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2019
Chapter 5 describes three sets of auxiliary methods that have emerged as add-on supplements to the traditional ARIMA model-building strategy. First, Bayesian information criteria (BIC) can be used to inform incremental modeling decisions. BICs are also the basis for the Bayesian hypothesis tests introduced in Chapter 6.
David McDowall +2 more
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Chapter 5 describes three sets of auxiliary methods that have emerged as add-on supplements to the traditional ARIMA model-building strategy. First, Bayesian information criteria (BIC) can be used to inform incremental modeling decisions. BICs are also the basis for the Bayesian hypothesis tests introduced in Chapter 6.
David McDowall +2 more
openaire +1 more source
J. Syst. Control. Eng.
Identification of multivariable systems is of great significance to control systems. This paper focuses on the parameter identification problems for multivariable autoregressive output-error autoregressive moving average (M-AROEARMA) systems.
Qian Zhang, Huihui Wang, Ximei Liu
semanticscholar +1 more source
Identification of multivariable systems is of great significance to control systems. This paper focuses on the parameter identification problems for multivariable autoregressive output-error autoregressive moving average (M-AROEARMA) systems.
Qian Zhang, Huihui Wang, Ximei Liu
semanticscholar +1 more source
Optimal control applications & methods
This article considers the iterative identification problems for a class of feedback nonlinear systems with moving average noise. The model contains both the dynamic linear module and the static nonlinear module, which brings challenges to the ...
Lijuan Liu +3 more
semanticscholar +1 more source
This article considers the iterative identification problems for a class of feedback nonlinear systems with moving average noise. The model contains both the dynamic linear module and the static nonlinear module, which brings challenges to the ...
Lijuan Liu +3 more
semanticscholar +1 more source
Auxiliary mixture sampling with applications to logistic models
Computational Statistics & Data Analysis, 2007zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Sylvia Frühwirth-Schnatter +1 more
openaire +2 more sources
IEEE Transactions on Instrumentation and Measurement
This article investigates the problem of robust parameter estimation for the Hammerstein output-error (OE) system with outlier-contaminated and randomly missing outputs. The outliers and data missing are relatively common problems in industrial processes,
Xin Liu, Chen Wang, Wei Dai
semanticscholar +1 more source
This article investigates the problem of robust parameter estimation for the Hammerstein output-error (OE) system with outlier-contaminated and randomly missing outputs. The outliers and data missing are relatively common problems in industrial processes,
Xin Liu, Chen Wang, Wei Dai
semanticscholar +1 more source
Journal of the Franklin Institute, 2020
This paper studies the parameter estimation algorithms of multivariate output-error autoregressive moving average (M-OEARMA) systems. By means of the filtering technique and the auxiliary model identification idea, this paper gives an auxiliary model ...
F. Ding +3 more
semanticscholar +1 more source
This paper studies the parameter estimation algorithms of multivariate output-error autoregressive moving average (M-OEARMA) systems. By means of the filtering technique and the auxiliary model identification idea, this paper gives an auxiliary model ...
F. Ding +3 more
semanticscholar +1 more source
Scrambled Response Models Based on Auxiliary Variables
2013We discuss the problem of obtaining reliable data on a sensitive quantitative variable without jeopardizing respondent privacy. The information is obtained by asking respondents to perturb the response through a scrambling mechanism. A general device allowing for the use of multi-auxiliary variables is illustrated as well as a class of estimators for ...
Diana G, PERRI, PIER FRANCESCO
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Journal of the Franklin Institute, 2019
This paper focuses on the identification of multiple-input single-output output-error systems with unknown time-delays. Since the time-delays are unknown, an identification model with a high dimensional and sparse parameter vector is derived based on ...
Junyao You, Yanjun Liu, J. Chen, F. Ding
semanticscholar +1 more source
This paper focuses on the identification of multiple-input single-output output-error systems with unknown time-delays. Since the time-delays are unknown, an identification model with a high dimensional and sparse parameter vector is derived based on ...
Junyao You, Yanjun Liu, J. Chen, F. Ding
semanticscholar +1 more source
Modeling of Systems of Automated Auxiliary Processes in Pharmaceutical Industry
2021The computer model of the device with the CIP (clean in place) system allows at the design stage to reduce the cost of implementation and commissioning. A computer model of the bioreactor washing process using the CIP system was built. Using the ANSYS finite element analysis system, diagrams of the distribution of fluid flows for different supply ...
Igor Korobiichuk +3 more
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Optimal control applications & methods
This paper considers recursive parameter identification for autoregressive output‐error autoregressive moving average (AR‐OE‐ARMA) systems from the perspective of computational efficiency. By means of the hierarchical identification principle, we propose
Feng Ding +3 more
semanticscholar +1 more source
This paper considers recursive parameter identification for autoregressive output‐error autoregressive moving average (AR‐OE‐ARMA) systems from the perspective of computational efficiency. By means of the hierarchical identification principle, we propose
Feng Ding +3 more
semanticscholar +1 more source