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A cornerstone of human statistical learning is the ability to extract temporal regularities / patterns from random sequences. Here we present a method of computing pattern time statistics with generating functions for first-order Markov…

Neurons and Cognition · Quantitative Biology 2018-06-29 Yanlong Sun , Hongbin Wang

The incorporation of uncertainties to calculations of signal significance in planned experiments is an actual task. Several approaches to this problem are discussed. We present a procedure for taking into account the systematic uncertainty…

High Energy Physics - Phenomenology · Physics 2009-11-07 S. I. Bityukov

This paper provides insight into when, why, and how forecast strategies fail when they are applied to complicated time series. We conjecture that the inherent complexity of real-world time-series data---which results from the dimension,…

Information Theory · Computer Science 2014-11-24 Joshua Garland , Ryan James , Elizabeth Bradley

This work starts from definition of randomness, the results of algorithmic randomness are analyzed from the perspective of application. Then, the source and nature of randomness is explored, and the relationship between infinity and…

General Mathematics · Mathematics 2022-12-01 Yongxin Li

We deal here with the issue of determinism versus randomness in time series. One wishes to identify their relative weights in a given time series. Two different tools have been advanced in the literature to such effect, namely, i) the…

Device-independent randomness generation and quantum key distribution protocols rely on a fundamental relation between the non-locality of quantum theory and its random character. This relation is usually expressed in terms of a trade-off…

Quantum Physics · Physics 2018-03-20 Olmo Nieto-Silleras , Cédric Bamps , Jonathan Silman , Stefano Pironio

Due to lack of scientific understanding, some mechanisms may be missing in mathematical modeling of complex phenomena in science and engineering. These mathematical models thus contain some uncertainties such as uncertain parameters. One…

Probability · Mathematics 2012-04-05 Jinqiao Duan , Ting Gao , Guowei He

This work delves into presenting a probabilistic method for analyzing linear process data with weakly dependent innovations, focusing on detecting change-points in the mean and estimating its spectral density. We develop a test for…

Statistics Theory · Mathematics 2024-10-01 Ramkrishna Jyoti Samanta

Biological sequences do not come at random. Instead, they appear with particular frequencies that reflect properties of the associated system or phenomenon. Knowing how biological sequences are distributed in sequence space is thus a…

Biological Physics · Physics 2024-04-18 Wei-Chia Chen , Juannan Zhou , David M. McCandlish

Randomness comes in two qualitatively different forms. Apparent randomness can result both from ignorance or lack of control of degrees of freedom in the system. In contrast, intrinsic randomness should not be ascribable to any such cause.…

Quantum Physics · Physics 2014-03-12 Chirag Dhara , Gonzalo de la Torre , Antonio Acín

The quantum mechanical probability densities are compared with the probability densities treated by the theory of random variables. The relevance of their difference for the interpretation of quantum mechanics is commented.

Quantum Physics · Physics 2008-04-28 Alberto C. de la Torre

We examine the dependence of quantization on global properties of a classical system. Quantization based on local properties may lead to ambiguities and inconsistency between local and global symmetries of a quantum system. Our quantization…

Astrophysics · Physics 2009-11-07 Wlodzimierz Piechocki

Spurious association arises from covariance between propensity for the treatment and individual risk for the outcome. For sensitivity analysis with stochastic counterfactuals we introduce a methodology to characterize uncertainty in causal…

Methodology · Statistics 2021-03-11 Brian Knaeble , Braxton Osting , Placede Tshiaba

Some data is linearly additive, other data is not. In this paper, I discuss types of data based on the boundedness of the data and their linearity. 1) Unbounded data can be linear. 2) One-side bounded data is usually log transformed to be…

Statistics Theory · Mathematics 2019-04-03 Christopher M. Rembold

A quantization method based on replacement of c-number by c-number parameterized by an unbiased hidden random variable is developed. In contrast to canonical quantization, the replacement has straightforward physical interpretation as…

Quantum Physics · Physics 2012-03-08 Agung Budiyono

The issue of defining a random sequence of qubits is studied in the framework of Algorithmic Free Probability Theory.Its connection with Quantum Algorithmic Information Theory is shown

Quantum Physics · Physics 2007-05-23 Gavriel Segre

It has been observed that an interesting class of non-Gaussian stationary processes is obtained when in the harmonics of a signal with random amplitudes and phases, frequencies can also vary randomly. In the resulting models, the…

Probability · Mathematics 2019-11-19 Anastassia Baxevani , Krzysztof Podgórski

The density matrix yields probabilistic information about the outcome of measurements on a quantum system, but it does not distinguish between classical randomness in the preparation of the system and entanglement with its environment.…

Quantum Physics · Physics 2025-09-11 Julien Pinske , Klaus Mølmer

We study algorithmic randomness and monotone complexity on product of the set of infinite binary sequences. We explore the following problems: monotone complexity on product space, Lambalgen's theorem for correlated probability,…

Information Theory · Computer Science 2010-06-29 Hayato Takahashi

Parametric statistical methods play a central role in analyzing risk through its underlying frequency and severity components. Given the wide availability of numerical algorithms and high-speed computers, researchers and practitioners often…

Applications · Statistics 2025-06-17 Michael R. Powers , Jiaxin Xu