Results 81 to 90 of about 3,605 (210)

Multiple Chains Markov Switching Vector Autoregression

Journal of Time Series Analysis, EarlyView.
ABSTRACT Both the U.S. stock and bond returns exhibit distinct Markovian regimes. However, because these regimes display limited coherence, conventional models typically require highly parameterized systems to adequately capture their joint distribution.
Leopoldo Catania
wiley   +1 more source

Asymptotic Analysis of Poverty Dynamics via Feller Semigroups

Mathematics
Poverty is a multifaceted phenomenon impacting millions globally, defined by a deficiency in both material and immaterial resources, which consequently restricts access to satisfactory living conditions. Comprehensive poverty analysis can be accomplished
Lahcen Boulaasair, Mehmet Yavuz, Hassane Bouzahir   +2 more
doaj   +1 more source

On Testing for Independence Between Generalized Error Models of Several Time Series

Journal of Time Series Analysis, EarlyView.
ABSTRACT We define generalized innovations associated with generalized error models having arbitrary distributions, that is, distributions that can be mixtures of continuous and discrete distributions. These models include stochastic volatility models and regime‐switching models with possibly zero‐inflated regimes.
Kilani Ghoudi, Bouchra R. Nasri, Bruno N. Rémillard   +2 more
wiley   +1 more source

Penalized Convex Estimation in Dynamic Location Models

Journal of Time Series Analysis, EarlyView.
ABSTRACT This paper studies L1$$ {L}^1 $$‐penalized estimation for location models yt=mt+ϵt$$ {y}_t={m}_t+{\epsilon}_t $$, where mt$$ {m}_t $$ is defined by a possibly non‐Markovian recursion and ϵt$$ {\epsilon}_t $$ is a martingale difference sequence with possibly time‐varying conditional variance.
Reda Alami Chentoufi
wiley   +1 more source

Moving Aggregate Modified Autoregressive Copula‐Based Time Series Models (MAGMAR‐Copulas)

Journal of Time Series Analysis, EarlyView.
ABSTRACT Copula‐based time series models can model univariate and stationary time series in a flexible way by decomposing the joint distribution of consecutive observations into a copula and the stationary distribution. Implicitly, this approach assumes a finite Markov order. In reality, a time series may not follow the Markov property.
Sven Pappert
wiley   +1 more source

STATISTICAL MECHANICS: BRIDGING MICROSCOPIC BEHAVIOR TO MACROSCOPIC OBSERVABLES: Gravitational waves

Worldwide Journal of Physics, 2023
This study investigates how statistical mechanics bridges the gap between microscopic particle dynamics and macroscopic thermodynamic observables through a mixed-methods framework combining ensemble theory, computational modeling, and statistical ...
Syed Rizwan Hussain, Aurang Zeb
doaj  

Detecting Periodicity of a General Stationary Time Series via AR(2)‐Model Fitting

Journal of Time Series Analysis, EarlyView.
ABSTRACT Estimating the periodicity of a stationary time series via fitting a second‐order stationary autoregressive (AR(2)) model has been initiated by the seminal paper of Yule (1927). We investigate properties of this procedure when applied to general stationary processes possessing a spectral density with a dominant peak at some unknown frequency ...
Jens‐Peter Kreiss, Panagiotis Maouris, Efstathios Paparoditis   +2 more
wiley   +1 more source

Parametric Time‐Variation in the Unconditional Volatility: Estimation and Inference

Journal of Time Series Analysis, EarlyView.
ABSTRACT We propose modeling time‐variation in the unconditional volatility by augmenting the standard GARCH model by a deterministic time‐varying intercept. The model, called the additive time‐varying (ATV‐)GARCH model, can be interpreted as a reduced form of a model including covariates and can be derived from a multiplicative decomposition of ...
Niklas Ahlgren, Alexander Back, Timo Teräsvirta   +2 more
wiley   +1 more source

Ergodic and mixing quantum channels in finite dimensions

New Journal of Physics, 2013
The paper provides a systematic characterization of quantum ergodic and mixing channels in finite dimensions and a discussion of their structural properties. In particular, we discuss ergodicity in the general case where the fixed point of the channel is
D Burgarth, G Chiribella, V Giovannetti, P Perinotti, K Yuasa   +4 more
doaj   +1 more source

Asymptotics of Time‐Varying Processes in Continuous‐Time Using Locally Stationary Approximations

Journal of Time Series Analysis, EarlyView.
ABSTRACT We introduce a general theory on stationary approximations for locally stationary continuous‐time processes. Based on the stationary approximation, we use θ$$ \theta $$‐weak dependence to establish laws of large numbers and central limit type results under different observation schemes.
Robert Stelzer, Bennet Ströh
wiley   +1 more source