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Large language model post-training relies on reinforcement learning to improve model capability and alignment quality. However, the off-policy training paradigm introduces distribution shift, which often pushes the policy beyond the trust…

Machine Learning · Computer Science 2026-04-24 Zhenpeng Su , Leiyu Pan , Minxuan Lv , Tiehua Mei , Zijia Lin , Yuntao Li , Wenping Hu , Ruiming Tang , Kun Gai , Guorui Zhou

In this paper, we introduce a flexible and widely applicable nonparametric entropy-based testing procedure that can be used to assess the validity of simple hypotheses about a specific parametric population distribution. The testing…

Econometrics · Economics 2022-01-19 Ron Mittelhammer , George Judge , Miguel Henry

Following the theory of information measures based on the cumulative distribution function, we propose the fractional generalized cumulative entropy, and its dynamic version. These entropies are particularly suitable to deal with…

Probability · Mathematics 2021-06-30 Antonio Di Crescenzo , Suchandan Kayal , Alessandra Meoli

Dealing with distribution shifts is one of the central challenges for modern machine learning. One fundamental situation is the covariate shift, where the input distributions of data change from training to testing stages while the…

Machine Learning · Computer Science 2024-05-28 Yu-Jie Zhang , Zhen-Yu Zhang , Peng Zhao , Masashi Sugiyama

The general weighted cumulative residual extropy (GWCRJ) and general weighted cumulative past extropy (GWCPJ) are introduced in this paper. There are some results in relation to GWCPJ and GWCRJ. We take into account GWCRJ-based uncertainty…

Statistics Theory · Mathematics 2024-04-23 Santosh Kumar Chaudhary , Nitin Gupta

This paper proposes new parametric model adequacy tests for possibly nonlinear and nonstationary time series models with noncontinuous data distribution, which is often the case in applied work. In particular, we consider the correct…

Statistics Theory · Mathematics 2021-08-10 Igor Kheifets , Carlos Velasco

Dynamic assessment of mortality risk in the intensive care unit (ICU) can be used to stratify patients, inform about treatment effectiveness or serve as part of an early-warning system. Static risk scoring systems, such as APACHE or SAPS,…

Machine Learning · Statistics 2020-11-03 Jonathan Heitz , Joanna Ficek , Martin Faltys , Tobias M. Merz , Gunnar Rätsch , Matthias Hüser

Fractional cumulative residual entropy (FCRE) is a powerful tool for the analysis of complex systems. Most of the theoretical results and applications related to the FCRE of the lifetime random variable are based on the distribution…

Statistics Theory · Mathematics 2025-02-04 Iona Ann Sebastian , S. M. Sunoj

We propose a frequentist testing procedure that maintains a defined coverage and is optimal in the sense that it gives maximal power to detect deviations from a null hypothesis when the alternative to the null hypothesis is sampled from a…

Applications · Statistics 2020-07-07 Christian Bartels , Johanna Mielke , Ekkehard Glimm

In the regression discontinuity design (RDD), it is common practice to assess the credibility of the design by testing the continuity of the density of the running variable at the cut-off, e.g., McCrary (2008). In this paper we propose an…

Econometrics · Economics 2020-02-13 Federico A. Bugni , Ivan A. Canay

In this paper, we develop an exact test for testing exponentiality against renewal increasing mean residual life class. Pitman's asymptotic efficacy value shows that our test perform well. Some numerical results are presented to demonstrate…

Statistics Theory · Mathematics 2016-09-05 K. K. Sudheesh

We revisit the outlier hypothesis testing framework of Li \emph{et al.} (TIT 2014) and derive fundamental limits for the optimal test under the generalized Neyman-Pearson criterion. In outlier hypothesis testing, one is given multiple…

Information Theory · Computer Science 2022-02-15 Lin Zhou , Yun Wei , Alfred Hero

Spatially referenced data often have autocovariance functions with elliptical isolevel contours, a property known as geometric anisotropy. The anisotropy parameters include the tilt of the ellipse (orientation angle) with respect to a…

Statistics Theory · Mathematics 2021-10-04 Manolis P. Petrakis , Dionissios T. Hristopulos

This paper proposes new specification tests for conditional models with discrete responses, which are key to apply efficient maximum likelihood methods, to obtain consistent estimates of partial effects and to get appropriate predictions of…

Statistics Theory · Mathematics 2018-02-01 Igor Kheifets , Carlos Velasco

Unlike traditional statistical methods, Conformal Prediction (CP) allows for the determination of valid and accurate confidence levels associated with individual predictions based only on exchangeability of the data. We here introduce a new…

Computer Vision and Pattern Recognition · Computer Science 2024-05-31 Marcos López-De-Castro , Alberto García-Galindo , Rubén Armañanzas

In this paper, we investigate several properties of the weighted varextropy measure and obtain it for specific distribution functions, such as the equilibrium and weighted distributions. We also obtain bounds for the weighted varextropy, as…

Statistics Theory · Mathematics 2025-07-01 Faranak Goodarzi

Recently Liu and Wang derived the likelihood ratio test (LRT) statistic and its asymptotic distribution for testing equality of two multinomial distributions vs. the alternative that the second distribution is larger in terms of increasing…

Statistics Theory · Mathematics 2007-06-13 Arthur Cohen , John Kolassa , Harold Sackrowitz

Density Functional Theory (DFT) stands as a widely used and efficient approach for addressing the many-electron Schr\"odinger equation across various domains such as physics, chemistry, and biology. However, a core challenge that persists…

Computational Engineering, Finance, and Science · Computer Science 2024-12-25 Sizhuo Jin , Shuo Chen , Jianjun Qian , Ying Tai , Jun Li

The conditional randomization test (CRT) was recently proposed to test whether two random variables X and Y are conditionally independent given random variables Z. The CRT assumes that the conditional distribution of X given Z is known…

Machine Learning · Computer Science 2023-04-11 Shuai Li , Ziqi Chen , Hongtu Zhu , Christina Dan Wang , Wang Wen

Verifying probabilistic forecasts for extreme events is a highly active research area because popular media and public opinions are naturally focused on extreme events, and biased conclusions are readily made. In this context, classical…