achieves automatic acceptance of trans-dimensional moves and high sampling efficiency. Why the authors say this matters The authors say this matters because many…
Dynamic likelihood estimation can improve hazard rate fitting
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in MathematicsSemiparametric method for hazard rate estimation combining parametric efficiency with nonparametric flexibility through dynamic local likelihood smoothing
Framework standardizes NHIS population surveillance analysis
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in Data scienceStandardized statistical framework for National Health Interview Survey analyses to improve methodological consistency, enable cross-study comparisons, and strengthen population health.
