Results 21 to 30 of about 10,511 (262)

ESTIMASI PARAMETER MODEL MIXTURE AUTOREGRESSIVE (MAR) MENGGUNAKAN ALGORITMA EKSPEKTASI MAKSIMISASI (EM)

Media Statistika, 2013
Mixture autoregressive (MAR) Model is a mixture of Gaussian autoregressive (AR) components. The mixture model is capable for modelling of nonlinear time series with multimodal conditional distributions.
Mika Asrini, Winita Sulandari, Santoso Budi Wiyono   +2 more
doaj   +1 more source

An Improved Method for Stochastic Nonlinear System’s Identification Using Fuzzy-Type Output-Error Autoregressive Hammerstein–Wiener Model Based on Gradient Algorithm, Multi-Innovation, and Data Filtering Techniques

Complexity, 2021
This paper proposes an innovative identification approach of nonlinear stochastic systems using Hammerstein–Wiener (HW) model with output-error autoregressive (OEA) noise.
Donia Ben Halima Abid, Saif Eddine Abouda, Hanane Medhaffar, Mohamed Chtourou   +3 more
doaj   +1 more source

Modeling Autoregressive Processes with Moving-Quantiles-Implied Nonlinearity [PDF]

Econometrics, 2015
We introduce and investigate some properties of a class of nonlinear time series models based on the moving sample quantiles in the autoregressive data generating process. We derive a test fit to detect this type of nonlinearity. Using the daily realized volatility data of Standard & Poor’s 500 (S&P 500) and several other indices, we obtained ...
Isao Ishida, Virmantas Kvedaras
openaire   +3 more sources

Least-Squares Parameter Estimation Algorithm for a Class of Input Nonlinear Systems

Journal of Applied Mathematics, 2012
This paper studies least-squares parameter estimation algorithms for input nonlinear systems, including the input nonlinear controlled autoregressive (IN-CAR) model and the input nonlinear controlled autoregressive autoregressive moving average (IN ...
Weili Xiong, Wei Fan, Rui Ding
doaj   +1 more source

Nonlinear modelling of periodic threshold autoregressions using Tsmars [PDF]

Journal of Time Series Analysis, 2002
We present new methods for modelling nonlinear threshold‐type autoregressive behaviour in periodically correlated time series. The methods are illustrated using a series of average monthly flows of the Fraser River in British Columbia. Commonly used nonlinearity tests of the river flow data in each month indicate nonlinear behaviour in certain months ...
Lewis, Peter A.W., Ray, Bonnie K.
openaire   +3 more sources

A Time Series Prediction Model of Foundation Pit Deformation Based on Empirical Wavelet Transform and NARX Network

Mathematics, 2020
Large deep foundation pits are usually in a complex environment, so their surface deformation tends to show a stable rising trend with a small range of fluctuation, which brings certain difficulty to the prediction work.
Qingwen Ma, Sihan Liu, Xinyu Fan, Chen Chai, Yangyang Wang, Ke Yang   +5 more
doaj   +1 more source

Latent carbon emission pricing model for Thailand: A nonlinear autoregressive distributed lag model

Energy Reports, 2022
Nowadays, many scientific researchers confirm that carbon emissions cause global warming. Accurate carbon emission pricing is a direct economic measure of greenhouse gas emissions’ actual cost or price.
Roengchai Tansuchat, Chia-Lin Chang
doaj   +1 more source

Two-Stage Spatiotemporal Time Series Modelling Approach for Rice Yield Prediction & Advanced Agroecosystem Management

Agronomy, 2021
A robust forecast of rice yields is of great importance for medium-to-long-term planning and decision-making in cereal production, from regional to national level.
Santosha Rathod, Amit Saha, Rahul Patil, Gabrijel Ondrasek, Channappa Gireesh, Madhyavenkatapura Siddaiah Anantha, Dhumannatarao Venkata Krishna Nageswara Rao, Nirmala Bandumula, Ponnuvel Senguttuvel, Arun Kumar Swarnaraj, Shaik N. Meera, Amtul Waris, Ponnuraj Jeyakumar, Brajendra Parmar, Pitchiahpillai Muthuraman, Raman Meenakshi Sundaram   +15 more
doaj   +1 more source

Adaptive Control Using Neural Networks and Approximate Models for Nonlinear Dynamic Systems

Modelling and Simulation in Engineering, 2020
In this research, a comparative study of two recurrent neural networks, nonlinear autoregressive with exogenous input (NARX) neural network and nonlinear autoregressive moving average (NARMA-L2), and a feedforward neural network (FFNN) is performed for ...
Khadija El Hamidi, Mostafa Mjahed, Abdeljalil El Kari, Hassan Ayad   +3 more
doaj   +1 more source

A Semiparametric Approach for Modeling Partially Linear Autoregressive Model with Skew Normal Innovations

Advances in Mathematical Physics, 2022
The nonlinear autoregressive models under normal innovations are commonly used for nonlinear time series analysis in various fields. However, using this class of models for modeling skewed data leads to unreliable results due to the disability of these ...
Leila Sakhabakhsh, Rahman Farnoosh, Afshin Fallah, Mohammadhassan Behzadi   +3 more
doaj   +1 more source