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The Annals of Statistics, 1975 In estimating a vector model, $\Sigma B(j)x(n-j)=\Sigma A(j)\epsilon(n-j), A(0)=I_r, E(\epsilon(m)\epsilon(n)')=\delta_{mn}K$ it is suggested that attention be confined to cases where $g(z) =\Sigma A(j)z^j, h(z)=\Sigma B(j)z^j$ have determinants with no zeroes inside the unit circle and have $I_r$ as greatest common left divisor and where $\1brack A(p)\
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SchWARMA: A model-based approach for time-correlated noise in quantum circuits
Physical Review Research, 2021 Temporal noise correlations are ubiquitous in quantum systems, yet often neglected in the analysis of quantum circuits due to the complexity required to accurately characterize and model them.
Kevin Schultz +3 more
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Comparative Study Among Different Time Series Models for Monthly Rainfall Forecasting in Shiraz Synoptic Station, Iran [PDF]
Water Harvesting Research, 2018 In this research, monthly rainfall of Shiraz synoptic station from March 1971 to February 2016 was studied using different time series models by ITSM Software.
Mehdi Bahrami +4 more
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Linear and nonlinear dynamic systems in financial time series prediction [PDF]
Management Science Letters, 2012 Autoregressive moving average (ARMA) process and dynamic neural networks namely the nonlinear autoregressive moving average with exogenous inputs (NARX) are compared by evaluating their ability to predict financial time series; for instance the S&P500 ...
Salim Lahmiri
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Journal of King Saud University: Computer and Information Sciences, 2014 To alleviate the limitations of statistical based methods of forecasting of exchange rates, soft and evolutionary computing based techniques have been introduced in the literature.
Minakhi Rout +3 more
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System identification using neuro fuzzy approach for IoT application
Measurement: Sensors, 2022 The Internet of Things (IoT) has become a popular application in recent years. However, it is the wireless communication mode. In such a scenario, the user would have to send information either nonlinear or dynamic data type in the form of a signal or an
Rakesh Kumar Pattanaik +3 more
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Testing a linear ARMA model against threshold-ARMA models: A Bayesian approach [PDF]
Communications in Statistics - Simulation and Computation, 2016 We introduce a Bayesian approach to test linear autoregressive moving-average (ARMA) models against threshold autoregressive moving-average (TARMA) models. Firstly, the marginal posterior densities of all parameters, including the threshold and delay, of a TARMA model are obtained by using Gibbs sampler with Metropolis-Hastings algorithm.
Liang, Rubing +3 more
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Two level Differential Evolution algorithms for ARMA parameters estimatio [PDF]
, 2013 The problem of determining simultaneously the model order and coefficient of an Autoregressive Moving Average (ARMA) model is examined in this paper. An Evolutionary Algorithm (EA) comprising two-level Differential Evolution (DE) optimization scheme ...
Tijani, Ismaila +2 more
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Heliyon, 2023 The article focuses on analyzing the robustness of Auto Regressive Integrated Moving Average (ARIMA) and Artificial Neural Networks (ANN) methods in unemployment rate estimation. In this context, a stochastic trend in the unemployment rate was determined
Dilek Surekci Yamacli, Serhan Yamacli
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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)
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