Results 41 to 50 of about 24,065 (262)
Frontiers in Sustainable Food SystemsIntroductionSince the 1960s, global agricultural prices have exhibited significant episodic volatility. This study aims to conduct a trend-cycle decomposition of these prices to identify the cyclical patterns of their long-run dynamic evolution ...
Yujia Li, Bingjian Zhao, Ming Che
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Health Economics Review, 2019 This article investigates the causal links between health and employment status. To disentangle correlation from causality effects, the authors leverage a French panel survey to estimate a bivariate dynamic probit model that can account for the ...
Eric Delattre +2 more
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A Structural Time Series Analysis of the Effect of Quantitative Easing on Stock Prices
International Journal of Financial Studies, 2022 In this paper, a structural time series model is estimated to analyse the effect of quantitative easing (QE) on stock prices for the US, UK and Japan. The model is estimated by maximum likelihood in a time-varying parametric framework, using the DJIA, S ...
George B. Tawadros, Imad A. Moosa
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Unobserved component time series models with Arch disturbances [PDF]
Journal of Econometrics, 1992 Abstract This paper considers how ARCH effects may be handled in time series models formulated in terms of unobserved components. A general model is formulated, but this includes as special cases a random walk plus noise model with both disturbances subject to ARCH effects, an ARCH-M model with a time-varying parameter, and a latent factor model with
Harvey, A. C. +2 more
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dynoGP: Deep Gaussian Processes for Dynamic System Identification
International Journal of Adaptive Control and Signal Processing, EarlyView.This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +2 more
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Detection of unobserved heterogeneity with growth mixture models
Revista de Matemática: Teoría y Aplicaciones, 2009 Latent growth curve models as structural equation models are extensively discussed in various research fields (Duncan et al., 2006). Recent methodological and statistical extension are focused on the consideration of unobserved heterogeneity in ...
Jost Reinecke, Luca Mariotti
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Advanced Engineering Materials, EarlyView.Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch +3 more
wiley +1 more source
REGCMPNT – A Fortran Program for Regression Models with ARIMA Component Errors
Journal of Statistical Software, 2011 RegComponent models are time series models with linear regression mean functions and error terms that follow ARIMA (autoregressive-integrated-moving average) component time series models.
William R. Bell
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Forecasting Oil Price by Hierarchical Shrinkage in Dynamic Parameter Models
Discrete Dynamics in Nature and Society, 2020 The aim of this paper is to forecast monthly crude oil price with a hierarchical shrinkage approach, which utilizes not only LASSO for predictor selection, but a hierarchical Bayesian method to determine whether constant coefficient (CC) or time-varying ...
Yuntong Liu, Yu Wei, Yi Liu, Wenjuan Li
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Multimodal Data‐Driven Microstructure Characterization
Advanced Engineering Materials, EarlyView.A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
wiley +1 more source