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In this paper, we consider Bayesian point estimation and predictive density estimation in the binomial case. After presenting preliminary results on these problems, we compare the risk functions of the Bayes estimators based on the…

Statistics Theory · Mathematics 2021-09-13 Yasuyuki Hamura

A collection of $n$ random events is said to be $(n - 1)$-wise independent if any $n - 1$ events among them are mutually independent. We characterise all probability measures with respect to which $n$ random events are $(n - 1)$-wise…

Probability · Mathematics 2022-11-04 Karthik Natarajan , Arjun Kodagehalli Ramachandra , Colin Tan

This paper considers a distributionally robust chance constraint model with a general ambiguity set. We show that a sample based approximation of this model converges under suitable sufficient conditions. We also show that upper and lower…

Optimization and Control · Mathematics 2025-01-17 Jiaqi Lei , Sanjay Mehrotra

In this paper we study the redundancy of Huffman codes. In particular, we consider sources for which the probability of one of the source symbols is known. We prove a conjecture of Ye and Yeung regarding the upper bound on the redundancy of…

Information Theory · Computer Science 2016-11-17 Soheil Mohajer , Payam Pakzad , Ali Kakhbod

Bruss's odds theorem \cite{Bruss1} addresses the problem of determining the optimal stopping time for sequences of independent indicator functions. In this note, we derive upper and lower bounds for the success probability under the optimal…

Probability · Mathematics 2025-11-27 A. M. Kabaeva , A. V. Logachov , A. A. Yambartsev

In this paper q-ary Raptor codes under ML decoding are considered. An upper bound on the probability of decoding failure is derived using the weight enumerator of the outer code, or its expected weight enumerator if the outer code is drawn…

Information Theory · Computer Science 2016-11-21 Francisco Lázaro , Gianluigi Liva , Enrico Paolini , Gerhard Bauch

Convex sample approximations of chance-constrained optimization problems are considered, in which chance constraints are replaced by sets of sampled constraints. We propose a randomized sample selection strategy that allows tight bounds to…

Optimization and Control · Mathematics 2018-05-22 Mark Cannon

This paper addresses the problem of deciding the lower-boundedness of an arbitrary real polynomial p in n variables.

Optimization and Control · Mathematics 2025-12-01 Nguyen Hong Duc , Vu Trung Hieu

Consider the probability that a binomial random variable Bi$(n,m/n)$ with integer expectation $m$ is at most its expectation. Chv\'atal conjectured that for any given $n$, this probability is smallest when $m$ is the integer closest to…

Probability · Mathematics 2020-10-20 Svante Janson

This paper defines theoretical lower bounds of uncertainty of observations of macroeconomic variables that depend on statistical moments and correlations of random values and volumes of market trades. Any econometric assessments of…

General Economics · Economics 2024-10-08 Victor Olkhov

We prove polynomial upper and lower bounds on the expected size of the maximum agreement subtree of two random binary phylogenetic trees under both the uniform distribution and Yule-Harding distribution. This positively answers a question…

Populations and Evolution · Quantitative Biology 2015-09-01 Daniel Irving Bernstein , Lam Si Tung Ho , Colby Long , Mike Steel , Katherine St. John , Seth Sullivant

In this paper we establish lower bounds on information divergence of a distribution on the integers from a Poisson distribution. These lower bounds are tight and in the cases where a rate of convergence in the Law of Thin Numbers can be…

Probability · Mathematics 2016-01-19 Peter Harremoës , Oliver Johnson , Ioannis Kontoyiannis

We investigate the properties of a discrete-time martingale $\{X_m\}_{m\in \mathbb Z_{\geq 0}}$, where all differences between adjacent random variables are limited to be not more than a constant as a promise. In this situation, it is known…

Probability · Mathematics 2019-05-16 Go Kato

The existing upper and lower bounds between entropy and error probability are mostly derived from the inequality of the entropy relations, which could introduce approximations into the analysis. We derive analytical bounds based on the…

Information Theory · Computer Science 2012-05-31 Bao-Gang Hu , Hong-Jie Xing

This paper presents an achievability bound that evaluates the exact probability of error of an ensemble of random codes that are decoded by a minimum distance decoder. Compared to the state-of-the-art which demands exponential computation…

Information Theory · Computer Science 2023-05-17 Ioannis Papoutsidakis , Angela Doufexi , Robert J. Piechocki

In this paper we shall consider some famous means such as arithmetic, harmonic, geometric, root square mean, etc. Considering the difference of these means, we can establish. some inequalities among them. Interestingly, the difference of…

Information Theory · Computer Science 2011-03-29 Inder Jeet Taneja

Within the context of the binomial model, we analyse sequences of values that are almost-uniform and we discuss a prediction method called the frequent outcome approach, in which the outcome that has occurred the most in the observed trials…

Statistics Theory · Mathematics 2022-09-29 Ben O'Neill

When epidemiologic studies are conducted in a subset of the population, selection bias can threaten the validity of causal inference. This bias can occur whether or not that selected population is the target population, and can occur even…

Methodology · Statistics 2019-06-07 Louisa H. Smith , Tyler J. VanderWeele

This paper gives upper and lower bounds on the gap in Jensen's inequality, i.e., the difference between the expected value of a function of a random variable and the value of the function at the expected value of the random variable. The…

Probability · Mathematics 2020-08-21 Xiang Gao , Meera Sitharam , Adrian E. Roitberg

This paper studies the least upper bounds on coverage probabilities of the empirical likelihood ratio confidence regions based on estimating equations. The implications of the bounds on empirical likelihood inference are also discussed.

Statistics Theory · Mathematics 2007-06-13 Min Tsao