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We develop two notions of time-restricted sensitivity to initial conditions for measurable dynamical systems, where the time before divergence of a pair of paths is at most an asymptotically logarithmic function of a measure of their…

Dynamical Systems · Mathematics 2014-01-23 Domenico Aiello , Hansheng Diao , Zhou Fan , Daniel O. King , Jessica Lin , Cesar E. Silva

This study aims to predict failure times for some units in some lifetime experiments. In some practical situations, the experimenter may not be able to register the failure times of all units during the experiment. Recently, this situation…

Statistics Theory · Mathematics 2023-04-13 Mahmoud Mansour , Mohamed Aboshady

We study properties of truncations in the dual and intertwining process in the monotone case. The main properties are stated for the time-reversed process and the time of absorption of the truncated intertwining process.

Probability · Mathematics 2019-11-05 Thierry Huillet , Servet Martinez

New measures for the quantization of systems with constraints are discussed and applied to several examples, in particular, examples of alternative but equivalent formulations of given first-class constraints, as well as a comparison of…

Quantum Physics · Physics 2007-05-23 John R. Klauder

Transfer entropy (TE) captures the directed relationships between two variables. Partial transfer entropy (PTE) accounts for the presence of all confounding variables of a multivariate system and infers only about direct causality. However,…

Methodology · Statistics 2021-02-03 Angeliki Papana , Ariadni Papana-Dagiasis , Elsa Siggiridou

Weighted conformal prediction (WCP) has been commonly used to quantify prediction uncertainty under covariate shift. However, the effectiveness of WCP relies heavily on the degree of overlap between the training and test covariate…

Methodology · Statistics 2026-04-02 Mufang Ying , Wenge Guo , Koulik Khamaru , Ying Hung

Let $A$ and $B$ be two accretive operators. We first introduce the weighted geometric mean of $A$ and $B$ together with some related properties. Afterwards, we define the relative entropy as well as the Tsallis entropy of $A$ and $B$. The…

Functional Analysis · Mathematics 2021-07-23 M. Raïssouli , M. S. Moslehian , S. Furuichi

Entropy is a measure of self-information which is used to quantify losses. Entropy was developed in thermodynamics, but is also used to compare probabilities based on their deviating information content. Corresponding model uncertainty is…

Probability · Mathematics 2018-01-23 Alois Pichler , Ruben Schlotter

The description of complex systems requires a progressively larger number of parameters. However, in practice, it often happens that a small subset of parameters suffices to describe the dynamics of the system itself: these combinations are…

The uncertainty principle brings out intrinsic quantum bounds on the precision of measuring non-commuting observables. Statistical outcomes in the measurement of incompatible observables reveal a trade-off on the sum of corresponding…

Quantum Physics · Physics 2013-11-11 H. S. Karthik , A. R. Usha Devi , J. Prabhu Tej , A. K. Rajagopal

Given an arbitrary measurement over a system of interest, the outcome of a posterior measurement can be used for improving the statistical estimation of the system state after the former measurement. Here, we realize an…

Quantum Physics · Physics 2018-02-07 Adrian A. Budini

Quantum resonance, i.e., amplification in transition probability available under certain conditions, offers a powerful means for determining fundamental quantities in physics, including the time duration of the second adopted in the SI…

Quantum Physics · Physics 2025-06-17 Daiki Ueda , Izumi Tsutsui

This paper proposes two estimators of the joint entropy of the Type-II censored data. Consistency of both estimators is proved. Simulation results show that the second one shows less bias and root of mean square error (RMSE) than leading…

Statistics Theory · Mathematics 2013-01-03 A. Kohansal , S. Rezakhah

The method of Maximum (relative) Entropy (ME) is used to translate the information contained in the known form of the likelihood into a prior distribution for Bayesian inference. The argument is guided by intuition gained from the…

Data Analysis, Statistics and Probability · Physics 2009-11-10 Ariel Caticha , Roland Preuss

The drift sequential parameter estimation problems for the Cox-Ingersoll-Ross (CIR) processes under the limited duration of observation are studied. Truncated sequential estimation methods for both scalar and {two}-dimensional parameter…

Statistics Theory · Mathematics 2025-04-08 Mohamed Ben Alaya , Thi-Bao Trâm Ngô , Serguei Pergamenchtchikov

Evaluating the performance of a prediction model is a common task in medical statistics. Standard accuracy metrics require the observation of the true outcomes. This is typically not possible in the setting with time-to-event outcomes due…

Methodology · Statistics 2025-07-18 Zhenwei Yang , Dimitris Rizopoulos , Lisa F. Newcomb , Nicole S. Erler

Concurrence introduced by Hill and Wootters [Phys. Rev. Lett. 78, 5022 (1997)], provides an important measure of entanglement for a general pair of qubits that is strictly positive entangled states and vanishes for all separable states. We…

Quantum Physics · Physics 2022-06-01 S Nibedita Swain , Vineeth S. Bhaskara , Prasanta K. Panigrahi

Combining several independent measurements of the same physical quantity is one of the most important tasks in metrology. Small samples, biased input estimates, not always adequate reported uncertainties, and unknown error distribution make…

Data Analysis, Statistics and Probability · Physics 2026-04-22 Zinovy Malkin

This note extends some results of Nishiyama [Ann. Probab. 28 (2000) 685--712]. A maximal inequality for stochastic integrals with respect to integer-valued random measures which may have infinitely many jumps on compact time intervals is…

Probability · Mathematics 2011-11-10 Yoichi Nishiyama

Statistical and structural modeling represent two distinct approaches to data analysis. In this paper, we propose a set of novel methods for combining statistical and structural models for improved prediction and causal inference. Our first…

Econometrics · Economics 2020-06-11 Jiaming Mao , Jingzhi Xu
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