Results 101 to 110 of about 7,605 (274)
Multivariate ARMA modeling by scalar algorithms
, 1993 An algorithm for multichannel autoregressive moving average (ARMA) modeling which uses scalar computations only and is well suited for parallel implementation is proposed. The given ARMA process is converted to an equivalent scalar, periodic ARMA process.
Prasad, S., Charaborty, M.
core +1 more source
The asymptotic CRLB for the spectrum of ARMA processes
IEEE Transactions on Signal Processing, 2003 This paper addresses the issue of quantifying the frequency domain accuracy of autoregressive moving average (ARMA) spectral estimates as dictated by the Cramer-Rao lower bound (CRLB). Classical work in this area has led to expressions that are asymptotically exact as both data length and model order tend to infinity, although they are commonly used in
openaire +2 more sources
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
wiley +1 more source
Tensorial products of functional ARMA processes
Journal of Multivariate Analysis, 2010 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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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
Computing and estimating information matrices of weak arma models
Numerous time series admit "weak" autoregressive-moving average (ARMA) representations, in which the errors are uncorrelated but not necessarily independent nor martingale differences.
Francq, Christian +2 more
core
A k- factor GIGARCH process : estimation and application to electricity market spot prices, [PDF]
Some crucial time series of market data, such as electricity spot prices, exhibit long memory, in the sense of slowly-decaying correlations combined with heteroscedasticity.
Dominique Guegan +2 more
core
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
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
doaj +1 more source
Are We in Control? How Best to Include a Control Group in Interrupted Time Series Designs: A Simulation Study. [PDF]
J Eval Clin PractABSTRACT Background While controlled interrupted time series (CITS) are commonly used to evaluate public health policies, how to incorporate control(s) into their statistical modelling has received limited attention. We aimed to compare the statistical performance of different model formulations for including control groups in various segmented ...
Manca F, Mackay D, Lewsey J.
europepmc +2 more sources