Decomposition based least squares iterative estimation algorithm for output error moving average systems

2014 ◽  
Vol 31 (4) ◽  
pp. 709-725 ◽  
Author(s):  
Wenge Zhang
Keyword(s):  
Least Squares ◽  
Design Methodology ◽  
Moving Average ◽  
Estimation Algorithm ◽  
Identification Algorithm ◽  
Iterative Identification ◽  
Iterative Estimation ◽  
Content Type ◽  
Engineering Computation ◽  
Parameter Estimation Algorithm

Purpose – The purpose of this paper is to solve the heavy computational problem of parameter estimation algorithm. Design/methodology/approach – Presents a decomposition least squares based iterative identification algorithm. Findings – Can estimate the parameters for linear or pseudo-linear systems and have lower computational burden. Originality/value – This paper adopts a decomposition technique to solve engineering computation problems and offers a potential and efficient algorithm.

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

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Weili Xiong ◽  
Wei Fan ◽  
Rui Ding
Keyword(s):  
Parameter Estimation ◽  
Nonlinear Systems ◽  
Least Squares ◽  
Moving Average ◽  
Estimation Algorithm ◽  
Autoregressive Moving Average ◽  
Parameter Estimates ◽  
Persistent Excitation ◽  
Estimation Algorithms ◽  
Parameter Estimation Algorithm

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-CARARMA) model. The basic idea is to obtain linear-in-parameters models by overparameterizing such nonlinear systems and to use the least-squares algorithm to estimate the unknown parameter vectors. It is proved that the parameter estimates consistently converge to their true values under the persistent excitation condition. A simulation example is provided.

When social media met commerce: a model of perceived customer value in group-buying

2016 ◽  
Vol 30 (4) ◽  
pp. 398-410 ◽  
Author(s):  
Yong-Ki Lee ◽  
Sally Y. Kim ◽  
Namho Chung ◽  
Kwanghoon Ahn ◽  
Jong-Won Lee
Keyword(s):  
Social Media ◽  
Least Squares ◽  
Significant Influence ◽  
Customer Value ◽  
Design Methodology ◽  
Social Commerce ◽  
Research Directions ◽  
Content Type ◽  
Group Buying ◽  
Perceived Customer Value

Purpose Social commerce using social media has been on the rapid increase. Among various social commerce models, group-buying has become the mainstream. There is a paucity of research related to how customers perceive value in group-buying situations. This paper aims to examine and analyze various factors that influence perceived customer value in group-buying. Design/methodology/approach Data were collected using a survey on customers who had purchased a restaurant service deal on a group-buying site. A partial least squares technique was used to estimate the model. Findings Results show that perceived customer value affects customers’ group buying intentions and that all four antecedents of perceived value (low price, valence of experience, trust in social media and reputation of the group-buying site) have a significant influence. Implications and further research directions are discussed at the end of the paper. Originality/value This study provides valuable strategic implications for social commerce firms.

Research of Fan System Identification Based on Improved Bayes Algorithm

2011 ◽  
Vol 66-68 ◽  
pp. 448-453
Author(s):  
Hai Tao Wang ◽  
Ze Zhang
Keyword(s):  
System Identification ◽  
Dynamic Characteristics ◽  
System Modeling ◽  
Estimation Algorithm ◽  
Parametric Model ◽  
Testing System ◽  
Identification Algorithm ◽  
Environment Protection ◽  
Parameter Estimation Algorithm ◽  
Bayes Algorithm

In every filed of natural science, more and more researchers attach importance to system quantitative analysis, control and prediction. In filed of automatic control, system identification is the extension of system dynamic characteristics testing. System modeling is the basis of system identification, non-parametric model can be obtained by means of dynamic characteristics testing, but parametric model must be established by means of parameter estimation algorithm, which is more prevalent than dynamic characteristics testing. Coal power plant produces more gas and dust, so how to control the fan system plays a very important role in environment protection. We must clarify the parameter of fan system before controlling it. The traditional Bayes identification algorithm is used widely in research and industry, and the effect is relatively good. The paper induces the concept of loss function based on traditional Bayes identification algorithm, and proposes an improved Bayes identification algorithm, which can be applied to fan system identification successfully.

Do females in audit firm governance affect firm performance? Findings from Turkey

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Murat Ocak
Keyword(s):  
Firm Performance ◽  
Least Squares ◽  
Design Methodology ◽  
Gender Diversity ◽  
Ordinary Least Squares ◽  
Content Type ◽  
Audit Firm ◽  
Hierarchical Levels ◽  
And Gender ◽  
Practical Implications

Purpose This study aims to contribute to the literature by offering a different sector and emphasising the importance of females in audit firm (AF) governance on audit firm performance (AFP). Design/methodology/approach Ordinary least squares (OLS) and instrument variables regression (IVREG) with two-stage least squares are used to test the paper’s hypotheses. Findings Both OLS and IVREG estimation results show that both the proportion of females and gender diversity at board and owner levels and the total number of shares of female owners seem to enhance the performance of AFs. Practical implications These results may be important for policymakers and regulators to set a quota for women’s representation on AF governance or decide arrangements for women in AFs as in the regulations for the high hierarchical levels of other corporate firms. Originality/value This paper extends the current literature in the context of AFs in Turkey, positing that females in AF governance might enhance performance to a great extent.

Do accountability and transparency promote community trust? Evidence from village government in Indonesia

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hafiez Sofyani ◽  
Suryo Pratolo ◽  
Zakiah Saleh
Keyword(s):  
Least Squares ◽  
Questionnaire Survey ◽  
Design Methodology ◽  
Research Data ◽  
Organisational Commitment ◽  
Content Type ◽  
Village Community ◽  
Community Trust ◽  
Village Government ◽  
Special Region

Purpose This study aims to examine the determinants of accountability and transparency of Indonesian village government(s), namely, the competence and organisational commitment of village government staff, and the consequences of accountability and transparency for village community trust. Design/methodology/approach This research was conducted in village governments in the province of the Special Region of Yogyakarta, covering four regencies: Sleman, Bantul, Kulon Progo and Gunung Kidul. A total of 128 village governments participated in this research. Data were collected by distributing a questionnaire survey, and a partial least squares technique was used to test the research hypotheses. Findings The study revealed that village government staff's competence and organisational commitment are positively associated with accountability. However, organisational commitment and accountability are not associated with transparency. In addition, it was discovered that transparency is positively associated with village community trust but accountability is not. Originality By testing the determinants and consequences of accountability and transparency following the ratification of the new village law regulating village government governance, this study is, to the best of the authors’ knowledge, pioneering research.

Customer insurance frauds: the influence of fraud type, moral intensity and fairness perception

2019 ◽  
Vol 45 (3) ◽  
pp. 452-467 ◽  
Author(s):  
Lu-Ming Tseng
Keyword(s):  
Least Squares ◽  
Design Methodology ◽  
Partial Least Squares Regression ◽  
Empirical Investigation ◽  
Moral Intensity ◽  
Demographic Variables ◽  
Insurance Fraud ◽  
Least Squares Regression ◽  
Content Type ◽  
Fairness Perception

Purpose The purpose of this paper is to examine customers’ ethical attitudes (EA) and intentions toward two types of insurance frauds. This study proposes that the factors, such as fraud types (i.e. opportunistic and planned insurance fraud), moral intensity and fairness perception (FP), can affect the customers’ acceptance of the insurance frauds. Design/methodology/approach To test the research hypotheses of this study, Taiwanese insurance customers are invited in the empirical investigation, and a scenario-based questionnaire is used to collect the data. The hypotheses of this study are tested by using a partial least squares regression. Findings The results show that moral intensity constructs and FP significantly relate to the respondents’ acceptance of insurance frauds, while fraud types also have significant impacts on the respondents’ perceptions of moral intensity and fairness. Originality/value There is no research which has examined the relationships among fraud types, moral intensity, FP, demographic variables and customers’ EA and intentions toward insurance frauds. Understanding the relationships among these variables could provide implications for those involved in the practice of anti-fraud programs.

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