Search Results - model estimation methods algorithm*
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…A computationally simple two-step iterative algorithm, called estimationapproximation algorithm, is introduced for estimating the parameters of the model on the basis of the rank estimators. …”
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Multiple equations model selection algorithm with iterative estimation method
Published 2016“…In particular, an algorithm on model selection for seemingly unrelated regression equations model using iterative feasible generalized least squares estimation method is proposed. …”
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Outlier Detections and Robust Estimation Methods for Nonlinear Regression Model Having Autocorrelated and Heteroscedastic Errors
Published 2010“…Finally, we proposed statistics practitioners to use the formal modeling algorithms to get better inferences. We also suggest them to employ appropriate robust methods for further analysis once a correct model has been chosen. …”
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Bayesian survival and hazard estimates for Weibull regression with censored data using modified Jeffreys prior
Published 2013“…We then incorporate covariates into the Weibull model. Under this regression model with regards to Bayesian, the usual method was not possible. …”
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Parameter estimation of tapioca starch hydrolysis process: Application of least squares and genetic algorithm
Published 2011Subjects: “…Gauss-Newton method…”
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Model selection approaches of water quality index data
Published 2016“…In order to select the best model, it is vital to ensure that proper estimation method is chosen in the modelling process.Different estimators have been proposed for the estimation of parameters of a model, including the least square and iterative estimators.This study aims to evaluate the forecasting performances of two algorithms on water quality index (WQI) of a river in Malaysia based on root mean square error (RMSE) and geometric root mean square error (GRMSE).Feasible generalised least squares (FGLS) and iterative maximum likelihood (ML) estimation methods are used in the algorithms, respectively.The results showed that SUREMLE-Autometrics has surpassed SURE-Autometrics; another simultaneous selection procedure of multipleequation models.Two individual selections, namely Autometrics-SUREMLE and Autometrics-SURE, though showed consistency only for GRMSE.All in all, ML estimation is a more appropriate method to be employed in this seemingly unrelated regression equations (SURE) model selection.…”
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Multifunctional optimized group method data handling for software effort estimation
Published 2022“…Group Method of Data Handling (GMDH) algorithms have been widely used for modelling and identifying complex systems and potentially applied in software effort estimation. …”
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An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems
Published 2019“…Based on the results, the QOBLESS method can be used as an efficient parameter estimation method in large-scale kinetic model building.…”
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Robust Estimation Methods And Outlier Detection In Mediation Models
Published 2010“…We suggest an alternative method for identification of high leverage points in the mediation model. …”
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Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data
Published 2011“…In this thesis, we considered two methods via the expectation maximization (EM) algorithm for cure rate estimation based on the BCH model using the two censoring types common to cancer clinical trials; namely, right and interval censoring. …”
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Air Pollution Index Estimation Model Based On Artificial Neural Network
Published 2021“…Three models were built in first part; ozone estimation model, particulate matter 10 (PM10) estimation model, and air pollution index (API) estimation model. …”
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An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems
Published 2019“…Based on the results, the QOBLESS method can be used as an efficient parameter estimation method in large-scale kinetic model building.…”
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Robust estimation methods for fixed effect panel data model having block-concentrated outliers
Published 2019“…The Ordinary Least Squares (OLS) is the commonly used method to estimate the parameters of fixed effect panel data model. …”
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QUANTIFYING CRITICAL PARAMETER IN DISEASE TRANSMISSION
Published 2015“…For numerical method, R programming algorithms were implemented to estimate the parameter faster and easier. …”
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A comparison of four different estimation approaches for prognostic survival oral cancer model
Published 2020“…Four types of estimation approaches for prognostic survival oral cancer model building are considered via a SAS algorithm: Efron’s Method, Exact Method, Breslow’s Method, and Discrete Method. …”
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Parametric cure fraction models for interval-censoring with a change-point based on a covariate threshold
Published 2015“…The parametric maximum likelihood estimation method is employed to verify the performance of the MCM within the framework of the expectation-maximization (EM) algorithm while the estimation methods for other models are employed in a simpler and straightforward setting. …”
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Robust techniques for linear regression with multicollinearity and outliers
Published 2016“…The proposed method is formulated by incorporating robust MM-estimator and the modified generalized M-estimator (MGM) in the LRR algorithm. …”
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Parameter estimation of tapioca starch hydrolysis process: application of least squares and genetic algorithm
Published 2005“…The performance of genetic algorithm (GA) in nonlinear kinetic parameter estimation of topiaca starch hydrolysis was studied and compared with Gauss-Newton method. …”
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Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares
Published 2009“…The Ordinary Least Squares (OLS) method is often used to estimate the parameters of a linear model. …”
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