Results 81 to 90 of about 4,545 (215)
Moving Sum Procedure for Multiple Change Point Detection in Large Factor Models
Journal of Time Series Analysis, EarlyView.ABSTRACT This paper proposes a moving sum methodology for detecting multiple change points in high‐dimensional time series under a factor model, where changes are attributed to those in loadings as well as emergence or disappearance of factors. We establish the asymptotic null distribution of the proposed test for family‐wise error control and show the
Matteo Barigozzi +2 more
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Empirical‐Process Limit Theory and Filter Approximation Bounds for Score‐Driven Time Series Models
Journal of Time Series Analysis, EarlyView.ABSTRACT This article examines the filtering and approximation‐theoretic properties of score‐driven time series models. Under specific Lipschitz‐type and tail conditions, new results are derived, leading to maximal and deviation inequalities for the filtering approximation error using empirical process theory.
Enzo D'Innocenzo
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Journal of Time Series Analysis, EarlyView.ABSTRACT The paper deals with the construction of a synthetic indicator of economic growth, obtained by projecting a quarterly measure of aggregate economic activity, namely gross domestic product (GDP), into the space spanned by a finite number of smooth principal components, representative of the medium‐to‐long‐run component of economic growth of a ...
Alessandro Giovannelli +2 more
wiley +1 more source
MathematicsThe rates of continuous evolution plays a crucial role in understanding the pace at which species evolve. Various statistical models have been developed to estimate the rates of continuous trait evolution for a group of related species evolving along a ...
Dwueng-Chwuan Jhwueng
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The Accuracy Smoothness Dilemma in Prediction: A Novel Multivariate M‐SSA Forecast Approach
Journal of Time Series Analysis, EarlyView.ABSTRACT Forecasting presents a complex estimation challenge, as it involves balancing multiple, often conflicting, priorities and objectives. Conventional forecast optimization methods typically emphasize a single metric, such as minimizing the mean squared error (MSE), which may neglect other crucial aspects of predictive performance. To address this
Marc Wildi
wiley +1 more source
Fully Modified GLS Estimation for Seemingly Unrelated Cointegrating Polynomial Regressions
Oxford Bulletin of Economics and Statistics, EarlyView.ABSTRACT A new feasible generalized least squares estimator is proposed. Our estimator incorporates (1) the inverse autocovariance matrix of multidimensional errors, and (2) second‐order bias corrections. The resulting estimator has the intuitive interpretation of applying a weighted least squares objective function to filtered data series.
Yicong Lin, Hanno Reuvers
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Lévy–Driven Continuous–Time ARMA Processes
, 2009 Gaussian ARMA processes with continuous time parameter, otherwise known as stationary continuous-time Gaussian processes with rational spectral density, have been of interest for many years. (See for example the papers of Doob (1944), Bartlett (1946), Phillips (1959), Durbin (1961), Dzhapararidze (1970,1971), Pham-Din-Tuan (1977) and the monograph of ...
openaire +2 more sources
Public Health Nursing, EarlyView.ABSTRACT Objective This study describes a nurse‐led intervention aimed at improving mental health literacy (MHL), reducing stigma, and encouraging help‐seeking behaviour. Design A quasi‐experimental design involved 578 responses ranging in age from 13 to 52 years (M = 20.28, SD = 6.29), including secondary school pupils, nursing undergraduates, and ...
Laura Alonso Martínez +5 more
wiley +1 more source
Plant Biology, EarlyView.Using a 4‐year drought experiment in the hot deserts of the US, we found that herbaceous plant communities were more sensitive to seasonal precipitation than to the cumulative effects of drought. Abstract The hot deserts of the southwestern United States are experiencing increased frequency, severity, and duration of drought due to anthropogenic ...
T. Ohlert +4 more
wiley +1 more source
New Strategies to Improve the Accuracy of Predictions based on Monte Carlo and Bootstrap Simulations: An Application to Bulgarian and Romanian Inflation || Nuevas estrategias para mejorar la exactitud de las predicciones de inflación en Rumanía y Bulgaria usando simulaciones Monte Carlo y Bootstrap [PDF]
Revista de Métodos Cuantitativos para la Economía y la Empresa, 2014 The necessity of improving the forecasts accuracy grew in the context of actual economic crisis, but few researchers were interested till now in finding out some empirical strategies to improve their predictions.
Simionescu, Mihaela
doaj