Search Results - (( using simulation method algorithm ) OR ( variable regression methods algorithm ))

Search alternatives:

Refine Results
  1. 1
    Comparing three methods of handling multicollinearity using simulation approach

    Comparing three methods of handling multicollinearity using simulation approach by Adnan, Norliza

    Published 2006
    “…The algorithm is described and for the purpose of comparing the three methods, simulated data sets where the number of cases was less than the number of observations were used. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  2. 2
    Penalized Quantile Regression Methods And Empirical Mode Decomposition For Improving The Accuracy Of The Model Selection

    Penalized Quantile Regression Methods And Empirical Mode Decomposition For Improving The Accuracy Of The Model Selection by Ambark, Ali Saleh Al-Massri

    Published 2024
    “…To verify the prediction performance of the proposed methods, the proposed methods are compared with three existing regression methods used in previous studies. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  3. 3
    A Comparative Study On Some Methods For Handling Multicollinearity Problems

    A Comparative Study On Some Methods For Handling Multicollinearity Problems by Adnan, Norliza, Ahmad, Maizah Hura, Adnan, Robiah

    Published 2006
    “…The algorithm is described and for the purpose of comparing the three methods, simulated data sets where the number of cases were less than the number of observations used. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  4. 4
    Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification

    Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification by Abd Samad, Md Fahmi

    Published 2011
    “…A deterministic mutation-based algorithm is introduced to overcome this problem. Identification studies using NARX (Nonlinear AutoRegressive with eXogenous input) models employing simulated systems and real plant data are used to demonstrate that the algorithm is able to detect significant variables and terms faster and to select a simpler model structure than other well-known EC methods.…”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  5. 5
    A comparative study on some methods for handling multicollinearity problems

    A comparative study on some methods for handling multicollinearity problems by Adnan, Norliza, Ahmad, Maizah Hura, Adnan, Robiah

    Published 2006
    “…The algorithm is described and for the purpose of comparing the three methods, simulated data sets where the number of cases were less than the number of observations used. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  6. 6
    Robust multivariate least angle regression

    Robust multivariate least angle regression by Uraibi, Hassan Sami, Midi, Habshah, Rana, Sohel

    Published 2017
    “…The least angle regression selection (LARS) algorithms that use the classical sample means, variances, and correlations between the original variables are very sensitive to the presence of outliers and other contamination. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  7. 7
    Elastic net penalized Quantile Regression Model and Empirical Mode Decomposition for Improving the Accuracy of the Model Selection

    Elastic net penalized Quantile Regression Model and Empirical Mode Decomposition for Improving the Accuracy of the Model Selection by Ali S.A. Ambark, Mohd Tahir Ismail, Abdullah S. Al-Jawarneh, Samsul Ariffin Abdul Karim

    Published 2023
    “…Such methods are ridge penalized quantile regression, lasso penalized quantile regression, and elastic net penalized quantile regression which are used for variable selection and regularization and deals with the multicollinearity problem when it exists between the predictor variables. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  8. 8
    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli

    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

    Published 2018
    “…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  9. 9
    Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm

    Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm by Nur Azulia, Kamarudin

    Published 2019
    “…However, SURE-Autometrics has not been estimated using maximum likelihood estimation (MLE). Therefore, in this study SUREAutometrics is improvised using two MLE methods, which are iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm, named as SURE(IFGLS)-Autometrics and SURE(EM)-Autometrics algorithms. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  10. 10
    Sure (EM)-Autometrics: An Automated Model Selection Procedure with Expectation Maximization Algorithm Estimation Method (S/O 14925)

    Sure (EM)-Autometrics: An Automated Model Selection Procedure with Expectation Maximization Algorithm Estimation Method (S/O 14925) by Kamarudin, Nur Azulia

    Published 2021
    “…Despite numerous emergences of procedures in selecting models automatically, there has been a lack of studies on procedures in selecting multiple equations models, particularly seemingly unrelated regression equations (SURE) models. Hence, this study concentrates on an automated model selection procedure for the SURE model by integrating the expectation-maximization (EM) algorithm estimation method, named SURE(EM)-Autometrics. …”
    Get full text
    Get full text
    Monograph
    Save to List
    Saved in:
  11. 11
    Deterministic Mutation Algorithm As A Winner Over Forward Selection Procedure

    Deterministic Mutation Algorithm As A Winner Over Forward Selection Procedure by Md Fahmi, Abd Samad

    Published 2016
    “…In the real data simulation, both methods obtained the same model structure whereas in simulated data modelling, only DMA was able to select the correct model structure. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  12. 12
    Cutpoint determination methods in competing risks subdistribution model

    Cutpoint determination methods in competing risks subdistribution model by Noor Akma Ibrahim, Abdul Kudus, Isa Daud, Mohd. Rizam Abu Bakar

    Published 2009
    “…Simulation results show that the deviance method has the desired properties. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  13. 13
    Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari

    Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

    Published 2015
    “…Model verification of all method and model proposed in this study are examined using the simulation study. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  14. 14
    Automated time series forecasting

    Automated time series forecasting by Ismail, Suzilah, Zakaria, Rohaiza, Tuan Muda, Tuan Zalizam

    Published 2011
    “…Moving Average, Decomposition, Exponential Smoothing, Time Series Regressions and ARIMA) were used.The algorithm was developed in JAVA using up to date forecasting process such as data partition, several error measures and rolling process.Successfully, the results of the algorithm tally with the results of SPSS and Excel.This automatic forecasting will not just benefit forecaster but also end users who do not have in depth knowledge about forecasting techniques.…”
    Get full text
    Get full text
    Get full text
    Monograph
    Save to List
    Saved in:
  15. 15
    Robust Estimation Methods And Outlier Detection In Mediation Models

    Robust Estimation Methods And Outlier Detection In Mediation Models by Fitrianto, Anwar

    Published 2010
    “…Simple mediation model consists of three regression equations. The Ordinary Least Squares (OLS) method is often use to estimate the parameters of the mediation model. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  16. 16
    Cutpoint determination methods in competing risks subdistribution model

    Cutpoint determination methods in competing risks subdistribution model by Ibrahim, Noor Akma, Kudus, Abdul, Daud, Isa, Abu Bakar, Mohd Rizam

    Published 2009
    “…Simulation results show that the deviance method has the desired properties. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  17. 17
    Information Theoretic-based Feature Selection for Machine Learning

    Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

    Published 2018
    “…The second test evaluates IFS in a controlled study using simulated datasets. Moreover, the third test used ten natural domain datasets obtained from UCI Repository, in about fifteen different experiments, using three to four different Machine Learning Algorithms for performance evaluation. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  18. 18
    Optimization of process parameters for pyrolsis of waste plastics by T method-1

    Optimization of process parameters for pyrolsis of waste plastics by T method-1 by Shankaran A/l Thiyagarajan

    Published 2023
    text::Final Year Project
    Save to List
    Saved in:
  19. 19
    Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data

    Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data by Oyebayo, Olaniran Ridwan

    Published 2018
    “…Random Forests (RF) are ensemble of trees methods widely used for data prediction, interpretation and variable selection purposes. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  20. 20
    Support vector machine and its applications for linear and nonlinear regression in the presence of outliers of high dimensional data

    Support vector machine and its applications for linear and nonlinear regression in the presence of outliers of high dimensional data by Sleabi, Waleed Dhhan

    Published 2016
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:

Search Tools: