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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…

In the paper we analyse dependence structures among international trade flows of major conventional weapons from 1952 to 2016. We employ a Network Disturbance Model commonly used in inferential network analysis and spatial econometrics. The…

Applications · Statistics 2018-03-12 Michael Lebacher , Göran Kauermann

In this paper we propose to extend the separable temporal exponential random graph model (STERGM) to account for time-varying network- and actor-specific effects. Our application case is the network of international major conventional…

Applications · Statistics 2019-09-05 Michael Lebacher , Paul W. Thurner , Göran Kauermann

When data are collected subject to a detection limit, observations below the detection limit may be considered censored. In addition, the domain of such observations may be restricted; for example, values may be required to be non-negative.…

Applications · Statistics 2020-06-30 Justin R. Williams , Hyung-Woo Kim , Catherine M. Crespi

In many fields of study, we only observe lower bounds on the true response value of some experiments. When fitting a regression model to predict the distribution of the outcomes, we cannot simply drop these right-censored observations, but…

Artificial Intelligence · Computer Science 2020-09-30 Katharina Eggensperger , Kai Haase , Philipp Müller , Marius Lindauer , Frank Hutter

This paper considers doing quantile regression on censored data using neural networks (NNs). This adds to the survival analysis toolkit by allowing direct prediction of the target variable, along with a distribution-free characterisation of…

Machine Learning · Statistics 2023-02-07 Tim Pearce , Jong-Hyeon Jeong , Yichen Jia , Jun Zhu

We propose a novel tie-oriented model for longitudinal event network data. The generating mechanism is assumed to be a multivariate Poisson process that governs the onset and repetition of yearly observed events with two separate intensity…

Applications · Statistics 2021-09-28 Cornelius Fritz , Paul W. Thurner , Göran Kauermann

Inferring the true demand for a product or a service from aggregate data is often challenging due to the limited available supply, thus resulting in observations that are censored and correspond to the realized demand, thereby not…

Machine Learning · Computer Science 2025-01-22 Filipe Rodrigues

The study of international relations by definition deals with interdependencies among countries. One form of interdependence between countries is the diffusion of country-level features, such as policies, political regimes, or conflict. In…

Applications · Statistics 2019-03-22 Johan A. Elkink , Thomas U. Grund

Jointly modeling and forecasting economic and financial variables across a large set of countries has long been a significant challenge. Two primary approaches have been utilized to address this issue: the vector autoregressive model with…

Machine Learning · Statistics 2025-03-12 Sanyou Wu , Dan Yang , Yan Xu , Long Feng

We develop a unified approach for classification and regression support vector machines for data subject to right censoring. We provide finite sample bounds on the generalization error of the algorithm, prove risk consistency for a wide…

Machine Learning · Statistics 2013-01-15 Yair Goldberg , Michael R. Kosorok

Insider trading is one of the numerous white collar crimes that can contribute to the instability of the economy. Traditionally, the detection of illegal insider trades has been a human-driven process. In this paper, we collect the insider…

Social and Information Networks · Computer Science 2017-02-21 Adarsh Kulkarni , Priya Mani , Carlotta Domeniconi

The problem of estimating censored linear regression models with autocorrelated errors arises in many environmental and social studies. The present work proposes a Bayesian approach to estimate censored regression models with AR(p) errors.…

Methodology · Statistics 2023-01-06 Rodney Sousa , Isabel Pereira , Maria Eduarda Silva , Brendan McCabe

Distributional effects, captured by quantile frameworks, are well-received for characterizing heterogeneous impacts of economic factors across the unobserved relative ranks. Censored outcome, endogenous regressor and heteroskedastic error…

Econometrics · Economics 2026-04-06 Xi Wang

When modelling censored observations, a typical approach in current regression methods is to use a censored-Gaussian (i.e. Tobit) model to describe the conditional output distribution. In this paper, as in the case of missing data, we argue…

Machine Learning · Statistics 2022-05-05 Daniele Gammelli , Kasper Pryds Rolsted , Dario Pacino , Filipe Rodrigues

Automated visual firearms classification from RGB images is an important real-world task with applications in public space security, intelligence gathering and law enforcement investigations. When applied to images massively crawled from…

Computer Vision and Pattern Recognition · Computer Science 2024-02-07 Sotirios Konstantakos , Despina Ioanna Chalkiadaki , Ioannis Mademlis , Adamantia Anna Rebolledo Chrysochoou , Georgios Th. Papadopoulos

In this paper we propose a bimodal gamma distribution using a quadratic transformation based on the alpha-skew-normal model. We discuss several properties of this distribution such as mean, variance, moments, hazard rate and entropy…

Methodology · Statistics 2020-05-08 R. Vila , L. Ferreira , H. Saulo , F. Prataviera , E. M. M. Ortega

We propose and study M-estimation to estimate the parameters in the censored regression model in the presence of endogeneity, i.e., the Tobit model. In the course of this study, we follow two-stage procedures: the first stage consists of…

Methodology · Statistics 2025-05-13 Swati Shukla , Subhra Sankar Dhar , Shalabh

Multiple-input multiple-output (MIMO) radar systems have been shown to achieve superior resolution as compared to traditional radar systems with the same number of transmit and receive antennas. This paper considers a distributed MIMO radar…

Information Theory · Computer Science 2016-11-15 Yao Yu , Athina P. Petropulu , H. Vincent Poor

Lomax distribution has been widely used in economics, business and actuarial sciences. Due to its importance, we consider the statistical inference of this model under joint type-II censoring scenario. In order to estimate the parameters,…

Statistics Theory · Mathematics 2019-12-06 Yasin Asar , R. Arabi Belaghi
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