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This paper introduces an expectation-maximization (EM) algorithm within a wavelet domain Bayesian framework for semi-blind channel estimation of multiband OFDM based UWB communications. A prior distribution is chosen for the wavelet…

Networking and Internet Architecture · Computer Science 2007-08-13 Sajad Sadough , Mahieddine Ichir , Emmanuel Jaffrot , Pierre Duhamel

Expectation maximisation (EM) is an unsupervised learning method for estimating the parameters of a finite mixture distribution. It works by introducing "hidden" or "latent" variables via Baum's auxiliary function $Q$ that allow the joint…

Machine Learning · Computer Science 2022-05-19 Graham W. Pulford

Censored quantile regression has emerged as a prominent alternative to classical Cox's proportional hazards model or accelerated failure time model in both theoretical and applied statistics. While quantile regression has been extensively…

Methodology · Statistics 2024-08-27 Taehwa Choi , Seohyeon Park , Hunyong Cho , Sangbum Choi

Many modern products are highly reliable, often exhibiting long lifetimes. As a result, conducting experiments under normal operating conditions can be prohibitively time-consuming to collect sufficient failure data for robust statistical…

Methodology · Statistics 2026-03-31 María Jaenada , Juan Millán , Leandro Pardo

In the present paper, Probability weighted moments (PWMs) method for parameter estimation of the median based unit weibull (MBUW) distribution is discussed. The most widely used first order PWMs is compared with the higher order PWMs for…

Methodology · Statistics 2025-11-20 Iman Mohammed Attia

Based on independent progressively Type-II censored samples from two-parameter Rayleigh distributions with the same location parameter but different scale parameters, the UMVUE and maximum likelihood estimator of $R=P(Y<X)$ are obtained.…

Applications · Statistics 2017-09-05 Akram Kohansal , Saeid Rezakhah

Nowadays, the confidentiality of data and information is of great importance for many companies and organizations. For this reason, they may prefer not to release exact data, but instead to grant researchers access to approximate data. For…

Methodology · Statistics 2021-12-24 Zahra A. Shirazi , João Pedro A. R. da Silva , Camila P. E. de Souza

In this paper, we focus on the parametric inference based on the Tampered Random Variable (TRV) model for simple step-stress life testing (SSLT) using Type-II censored data. The baseline lifetime of the experimental units, under normal…

Methodology · Statistics 2023-02-20 Subhankar Dutta , Farha Sultana , Suchandan Kayal

This paper presents a unified and novel estimation framework for the Weibull, Gamma, and Log-normal distributions based on arbitrary-order moment pairs. Traditional estimation techniques, such as Maximum Likelihood Estimation (MLE) and the…

Methodology · Statistics 2025-05-06 Kang Liu

The Student-$t$ distribution is widely used in statistical modeling of datasets involving outliers since its longer-than-normal tails provide a robust approach to hand such data. Furthermore, data collected over time may contain censored or…

This paper develops a Bayesian control chart for the percentiles of the Weibull distribution, when both its in-control and out-of-control parameters are unknown. The Bayesian approach enhances parameter estimates for small sample sizes that…

Methodology · Statistics 2013-08-06 Pasquale Erto , Giuliana Pallotta , Christina M. Mastrangelo

We introduce a new multivariate circular linear distribution suitable for modeling direction and speed in (multiple) animal movement data. To properly account for specific data features, such as heterogeneity and time dependence, a hidden…

Applications · Statistics 2016-06-28 Gianluca Mastrantonio

We propose sequential Monte Carlo based algorithms for maximum likelihood estimation of the static parameters in hidden Markov models with an intractable likelihood using ideas from approximate Bayesian computation. The static parameter…

Computation · Statistics 2013-11-19 Sinan Yildirim , Sumeetpal Singh , Thomas Dean , Ajay Jasra

In this paper, a new three-parameter lifetime distribution is introduced and many of its standard properties are discussed. These include shape of the probability density function, hazard rate function and its shape, quantile function,…

Methodology · Statistics 2013-08-21 Min Wang

Interval-censored covariates are frequently encountered in biomedical studies, particularly in time-to-event data or when measurements are subject to detection or quantification limits. Yet, the estimation of regression models with…

Methodology · Statistics 2026-01-15 Andrea Toloba , Klaus Langohr , Guadalupe Gómez Melis

In this paper, distributed Bayesian detection problems with unknown prior probabilities of hypotheses are considered. The sensors obtain observations which are conditionally dependent across sensors and their probability density functions…

Information Theory · Computer Science 2012-09-20 Xiaojing Shen , Pramod K. Varshney , Yunmin Zhu

Weibull distribution is widely used in modelling health data. However, its lack of sufficient tail flexibility often results in poor fit in extreme events. We proposed another three-parameter extension of the Weibull distribution with…

Methodology · Statistics 2026-04-07 Isqeel Ogunsola , Nurudeen Ajadi , Gboyega Adepoju

In transportation, Weigh-in motion (WIM) stations, Electronic Toll Collection (ETC) systems, Closed-circuit Television (CCTV) are widely deployed to collect data at different locations. Vehicle re-identification, by matching the same…

Applications · Statistics 2024-11-06 Diyi Liu , Yangsong Gu , Lee D. Han

This paper considers estimation and inference about tail features when the observations beyond some threshold are censored. We first show that ignoring such tail censoring could lead to substantial bias and size distortion, even if the…

Econometrics · Economics 2020-02-25 Yulong Wang , Zhijie Xiao

We develop a maximum likelihood estimating approach for time-to-event Weibull regression models with outcome-dependent sampling, where sampling of subjects is dependent on the residual fraction of the time left to developing the event of…

Applications · Statistics 2014-08-01 Brian D. M. Tom , Vernon T. Farewell , Sheila M. Bird
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