Results 21 to 30 of about 4,998 (266)

Pivot Clustering to Minimize Error in Forecasting Aggregated Demand Streams Each Following an Autoregressive Moving Average Model

Stats, 2023
In this paper, we compare the effects of forecasting demand using individual (disaggregated) components versus first aggregating the components either fully or into several clusters.
Vladimir Kovtun, Avi Giloni, Clifford Hurvich, Sridhar Seshadri   +3 more
doaj   +1 more source

On the Genuine Relevance of the Data-Driven Signal Decomposition-Based Multiscale Permutation Entropy

Entropy, 2022
Ordinal pattern-based approaches have great potential to capture intrinsic structures of dynamical systems, and therefore, they continue to be developed in various research fields. Among these, the permutation entropy (PE), defined as the Shannon entropy
Meryem Jabloun, Philippe Ravier, Olivier Buttelli   +2 more
doaj   +1 more source

Modeling Markov Switching ARMA-GARCH Neural Networks Models and an Application to Forecasting Stock Returns

The Scientific World Journal, 2014
The study has two aims. The first aim is to propose a family of nonlinear GARCH models that incorporate fractional integration and asymmetric power properties to MS-GARCH processes.
Melike Bildirici, Özgür Ersin
doaj   +1 more source

Rate Distortion Function of Gaussian Asymptotically WSS Vector Processes

Entropy, 2018
In this paper, we obtain an integral formula for the rate distortion function (RDF) of any Gaussian asymptotically wide sense stationary (AWSS) vector process.
Jesús Gutiérrez-Gutiérrez, Marta Zárraga-Rodríguez, Pedro M. Crespo, Xabier Insausti   +3 more
doaj   +1 more source

On nonnegative solutions of SDDEs with an application to CARMA processes

Modern Stochastics: Theory and Applications, 2021
This note provides a simple sufficient condition ensuring that solutions of stochastic delay differential equations (SDDEs) driven by subordinators are nonnegative.
Mikkel Slot Nielsen, Victor Rohde
doaj   +1 more source

ARMA model for random periodic processes [PDF]

, 2018
In this thesis, we construct ARMA model for random periodic processes. We stress on the mixed periodicity and randomness of the model and redefined the definition of sample autocovariance function.
Yujia Liu (1250571)
core   +1 more source

Stability Monitoring of Batch Processes with Iterative Learning Control

Advances in Mathematical Physics, 2017
In recent years, the iterative learning control (ILC) is widely used in batch processes to improve the quality of the products. Stability is a preoccupation of batch processes when the ILC is applied.
Yan Wang, Junwei Sun, Taishan Lou, Lexiang Wang   +3 more
doaj   +1 more source

On autoregressive moving-average models as a tool of virtual stock-exchange: experimental investigation

Lietuvos Matematikos Rinkinys, 2012
The objective of this work is to investigate experimentally the well-known autoregressive models as simplest algorithms simulating prediction processes of the stockholders using the historical stock rates only.
Jonas Mockus, Joana Katina, Igor Katin
doaj   +1 more source

Significance and Causality in Continuous Wavelet and Wavelet Coherence Spectra Applied to Hydrological Time Series

Hydrology, 2020
Wavelet transform, wavelet spectra, and coherence are popular tools for studying fluctuations in time series in the form of a bidimensional time and scale representation.
Juan Carlos Rodríguez-Murillo, Montserrat Filella   +1 more
doaj   +1 more source

Development of a first order integrated moving average model corrupted with a Markov modulated convex combination of autoregressive moving average errors

Statistical Theory and Related Fields, 2019
With a view to providing a tool to accurately model time series processes which may be corrupted with errors such as measurement, round-off and data aggregation, this study developed an integrated moving average (IMA) model with a transition matrix for ...
S. A. Komolafe, T. O. Obilade, I. O. Ayodeji, A. R. Babalola   +3 more
doaj   +1 more source