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This paper discusses phase retrieval algorithms for maximum likelihood (ML) estimation from measurements following independent Poisson distributions in very low-count regimes, e.g., 0.25 photon per pixel. To maximize the log-likelihood of…

Information Theory · Computer Science 2022-09-27 Zongyu Li , Kenneth Lange , Jeffrey A. Fessler

Estimates are constructed for the deviation of the concentration functions of sums of independent random variables with finite variances from the folded normal distribution function without any assumptions concerning the existence of the…

Probability · Mathematics 2016-08-11 V. Yu. Korolev , A. V. Dorofeeva

For $f$ a Steinhaus random multiplicative function, we prove convergence in distribution of the appropriately normalised partial sums \[ \frac{{(\log \log x)}^{1/4}}{\sqrt{x}} \sum_{\substack{n \leq x \\ P(n) > \sqrt{x}}} f(n), \] where…

Number Theory · Mathematics 2025-03-11 Seth Hardy

In this paper, we define a fractional negative binomial process (FNBP) by replacing the Poisson process by a fractional Poisson process (FPP) in the gamma subordinated form of the negative binomial process. First, it is shown that the…

Probability · Mathematics 2014-10-08 P. Vellaisamy , A. Maheshwari

In this work, we prove the joint convergence in distribution of $q$ variables modulo one obtained as partial sums of a sequence of i.i.d. square integrable random variables multiplied by a common factor given by some function of an…

Probability · Mathematics 2023-08-08 Roberta Flenghi , Benjamin Jourdain

Nonnegative Matrix Factorization (NMF) with Kullback-Leibler Divergence (NMF-KL) is one of the most significant NMF problems and equivalent to Probabilistic Latent Semantic Indexing (PLSI), which has been successfully applied in many…

Optimization and Control · Mathematics 2016-04-15 Duy Khuong Nguyen , Tu Bao Ho

This paper compares six different parameter estimation methods for shared frailty models via a series of simulation studies. A shared frailty model is a survival model that incorporates a random effect term, where the frailties are common…

Methodology · Statistics 2023-11-21 Tingxuan Wu , Cindy Feng , Longhai Li

The purpose of this article is to develop a general parametric estimation theory that allows the derivation of the limit distribution of estimators in non-regular models where the true parameter value may lie on the boundary of the…

Statistics Theory · Mathematics 2022-11-28 Junichiro Yoshida , Nakahiro Yoshida

Using the LePage representation, a strictly stable random element in a Banach space with $\alpha\in(0,2)$ can be represented as a sum of points of a Poisson process. This point process is union-stable, i.e. the union of its two independent…

Probability · Mathematics 2007-05-23 Youri Davydov , Ilya Molchanov , Sergei Zuyev

The paper examines the Fractional Fourier Transform (FRFT) based technique as a tool for obtaining probability density function and its derivatives, and mainly for fitting stochastic model with the fundamental probabilistic relationships of…

Methodology · Statistics 2021-07-13 A. H. Nzokem

The Landau-Selberg-Delange method provides an asymptotic formula for the partial sums of a multiplicative function whose average value on primes is a fixed complex number $v$. The shape of this asymptotic implies that $f$ can get very small…

Number Theory · Mathematics 2020-05-13 Dimitris Koukoulopoulos , K. Soundararajan

Fractional Poisson processes, a rapidly growing area of non-Markovian stochastic processes, are useful in statistics to describe data from counting processes when waiting times are not exponentially distributed. We show that the fractional…

Classical Analysis and ODEs · Mathematics 2013-10-14 Markus Kreer , Ayse Kizilersu , Anthony W. Thomas

We study the nonparametric maximum likelihood estimator (NPMLE) for Gaussian and Poisson mixture models, assuming the support of the true mixing distribution lies in a fixed bounded set. In this setting, we establish exact parametric rates…

Statistics Theory · Mathematics 2026-04-15 Yan Zhang , Stanislav Volgushev

For a measure preserving transformation $T$ of a probability space $(X,\mathcal F,\mu)$ we investigate almost sure and distributional convergence of random variables of the form $$x \to \frac{1}{C_n} \sum_{i_1<n,...,i_d<n}…

Dynamical Systems · Mathematics 2014-12-03 Manfred Denker , Mikhail Gordin

A multivariate fractional Poisson process was recently defined in Beghin and Macci (2016) by considering a common independent random time change for a finite dimensional vector of independent (non-fractional) Poisson processes; moreover it…

Probability · Mathematics 2016-09-13 Luisa Beghin , Claudio Macci

This paper introduces the Non-homogeneous Generalized Skellam process (NGSP) and its fractional version NGFSP by time changing it with an independent inverse stable subordinator. We study distributional properties for NGSP and NGFSP…

Probability · Mathematics 2025-09-23 Kartik Tathe , Sayan Ghosh

In this paper we consider the fractional parts of a general sequence, for example the sequence $\alpha \sqrt{n}$ or $\alpha n^2$. We give a general method, which allows one to show that long-range correlations (correlations where the…

Dynamical Systems · Mathematics 2020-07-21 Christopher Lutsko

This paper proposes a new generalized linear model with the fractional binomial distribution. Zero-inflated Poisson/negative binomial distributions are used for count data with many zeros. To analyze the association of such a count variable…

Methodology · Statistics 2025-08-01 Jeonghwa Lee , Chloe Breece

We study mixture of linear regression (random coefficient) models, which capture population heterogeneity by allowing the regression coefficients to follow an unknown distribution $G^*$. In contrast to common parametric methods that fix the…

Methodology · Statistics 2025-07-01 Hansheng Jiang , Adityanand Guntuboyina

We consider predictions of the random number and the magnitude of each iid component in a random sum based on its distributional structure, where only a total value of the sum is available and where iid random components are non-negative.…

Probability · Mathematics 2015-07-13 Muneya Matsui
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