English
Related papers

Related papers: An Alternative Discrete Skew Logistic Distribution

200 papers

Regression analysis with probability measures as input predictors and output response has recently drawn great attention. However, it is challenging to handle multiple input probability measures due to the non-flat Riemannian geometry of…

Methodology · Statistics 2024-05-23 Xiaoyu Chen , Mengfan Fu , Yujing Huang , Xinwei Deng

We present DUAL-LOCO, a communication-efficient algorithm for distributed statistical estimation. DUAL-LOCO assumes that the data is distributed according to the features rather than the samples. It requires only a single round of…

Machine Learning · Statistics 2016-08-04 Christina Heinze , Brian McWilliams , Nicolai Meinshausen

We develop two novel approaches for constructing skewed and bimodal flexible distributions that can effectively generalize classical symmetric distributions. We illustrate the application of introduced techniques by extending normal,…

Methodology · Statistics 2021-07-01 Jamil Ownuk , Ahmad Nezakati , Hossein Baghishani

The discrete moment problem is a foundational problem in distribution-free robust optimization, where the goal is to find a worst-case distribution that satisfies a given set of moments. This paper studies the discrete moment problems with…

Optimization and Control · Mathematics 2017-08-08 Xi Chen , Simai He , Bo Jiang , Christopher Thomas Ryan , Teng Zhang

We propose new numerical approach to non-conservative dynamical systems. Our method being of low order, enhances qualitative performance of standard discrete gradient algorithm, thank to new concept of a reservoir. Paper is of explanatory…

Numerical Analysis · Mathematics 2020-02-18 Artur Kobus

We study the problem of predicting numeric labels that are constrained to the integers or to a subrange of the integers. For example, the number of up-votes on social media posts, or the number of bicycles available at a public rental…

Machine Learning · Computer Science 2026-04-14 Bas Maat , Peter Bloem

We present a new algorithm to optimize distributions defined implicitly by parameterized stochastic diffusions. Doing so allows us to modify the outcome distribution of sampling processes by optimizing over their parameters. We introduce a…

We propose to solve a constrained distribution steering problem, i.e., steering a stochastic linear system from an initial distribution to some final, desired distribution subject to chance constraints. We do so by characterizing the…

Optimization and Control · Mathematics 2021-10-14 Vignesh Sivaramakrishnan , Joshua Pilipovsky , Meeko M. K. Oishi , Panagiotis Tsiotras

We introduce a general class of continuous univariate distributions with positive support obtained by transforming the class of two-piece distributions. We show that this class of distributions is very flexible, easy to implement, and…

Applications · Statistics 2015-11-06 Francisco J. Rubio , Yili Hong

Adaptive importance sampling is a class of techniques for finding good proposal distributions for importance sampling. Often the proposal distributions are standard probability distributions whose parameters are adapted based on the…

Computation · Statistics 2021-03-10 Topi Paananen , Juho Piironen , Paul-Christian Bürkner , Aki Vehtari

Estimating copulas with discrete marginal distributions is challenging, especially in high dimensions, because computing the likelihood contribution of each observation requires evaluating $2^{J}$ terms, with $J$ the number of discrete…

Methodology · Statistics 2018-11-12 D. Gunawan , M. -N. Tran , K. Suzuki , J. Dick , R. Kohn

Using offline observational data for policy evaluation and learning allows decision-makers to evaluate and learn a policy that connects characteristics and interventions. Most existing literature has focused on either discrete treatment…

Artificial Intelligence · Computer Science 2025-01-22 Cheuk Hang Leung , Yiyan Huang , Yijun Li , Qi Wu

We propose a new approach for estimating the parameters of a probability distribution. It consists on combining two new methods of estimation. The first is based on the definition of a new distance measuring the difference between…

Methodology · Statistics 2008-12-30 Ahmed Guellil , Tewfik Kernane

This article proposes a new class of Real Elliptically Skewed (RESK) distributions and associated clustering algorithms that allow for integrating robustness and skewness into a single unified cluster analysis framework. Non-symmetrically…

Signal Processing · Electrical Eng. & Systems 2021-07-05 Christian A. Schroth , Michael Muma

Several probability distributions have been proposed in the literature, especially with the aim of obtaining models that are more flexible relative to the behaviors of the density and hazard rate functions. Recently, a new generalization of…

Computation · Statistics 2016-04-26 K. V. P. Barco , J. Mazucheli , V. Janeiro

Sampling is an important tool for estimating large, complex sums and integrals over high dimensional spaces. For instance, important sampling has been used as an alternative to exact methods for inference in belief networks. Ideally, we…

Artificial Intelligence · Computer Science 2013-01-18 Luis E. Ortiz , Leslie Pack Kaelbling

We consider the problem of inference in shift-share research designs. The choice between existing approaches that allow for unrestricted spatial correlation involves tradeoffs, varying in terms of their validity when there are relatively…

Econometrics · Economics 2022-06-03 Luis Alvarez , Bruno Ferman , Raoni Oliveira

In this paper we develop a statistical theory and an implementation of deep learning models. We show that an elegant variable splitting scheme for the alternating direction method of multipliers optimises a deep learning objective. We allow…

Machine Learning · Statistics 2015-09-22 Nicholas G. Polson , Brandon T. Willard , Massoud Heidari

Exponential random graph models are an important tool in the statistical analysis of data. However, Bayesian parameter estimation for these models is extremely challenging, since evaluation of the posterior distribution typically involves…

Computation · Statistics 2017-05-05 Lampros Bouranis , Nial Friel , Florian Maire

This paper presents a new methodology for generating continuous statistical distributions, integrating the exponentiated odds ratio within the framework of survival analysis. This new method enhances the flexibility and adaptability of…

Statistics Theory · Mathematics 2024-02-28 Xinyu Chen , Yuanqi Xie , Achraf Cohen , Shusen Pu