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We develop a stochastic calculus that makes it easy to capture a variety of predictable transformations of semimartingales such as changes of variables, stochastic integrals, and their compositions. The framework offers a unified treatment…

Probability · Mathematics 2022-01-13 Aleš Černý , Johannes Ruf

In this article we present very intuitive, easy to follow, yet mathematically rigorous, approach to the so called data fitting process. Rather than minimizing the distance between measured and simulated data points, we prefer to find such…

Data Analysis, Statistics and Probability · Physics 2017-08-07 Marek W. Gutowski

For a one dimensional diffusion process $X=\{X(t) ; 0\leq t \leq T \}$, we suppose that $X(t)$ is hidden if it is below some fixed and known threshold $\tau$, but otherwise it is visible. This means a partially hidden diffusion process. The…

Statistics Theory · Mathematics 2011-11-09 Stefano Iacus , Masayuki Uchida , Nakahiro Yoshida

Interval calculus is a relatively new branch of mathematics. Initially understood as a set of tools to assess the quality of numerical calculations (rigorous control of rounding errors), it became a discipline in its own rights today.…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Marek W. Gutowski

The calculus of finite differences is a solid foundation for the development of operations such as the derivative and the integral for infinite sequences. Here we showed a way to extend it for finite sequences. We could then define…

Discrete Mathematics · Computer Science 2018-11-06 Sérgio Martins Filho

We present a new paradigm for capturing the complementarity of two observables. It is based on the entanglement created by the interaction between the system observed and the two measurement devices used to measure the observables…

Quantum Physics · Physics 2014-01-29 Patrick J. Coles , Marco Piani

We present the concept of the \emph{information efficiency of functions} as a technique to understand the interaction between information and computation. Based on these results we identify a new class of objects that we call…

Computational Complexity · Computer Science 2019-04-09 P. W. Adriaans

Indirect measurement can be used to read out the outcome of a quantum system without resorting to a straightforward approach, and it is the foundation of the measurement uncertainty relations that explain the incompatibility of conjugate…

Quantum Physics · Physics 2022-08-09 Ryo Mihashi , Yoshihiko Hasegawa

We consider the contextual fraction as a quantitative measure of contextuality of empirical models, i.e. tables of probabilities of measurement outcomes in an experimental scenario. It provides a general way to compare the degree of…

Quantum Physics · Physics 2017-08-09 Samson Abramsky , Rui Soares Barbosa , Shane Mansfield

Mechanisms for the automation of uncertainty are required for expert systems. Sometimes these mechanisms need to obey the properties of probabilistic reasoning. A purely numeric mechanism, like those proposed so far, cannot provide a…

Artificial Intelligence · Computer Science 2013-04-15 Alan Bundy

The Mann-Kendall test for trend has gained a lot of attention in a range of disciplines, especially in the environmental sciences. One of the drawbacks of the Mann-Kendall test when applied to real data is that no distinction can be made…

Methodology · Statistics 2023-05-24 Stavros Nikolakopoulos , Eric Cator , Mart P. Janssen

Neutrosophic Analysis is a generalization of Set Analysis, which in its turn is a generalization of Interval Analysis. Neutrosophic Precalculus is referred to indeterminate staticity, while Neutrosophic Calculus is the mathematics of…

General Mathematics · Mathematics 2015-09-28 Florentin Smarandache

We study distributional similarity measures for the purpose of improving probability estimation for unseen cooccurrences. Our contributions are three-fold: an empirical comparison of a broad range of measures; a classification of similarity…

Computation and Language · Computer Science 2007-05-23 Lillian Lee

The paper treats density measures as typical examples of finitely additive measures in $\mathbb{R}^n$. We study their structure and derive basic properties. In addition, estimates for related integrals are provided. The results are applied…

Analysis of PDEs · Mathematics 2026-03-26 Moritz Schönherr , Friedemann Schuricht

In this paper, an alternative approximation to the innovation method is introduced for the parameter estimation of diffusion processes from partial and noisy observations. This is based on a convergent approximation to the first two…

Optimization and Control · Mathematics 2013-12-19 J. C. Jimenez

This paper offers a mathematical invention that shows how to convert integrated quantiles, which often appear in risk measures, into integrated cumulative distribution functions, which are technically more tractable from various…

Risk Management · Quantitative Finance 2023-04-26 Yunran Wei , Ricardas Zitikis

We study dynamic risk measures in a very general framework enabling to model uncertainty and processes with jumps. We previously showed the existence of a canonical equivalence class of probability measures hidden behind a given set of…

Probability · Mathematics 2010-12-30 Jocelyne Bion-Nadal , Magali Kervarec

A semi-measure is a generalization of a probability measure obtained by relaxing the additivity requirement to super-additivity. We introduce and study several randomness notions for left-c.e. semi-measures, a natural class of effectively…

Logic · Mathematics 2017-10-18 Laurent Bienvenu , Rupert Hölzl , Christopher P. Porter , Paul Shafer

We introduce the concepts of dual instruments and sub-observables. We show that although a dual instruments measures a unique observable, it determines many sub-observables. We define a unique minimal extension of a sub-observable to an…

Quantum Physics · Physics 2023-02-24 Stanley Gudder

We identity the optimal non-infinitesimal direction of descent for a convex function. An algorithm is developed that can theoretically minimize a subset of (non-convex) functions.

Optimization and Control · Mathematics 2025-09-19 Andrew J. Young