Search Results - "errors in variables"

The application of simple errors in variables model on real data by Mohammadi, Mandana, Midi, Habshah, Rana, Sohel, Arasan, Jayanthi

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Bayesian approach to errors-in-variables in count data regression models / Nur Aainaa Rozliman by Nur Aainaa , Rozliman

“…In most practical applications, data sets are often contaminated with error or mismeasured covariates. When these errors-in-variables or measurement errors are not corrected, they will cause misleading statistical inferences and analysis. …”
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Parameter estimation of a continuous-time plant – the least-absolute error with variable forgetting factor method by Selamat, Hazlina, Yusof, Rubiyah, Goodall, Roger M.

“…The least-absolute error with variable forgetting factor (LAE+VFF) estimation method is proposed in this paper to estimate the parameters of time-varying continuous-time (C-T) systems. …”
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Instrumental-Variable Estimation Of Bangkokweather Effects In The Stock Exchange Of Thailand by Khanthavit, Anya

“…The incorrect fxed-effect assumption, missing-data problem, omitted-variable problem, and errors-in-variables (EIV) problem are estimation problems that are generally found in studies on weather effects on asset returns. …”
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Pseudorandom maximum length signal design with bias compensation least squares estimation for system identification by Foo, Mathias Fui Lin, Tang, Ai Hui, Basu, Kartik Prasad

“…This leads to the problem of errors-in-variables (EIV). The effectiveness of one particular EIV method, namely the bias compensation least squares estimation method, is analyzed, with simulations carried out on a first order bilinear system. …”
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The Evaluation of Asset Pricing Models in Hong Kong Stock Market by Chen, Ruoxi

“…The time series regression, cross sectional regression, GRS F-tests, Hansen and Jagannathan (1997) distance, the Fama-MacBeth (1973) t-test and the Shanken (1992) errors in variables (EIV) corrected t-test are used in this paper. …”
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Revisit problems encountered in linear regression models by Yip, Chee Yin, Lim, Hock Eam

“…The exogenous condition for linear regression is verified by using the triangular law of vectors and dot product of vectors. Errors in variables and missing variables are analyzed analytically. …”
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Reactivity ratio determination of newly synthesized copolymers from glycidyl methacrylate and tetrahydrofurfuryl acrylate by Ahmad Danial Azzahari, Rosiyah Yahya, Aziz Hassan

“…Reactivity ratios for GMA and THFA were determined by the Kelen-Tudos, Tidwell-Mortimer and error-in-variables model methods. The results showed that all these copolymerizations were strictly linear systems describable by the Mayo-Lewis equation based on the terminal model and that accurate reactivity ratio data can be obtained.…”
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Modelling wind speed data in Pulau Langkawi with functional relationship by Nur Ain Al-Hameefatul Jamaliyatul, Basri Badyalina, Nurkhairany Amyra Mokhtar, Adzhar Rambli, Yong Zulina Zubairi, Adilah Abdul Ghapor

“…To model wind speed data that follows a normal distribution. An error-in-variables model (EIVM) is utilised, which is a linear functional relationship model (LFRM). …”
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Railway wheelset parameter estimation using signals from lateral velocity sensor by Selamat, H., Alimin, A. J., Sam, Y.M.

“…A type of parameter estimation technique based on the linear integral filter (LIF) method, the least-absolute error with variable forgetting factor (LAE+VFF) estimation method, is proposed in this paper to estimate the railway wheelset parameters modelled as a time-varying continuous-time (C-T) system. …”
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Path planning and parameter optimization of uniform removal in active feed polishing by Liu, Jian, Wang, S., Zhang, C., Zhang, L., Chen, H.

“…In order to maintain the processed figure error, a variable pitch spiral path planning algorithm and the dwell time-solving model are proposed. …”
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Embedded explicit Runge–Kutta type methods for directly solving special third order differential equations y‴=f(x,y) by Senu, Norazak, Mechee, Mohammed Sahib, Ismail, Fudziah, Siri, Zailan

“…The methods are derived with the strategies such that the higher order methods are very accurate and the lower order methods will give the best error estimates. Variables stepsize codes are developed based on the methods and used to solve a set of special third order problems. …”
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Applications of Linear and Nonlinear Models by Grafarend, E., Awange, Joseph

“…Collocation is an example.Another speciality is our sixth problem of probabilistic regression, the model "errors-in-variable”, also called Total Least Squares, namely SIMEX and SYMEX developed by Carroll-Cook-Stefanski-Polzehl-Zwanzig. …”
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Volatility forecasting approach to risk assessment of private equity mutual funds in Malaysia by Wan, Cheong Kin

“…However, the robust and outlier resilience STES with Error and Absolute Error transition variable is the overall best model in the one-day ahead volatility forecasting. …”
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