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Estimating means of bounded random variables by betting
We derive confidence intervals (CIs) and confidence sequences (CSs) for the classical
problem of estimating a bounded mean. Our approach generalizes and improves on the …
problem of estimating a bounded mean. Our approach generalizes and improves on the …
Tight concentrations and confidence sequences from the regret of universal portfolio
A classic problem in statistics is the estimation of the expectation of random variables from
samples. This gives rise to the tightly connected problems of deriving concentration …
samples. This gives rise to the tightly connected problems of deriving concentration …
Empirical Bernstein in smooth Banach spaces
Existing concentration bounds for bounded vector-valued random variables include
extensions of the scalar Hoeffding and Bernstein inequalities. While the latter is typically …
extensions of the scalar Hoeffding and Bernstein inequalities. While the latter is typically …
Peeking with PEAK: Sequential, nonparametric composite hypothesis tests for means of multiple data streams
We propose a novel nonparametric sequential test for composite hypotheses for means of
multiple data streams. Our proposed method,\emph {peeking with expectation-based …
multiple data streams. Our proposed method,\emph {peeking with expectation-based …
Jiayi Li, Yuantong Li and **aowu Dai's contribution to the Discussion of 'Estimating means of bounded random variables by betting'by Waudby-Smith and Ramdas
1 Methods Consider a sequence of random variables (X t) t= 1∞, drawn from a distribution
P∈ P μ, where P μ represents the set of all distributions on [0, 1]∞. We assume EP [X t| X …
P∈ P μ, where P μ represents the set of all distributions on [0, 1]∞. We assume EP [X t| X …
Art Owen's contribution to the Discussion of 'Estimating means of bounded random variables by betting'by Waudby-Smith and Ramdas
We derive confidence intervals (CIs) and confidence sequences (CSs) for the classical
problem of estimating a bounded mean. Our approach generalizes and improves on the …
problem of estimating a bounded mean. Our approach generalizes and improves on the …
Gambling-based confidence sequences for bounded random vectors
A confidence sequence (CS) is a sequence of confidence sets that contains a target
parameter of an underlying stochastic process at any time step with high probability. This …
parameter of an underlying stochastic process at any time step with high probability. This …
Philip B. Stark's contribution to the Discussion of 'Estimating means of bounded random variables by betting'by Waudby-Smith and Ramdas
We derive confidence intervals (CIs) and confidence sequences (CSs) for the classical
problem of estimating a bounded mean. Our approach generalizes and improves on the …
problem of estimating a bounded mean. Our approach generalizes and improves on the …
Anastasios N. Angelopoulos' contribution to the Discussion of 'Estimating means of bounded random variables by betting'by Waudby-Smith and Ramdas
We derive confidence intervals (CIs) and confidence sequences (CSs) for the classical
problem of estimating a bounded mean. Our approach generalizes and improves on the …
problem of estimating a bounded mean. Our approach generalizes and improves on the …
Steven R Howard's contribution to the Discussion of 'Estimating means of bounded random variables by betting'by Waudby-Smith and Ramdas
We derive confidence intervals (CIs) and confidence sequences (CSs) for the classical
problem of estimating a bounded mean. Our approach generalizes and improves on the …
problem of estimating a bounded mean. Our approach generalizes and improves on the …