The effective sample size
Summary
The post explains effective sample size in the context of importance sampling and covariate shift, showing how reweighting data increases variance and reduces usable information. It defines n_eff via Kish's method, derives it through two approaches (variance of a weighted sum of normals and Hoeffding’s inequality), and discusses applications to replay buffers in off-policy reinforcement learning and Sequential Monte Carlo.