Results 81 to 90 of about 52,018 (229)

Econometrics at the Extreme: From Quantile Regression to QFAVAR1

Journal of Economic Surveys, EarlyView.
ABSTRACT This paper surveys quantile modelling from its theoretical origins to current advances. We organize the literature and present core econometric formulations and estimation methods for: (i) cross‐sectional quantile regression; (ii) quantile time series models and their time series properties; (iii) quantile vector autoregressions for ...
Stéphane Goutte, Konstantinos N. Konstantakis, Dimitris Konstantios, Panayotis G. Michaelides, Arsenios‐Georgios N. Prelorentzos   +4 more
wiley   +1 more source

Ergodicity, lack thereof, and the performance of reservoir computing with memristive networks

Nano Express
Networks composed of nanoscale memristive components, such as nanowire and nanoparticle networks, have recently received considerable attention because of their potential use as neuromorphic devices.
Valentina Baccetti, Ruomin Zhu, Zdenka Kuncic, Francesco Caravelli   +3 more
doaj   +1 more source

MODEL OF THE QUALITY MANAGEMENT SYSTEM OF A MACHINE TOOL COMPANY

Вісник Національного технічного університету «ХПÌ». Серія: Стратегічне управління, управління портфелями, програмами та проектами, 2016
Development of models and methods such that would improve the competitive position of enterprises by improving management processes is an important task of project management.
Катерина Вікторівна КОЛЕСНІКОВА, Артем Олександрович НЕГРІ, Георгій Сергійович ОЛЕХ, Богдан Олександрович ЛЕБЕДЕНКО   +3 more
doaj   +1 more source

Dobrushin's ergodicity coefficient for Markov operators on cones

, 2014
We give a characterization of the contraction ratio of bounded linear maps in Banach space with respect to Hopf's oscillation seminorm, which is the infinitesimal distance associated to Hilbert's projective metric, in terms of the extreme points of a ...
Gaubert, Stephane, Qu, Zheng
core   +2 more sources

Markov Determinantal Point Process for Dynamic Random Sets

Journal of Time Series Analysis, EarlyView.
ABSTRACT The Law of Determinantal Point Process (LDPP) is a flexible parametric family of distributions over random sets defined on a finite state space, or equivalently over multivariate binary variables. The aim of this paper is to introduce Markov processes of random sets within the LDPP framework. We show that, when the pairwise distribution of two
Christian Gouriéroux, Yang Lu
wiley   +1 more source

Universal quantum uncertainty relations between non-ergodicity and loss of information

, 2018
We establish uncertainty relations between information loss in general open quantum systems and the amount of non-ergodicity of the corresponding dynamics. The relations hold for arbitrary quantum systems interacting with an arbitrary quantum environment.
Awasthi, Natasha, Bhattacharya, Samyadeb, De, Aditi Sen, Sen, Ujjwal   +3 more
core   +1 more source

On Exponential‐Family INGARCH Models

Journal of Time Series Analysis, EarlyView.
ABSTRACT A range of integer‐valued generalised autoregressive conditional heteroscedastic (INGARCH) models have been proposed in the literature, including those based on conditional Poisson, negative binomial and Conway‐Maxwell‐Poisson distributions. This note considers a larger class of exponential‐family INGARCH models, showing that maximum empirical
Alan Huang, Thomas Fung, Kyle Macaskill, Rowan Aukes   +3 more
wiley   +1 more source

General limit distributions for sums of random variables with a matrix product representation

, 2014
The general limit distributions of the sum of random variables described by a finite matrix product ansatz are characterized. Using a mapping to a Hidden Markov Chain formalism, non-standard limit distributions are obtained, and related to a form of ...
Abry, Patrice, Angeletti, Florian, Bertin, Eric   +2 more
core   +1 more source

Time‐Varying Dispersion Integer‐Valued GARCH Models

Journal of Time Series Analysis, EarlyView.
ABSTRACT We introduce a general class of INteger‐valued Generalized AutoRegressive Conditionally Heteroscedastic (INGARCH) processes by allowing simultaneously time‐varying mean and dispersion parameters. We call such models time‐varying dispersion INGARCH (tv‐DINGARCH) models.
Wagner Barreto‐Souza, Luiza S. C. Piancastelli, Konstantinos Fokianos, Hernando Ombao   +3 more
wiley   +1 more source

Statistical inference for nth-order mixed fractional Brownian motion with polynomial drift

Modern Stochastics: Theory and Applications
The mixed model with polynomial drift of the form $X(t)=\theta \mathcal{P}(t)+\alpha W(t)+\sigma {B_{H}^{n}}(t)$ is studied, where ${B_{H}^{n}}$ is the nth-order fractional Brownian motion with Hurst index $H\in (n-1,n)$ and $n\ge 2$, independent of the ...
Mohamed El Omari
doaj   +1 more source