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The full width at half maximum (FWHM) is a useful quantity for characterizing the bandwidth of unimodal functions. However, a closed-form expression for the FWHM of gamma-shaped functions-i.e. functions that are shaped like the gamma…

Signal Processing · Electrical Eng. & Systems 2025-09-25 Anthony LoPrete , Johannes Burge

Importance weighting is a fundamental procedure in statistics and machine learning that weights the objective function or probability distribution based on the importance of the instance in some sense. The simplicity and usefulness of the…

Machine Learning · Computer Science 2024-05-15 Masanari Kimura , Hideitsu Hino

The Lindley distribution and its numerous generalizations are widely used in statistical and engineering practice. Recently, a power transformation of Lindley distribution, called the power Lindley distribution, has been introduced by M. E.…

Statistics Theory · Mathematics 2019-07-02 Mohammed Khalleefah , Sofiya Ostrovska , Mehmet Turan

Statistical prediction plays an important role in many decision processes such as university budgeting (depending on the number of students who will enroll), capital budgeting (depending on the remaining lifetime of a fleet of systems), the…

Methodology · Statistics 2021-10-14 Qinglong Tian , Daniel J. Nordman , William Q. Meeker

Application of the exact statistical inference frequently leads to a non-standard probability distributions of the considered estimators or test statistics. The exact distributions of many estimators and test statistics can be specified by…

Computation · Statistics 2018-01-09 Viktor Witkovský

In this work, we redefined two important statistics, the CLRT test (Bai et.al., Ann. Stat. 37 (2009) 3822-3840) and the LW test (Ledoit and Wolf, Ann. Stat. 30 (2002) 1081-1102) on identity tests for high dimensional data using random…

Methodology · Statistics 2013-04-12 Cheng Wang , Jing Yang , Baiqi Miao , Longbing Cao

Inference about a scalar parameter of interest is a core statistical task that has attracted immense research in statistics. The Wald statistic is a prime candidate for the task, on the grounds of the asymptotic validity of the standard…

Methodology · Statistics 2019-03-12 C. Di Caterina , I. Kosmidis

In this tutorial survey we recall the basic properties of the special function of the Mittag-Leffler and Wright type that are known to be relevant in processes dealt with the fractional calculus. We outline the major applications of these…

General Mathematics · Mathematics 2021-08-29 Francesco Mainardi

A new approach is presented for the calculation of p_n and pi_n which uses the Lambert W function. An approximation is first found and using a calculation technique it makes it possible to have an estimate of these two quantities more…

Number Theory · Mathematics 2020-06-04 Simon Plouffe

The likelihood function is central to both frequentist and Bayesian formulations of parametric statistical inference, and large-sample approximations to the sampling distributions of estimators and test statistics, and to posterior…

Methodology · Statistics 2022-04-05 Anthony C. Davison , Nancy Reid

The paper analyzes theoretically and empirically the performance of likelihood weighting (LW) on a subset of nodes in Bayesian networks. The proposed scheme requires fewer samples to converge due to reduction in sampling variance. The…

Artificial Intelligence · Computer Science 2012-07-02 Bozhena Bidyuk , Rina Dechter

The statistical decision theory pioneered by Wald (1950) has used state-dependent mean loss (risk) to measure the performance of statistical decision functions across potential samples. We think it evident that evaluation of performance…

Econometrics · Economics 2023-08-11 Charles F. Manski , Aleksey Tetenov

This brief note complements some results regarding a recently developed technique for the stability analysis of linear time-invariant, time delay systems using the matrix Lambert W function. By means of a numeric example, it is shown that…

Optimization and Control · Mathematics 2017-08-14 Rudy Cepeda-Gomez

Mathematical formulations and proofs for a wavelet based statistic employed in functional data analysis is elaborately discussed in this report. The propositions and derivations discussed here apply to a wavelet based statistic with hard…

Statistics Theory · Mathematics 2014-08-13 Senthil B. Girimurugan , Eric Chicken

This is an up-to-date introduction to, and overview of, marginal likelihood computation for model selection and hypothesis testing. Computing normalizing constants of probability models (or ratio of constants) is a fundamental issue in many…

Computation · Statistics 2023-02-13 Fernando Llorente , Luca Martino , David Delgado , Javier Lopez-Santiago

The established language for statistical testing --- significance levels, power, and p-values --- is overly complicated and deceptively conclusive. Even teachers of statistics and scientists who use statistics misinterpret the results of…

Statistics Theory · Mathematics 2019-10-23 Glenn Shafer

This paper offers a commentary on the use of notions of statistical significance in choice modelling. We review the reasons for uncertainty in parameter estimates, provide a precise discussion on the computation of measures of uncertainty…

Econometrics · Economics 2026-05-18 Stephane Hess , Andrew Daly , Michiel Bliemer , Angelo Guevara , Ricardo Daziano , Thijs Dekker

In this note, analysis of time delay systems using Lambert W function approach is reassessed. A common canonical form of time delay systems is defined. We extended the recent results of [6] for second order into nth order system. The…

Systems and Control · Computer Science 2017-09-05 Niraj Choudhary , Janardhanan Sivaramakrishnan , Indra Narayan Kar

In this paper we complete our understanding of the role played by the limiting (or residue) function in the context of mod-Gaussian convergence. The question about the probabilistic interpretation of such functions was initially raised by…

Probability · Mathematics 2014-09-10 Pierre-Loïc Méliot , Ashkan Nikeghbali

Recent work used importance sampling ideas for better variational bounds on likelihoods. We clarify the applicability of these ideas to pure probabilistic inference, by showing the resulting Importance Weighted Variational Inference (IWVI)…

Machine Learning · Computer Science 2018-10-30 Justin Domke , Daniel Sheldon