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We consider statistical inference for a finite-dimensional parameter in a regular semiparametric model under a distributed setting with blockwise missingness, where entire blocks of variables are unavailable at certain sites and sharing…

Methodology · Statistics 2025-08-26 Jingyue Huang , Huiyuan Wang , Yuqing Lei , Yong Chen

We introduce generalized notions of a divergence function and a Fisher information matrix. We propose to generalize the notion of an exponential family of models by reformulating it in terms of the Fisher information matrix. Our methods are…

Information Theory · Computer Science 2013-02-22 Jan Naudts , Ben Anthonis

While statistical learning methods have proved powerful tools for predictive modeling, the black-box nature of the models they produce can severely limit their interpretability and the ability to conduct formal inference. However, the…

Machine Learning · Statistics 2016-08-30 Lucas Mentch , Giles Hooker

Nonignorable missing outcomes are common in real world datasets and often require strong parametric assumptions to achieve identification. These assumptions can be implausible or untestable, and so we may forgo them in favour of partially…

Methodology · Statistics 2023-10-19 Daniel Daly-Grafstein , Paul Gustafson

In the article [B.J.West, Exact solution to fractional logistic equation, Physica A: Statistical Mechanics and its Applications 429 (2015) 103-108], the author has obtained a function as the solution to fractional logistic equation (FLE).…

Mathematical Physics · Physics 2018-04-24 Mirko D'Ovidio , Paola Loreti , Sima Sarv Ahrabi

We discuss how one-dimensional interacting fermion systems, which in the low energy approximation are described by Luttinger liquid theory, can be reformulated as systems of weakly interacting particles with fractional charge and…

Mesoscale and Nanoscale Physics · Physics 2017-04-26 Jon Magne Leinaas

We consider the problem of full information maximum likelihood (FIML) estimation in a factor analysis model when a majority of the data values are missing. The expectation-maximization (EM) algorithm is often used to find the FIML…

Computation · Statistics 2013-12-20 Kei Hirose , Sunyong Kim , Yutaka Kano , Miyuki Imada , Manabu Yoshida , Masato Matsuo

The joint probability distribution in the full counting statistics (FCS) for noninteracting electrons is discussed for an arbitrary number of initially separate subsystems which are connected at t=0 and separated at a later time. A simple…

Mesoscale and Nanoscale Physics · Physics 2015-05-13 L. Inhester , K. Schonhammer

A recent paper presents the "false confidence theorem" (FCT) which has potentially broad implications for statistical inference using Bayesian posterior uncertainty. This theorem says that with arbitrarily large (sampling/frequentist)…

Methodology · Statistics 2018-07-18 Iain Carmichael , Jonathan P Williams

Currently, there is renewed interest in the problem, raised by Shafer in 1985, of updating probabilities when observations are incomplete (or set-valued). This is a fundamental problem, and of particular interest for Bayesian networks.…

Artificial Intelligence · Computer Science 2014-08-08 Gert de Cooman , Marco Zaffalon

Although living organisms are affected by many interrelated and unidentified variables, this complexity does not automatically impose a fundamental limitation on statistical inference. Nor need one invoke such complexity as an explanation…

Data Analysis, Statistics and Probability · Physics 2013-02-06 Drew M. Thomas

This paper proposes an imputation procedure that uses the factors estimated from a tall block along with the re-rotated loadings estimated from a wide block to impute missing values in a panel of data. Assuming that a strong factor…

Econometrics · Economics 2021-08-13 Jushan Bai , Serena Ng

Fractional calculus is an effective tool in incorporating the effects of non-locality and memory into physical models. In this regard, successful applications exist rang- ing from signal processing to anomalous diffusion and quantum…

General Physics · Physics 2014-08-26 S. S. Bayin , J. P. Krisch

Recent developments in extracting and processing biological and clinical data are allowing quantitative approaches to studying living systems. High-throughput sequencing, expression profiles, proteomics, and electronic health records are…

Quantitative Methods · Quantitative Biology 2010-10-22 Vladimir Trifonov , Laura Pasqualucci , Riccardo Dalla-Favera , Raul Rabadan

Fractional equations have become the model of choice in several applications where heterogeneities at the microstructure result in anomalous diffusive behavior at the macroscale. In this work we introduce a new fractional operator…

Numerical Analysis · Mathematics 2021-01-29 Marta D'Elia , Christian Glusa

In spite of recent contributions to the literature, informative cluster size settings are not well known and understood. In this paper, we give a formal definition of the problem and describe it from different viewpoints. Data generating…

Statistics Theory · Mathematics 2018-03-06 Jaakko Nevalainen , Somnath Datta , Hannu Oja

Large-scale datasets are increasingly being used to inform decision making. While this effort aims to ground policy in real-world evidence, challenges have arisen as selection bias and other forms of distribution shifts often plague…

Methodology · Statistics 2023-11-07 Santiago Cortes-Gomez , Mateo Dulce , Carlos Patino , Bryan Wilder

In order to overcome the limitations of the original expression of the probability distribution appearing in literature of Incomplete Statistics, a new expression of the probability distribution is derived, where the Lagrange multiplier %B%…

Statistical Mechanics · Physics 2007-05-23 ZhiFu Huang , Bihong Lin , Jincan Chen

Fractional scoring has been proposed to avoid inconsistencies in the attribution of publications to percentile rank classes. Uncertainties and ambiguities in the evaluation of percentile ranks can be demonstrated most easily with small…

Digital Libraries · Computer Science 2013-03-25 Michael Schreiber

We consider problems in which a system receives external \emph{perturbations} from time to time. For instance, the system can be a train network in which particular lines are repeatedly disrupted without warning, having an effect on…

Machine Learning · Computer Science 2019-08-21 Nicolo Colombo , Ricardo Silva , Soong M Kang , Arthur Gretton
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