Results 101 to 110 of about 13,145 (245)
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
This paper considers geometric ergodicity and likelihood based inference for linear and nonlinear Poisson autoregressions. In the linear case the conditional mean is linked linearly to its past values as well as the observed values of the Poisson process.
Dag Tjøstheim +2 more
core
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
"Computing Densities: A Conditional Monte Carlo Estimator" [PDF]
We propose a generalized conditional Monte Carlo technique for computing densities in economic models. Global consistency and functional asymptotic normality are established under ergodicity assumptions on the simulated process.
Huiyu Li +2 more
core +2 more sources
Geometric erogdicity of a bead-spring pair with stochastic Stokes forcing [PDF]
, 2009 We consider a simple model for the uctuating hydrodynamics of a exible polymer in dilute solution, demonstrating geometric ergodicity for a pair of particles that interact with each other through a nonlinear spring potential while being advected by ...
McKinley, Scott A. +2 more
core
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 +2 more
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
Structure and Asymptotic Theory for Nonlinear Models with GARCH Errors [PDF]
Nonlinear time series models, especially those with regime-switching and conditionally heteroskedastic errors, have become increasingly popular in the economics and finance literature.
Michael McAleer +2 more
core
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 +2 more
wiley +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