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Related papers: On Identifying a Massive Number of Distributions

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We study a special case of the problem of statistical learning without the i.i.d. assumption. Specifically, we suppose a learning method is presented with a sequence of data points, and required to make a prediction (e.g., a classification)…

Machine Learning · Computer Science 2018-05-22 Steve Hanneke , Liu Yang

Denote by $\mathbb{N}$ and $\mathbb{P}$ the set of all positive integers and prime numbers, respectively. Let $\mathbb{P}=\{p_1<p_2<\dots <p_n<\dots\}$, where $p_n$ is the $n$-th prime number. For $k\in\mathbb{N}$ we recursively define…

Number Theory · Mathematics 2022-01-06 Piotr Miska , János T. Tóth , Błażej Żmija

Commonly observed patterns typically follow a few distinct families of probability distributions. Over one hundred years ago, Karl Pearson provided a systematic derivation and classification of the common continuous distributions. His…

Probability · Mathematics 2011-02-28 Steven A. Frank , Eric Smith

Let X_1,...., X_n be a collection of iid discrete random variables, and Y_1,..., Y_m a set of noisy observations of such variables. Assume each observation Y_a to be a random function of some a random subset of the X_i's, and consider the…

Information Theory · Computer Science 2007-09-04 Andrea Montanari

The distribution of differences of consecutive members of sequences of primes is investigated. A quantitative measure for oscillations among these differences is the curvature of the sequence. If the sequence is not too sparse, then sharp…

Number Theory · Mathematics 2017-02-02 Jörg Brüdern , Christian Elsholtz

Given only aggregate choice data and limited information about how menus are distributed across the population, we describe what can be inferred robustly about the distribution of preferences (or more general decision rules). We strengthen…

Theoretical Economics · Economics 2024-05-16 Larry G Epstein , Kaushil Patel

Given a set of independent Poisson random variables with common mean, we study the distribution of their maximum and obtain an accurate asymptotic formula to locate the most probable value of the maximum. We verify our analytic results with…

Probability · Mathematics 2009-03-26 K. M. Briggs , L. Song , T. Prellberg

We consider the estimation of the mixing distribution of a normal distribution where both the shift and scale are unobserved random variables. We argue that in general, the model is not identifiable. We give an elegant non-constructive…

Statistics Theory · Mathematics 2024-08-20 Ya'acov Ritov

The problem of reconstructing a sequence of independent and identically distributed symbols from a set of equal size, consecutive, fragments, as well as a dependent reference sequence, is considered. First, in the regime in which the…

Information Theory · Computer Science 2023-07-20 Nir Weinberger , Ilan Shomorony

The relationship between three probability distributions and their maximizable entropy forms is discussed without postulating entropy property. For this purpose, the entropy I is defined as a measure of uncertainty of the probability…

Statistical Mechanics · Physics 2020-10-28 Qiuping A. Wang

We consider the best-choice problem for independent (not necessarily iid) observations $X_1, \cdots, X_n$ with the aim of selecting the sample minimum. We show that in this full generality the monotone case of optimal stopping holds and the…

Probability · Mathematics 2021-10-13 Alexander Gnedin , Patryk Kozieł , Małgorzata Sulkowska

The distribution of frequency counts of distinct words by length in a language's vocabulary will be analyzed using two methods. The first, will look at the empirical distributions of several languages and derive a distribution that…

Computation and Language · Computer Science 2012-07-17 Reginald D. Smith

Multiplicity distributions, P(N), provide valuable information on the mechanism of the production process. We argue that the observed P(N) contain more information (located in the small N region) than expected and used so far. We…

High Energy Physics - Phenomenology · Physics 2019-06-06 M. Rybczyński , G. Wilk , Z. Włodarczyk

We study the best-choice problem for processes which generalise the process of records from Poisson-paced i.i.d. observations. Under the assumption that the observer knows distribution of the process and the horizon, we determine the…

Probability · Mathematics 2007-05-23 Alexander Gnedin

To infer a diffusion network based on observations from historical diffusion processes, existing approaches assume that observation data contain exact occurrence time of each node infection, or at least the eventual infection statuses of…

Social and Information Networks · Computer Science 2023-12-14 Hao Huang , Qian Yan , Keqi Han , Ting Gan , Jiawei Jiang , Quanqing Xu , Chuanhui Yan

Pyrosequencing is emerging as one of the important next-generation sequencing technologies. We derive the statistical distributions of this technique in terms of nucleotide probabilities of the target sequences. We give exact distributions…

Genomics · Quantitative Biology 2024-05-28 Yong Kong

We investigate the probability of observing a given pattern of $n$ rises and falls in a random stationary data series. The data are modelled as a sequence of $n+1$ independent and identically distributed random numbers. This probabilistic…

Statistical Mechanics · Physics 2014-04-29 J M Luck

With reference to a previous work, the problem of the experimental detection of non-causal synordination patterns between two series of physical events is examined. It is necessary that the patterns in question act in a reproducible, or at…

General Physics · Physics 2008-07-22 Leonardo Chiatti

We consider the problem of hypothesis testing for discrete distributions. In the standard model, where we have sample access to an underlying distribution $p$, extensive research has established optimal bounds for uniformity testing,…

Machine Learning · Computer Science 2024-12-03 Maryam Aliakbarpour , Piotr Indyk , Ronitt Rubinfeld , Sandeep Silwal

In counting experiments, one can set an upper limit on the rate of a Poisson process based on a count of the number of events observed due to the process. In some experiments, one makes several counts of the number of events, using…

Data Analysis, Statistics and Probability · Physics 2014-11-20 Patrick J. Sutton
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