English
Related papers

Related papers: Minimum Density Power Divergence Estimation for th…

200 papers

The stochastic differential equation (SDE)-based random process models of volatile renewable energy sources (RESs) jointly capture the evolving probability distribution and temporal correlation in continuous time. It has enabled recent…

Machine Learning · Computer Science 2023-12-12 Yiwei Qiu , Jin Lin , Zhipeng Zhou , Ningyi Dai , Feng Liu , Yonghua Song

The Power Generalized DUS (PGDUS) Transformation is significant in reliability theory, especially for analyzing parallel systems. From the Generalized Extreme Value distribution, Inverse Weibull model particularly has wide applicability in…

Methodology · Statistics 2025-04-18 P Gauthami , V M Chacko

We analyse the probability densities of daily rainfall amounts at a variety of locations on the Earth. The observed distributions of the amount of rainfall fit well to a q-exponential distribution with exponent q close to q=1.3. We discuss…

Statistical Mechanics · Physics 2016-03-10 G. Cigdem Yalcin , Pau Rabassa , Christian Beck

Assuming an exponential power distribution is one way to deal with outliers in regression and clustering, which can increase the robustness of the analysis. Gaussian distribution is a special case of an exponential distribution. And an…

Methodology · Statistics 2020-12-22 Xiao Chen

In recent years traditional numerical methods for accurate weather prediction have been increasingly challenged by deep learning methods. Numerous historical datasets used for short and medium-range weather forecasts are typically organized…

Machine Learning · Computer Science 2023-09-06 Andrea Asperti , Fabio Merizzi , Alberto Paparella , Giorgio Pedrazzi , Matteo Angelinelli , Stefano Colamonaco

Covariance matrix estimation is an important problem in multivariate data analysis, both from theoretical as well as applied points of view. Many simple and popular covariance matrix estimators are known to be severely affected by model…

Methodology · Statistics 2025-11-21 Soumya Chakraborty , Ayanendranath Basu , Abhik Ghosh

The heavy-tailed behavior of the generalized extreme-value distribution makes it a popular choice for modeling extreme events such as floods, droughts, heatwaves, wildfires, etc. However, estimating the distribution's parameters using…

Rain introduces broadband and frequency-selective attenuation in wideband terahertz (THz) links, making it necessary to identify a compact spectral descriptor that captures how the dominant loss region evolves with rainfall conditions. This…

Applied Physics · Physics 2026-04-20 Yuheng Song , Wanzhu Chang , Kefeng Huang , Kaixin Sun , Chen Yao , Jianjun Ma

This paper develops a robust parametric framework for jump detection in discretely observed CKLS-type jump-diffusion processes with high-frequency asymptotics, based on the minimum density power divergence estimator (MDPDE). The methodology…

Statistical Finance · Quantitative Finance 2026-03-06 Sourojyoti Barick

The increasing frequency of extreme weather events poses significant risks to power distribution systems, leading to widespread outages and severe economic and social consequences. This paper presents a novel simulation framework for…

Systems and Control · Electrical Eng. & Systems 2025-02-13 Xuesong Wang , Shuo Yuan , Sharaf K. Magableh , Oraib Dawaghreh , Caisheng Wang , Le Yi Wang

We carry out a study of the statistical distribution of rainfall precipitation data for 20 cites in India. We have determined the best-fit probability distribution for these cities from the monthly precipitation data spanning 100 years of…

Applications · Statistics 2018-08-20 Anumandla Sukrutha , Sristi Ram Dyuthi , Shantanu Desai

In testing of hypothesis the robustness of the tests is an important concern. Generally, the maximum likelihood based tests are most efficient under standard regularity conditions, but they are highly non-robust even under small deviations…

Methodology · Statistics 2018-05-01 Ayanendranath Basu , Abhijit Mandal , Nirian Martin , Leandro Pardo

Many modern products exhibit high reliability under normal operating conditions. Conducting life tests under these conditions may result in very few observed failures, insufficient for accurate inferences. Instead, accelerated life tests…

Applications · Statistics 2024-09-25 Narayanaswamy Balakrishnan , María Jaenada , Leandro Pardo

Frequent significant deviations of the observed magnitude distribution of anthropogenic seismicity from the Gutenberg-Richter relation require alternative estimation methods for probabilistic seismic hazard assessments. We evaluate five…

Geophysics · Physics 2025-12-22 Francis Tong , Stanisław Lasocki , Beata Orlecka-Sikora

The Mutual Information (MI) is an often used measure of dependency between two random variables utilized in information theory, statistics and machine learning. Recently several MI estimators have been proposed that can achieve parametric…

Information Theory · Computer Science 2018-11-26 Morteza Noshad , Yu Zeng , Alfred O. Hero

Improving the representation of precipitation in Earth system models (ESMs) is critical for assessing the impacts of climate change and especially of extreme events like floods and droughts. In existing ESMs, precipitation is not resolved…

Machine Learning · Computer Science 2026-05-27 Michael Aich , Sebastian Bathiany , Philipp Hess , Yu Huang , Niklas Boers

Let $X_1,\ldots,X_n$ be a random sample from the Gamma distribution with density $f(x)=\lambda^{\alpha}x^{\alpha-1}e^{-\lambda x}/\Gamma(\alpha)$, $x>0$, where both $\alpha>0$ (the shape parameter) and $\lambda>0$ (the reciprocal scale…

Statistics Theory · Mathematics 2022-05-24 Nickos Papadatos

This article aims to introduced a new lifetime distribution named as exponentiated xgamma distribution (EXGD). The new generalization obtained from xgamma distribution, a special finite mixture of exponential and gamma distributions. The…

Statistics Theory · Mathematics 2018-10-22 Abhimanyu Singh Yadav , Mahendra Saha , Harsh Tripathi , Sumit Kumar

We establish consistency and asymptotic normality of the minimum density power divergence estimator under regularity conditions different from those originally provided by Basu et al.

Statistics Theory · Mathematics 2016-08-16 Sergio F. Juárez , William R. Schucany

Maximum entropy reinforcement learning (MaxEnt-RL) has become the standard approach to RL due to its beneficial exploration properties. Traditionally, policies are parameterized using Gaussian distributions, which significantly limits their…

Machine Learning · Computer Science 2025-06-11 Onur Celik , Zechu Li , Denis Blessing , Ge Li , Daniel Palenicek , Jan Peters , Georgia Chalvatzaki , Gerhard Neumann