Results 11 to 20 of about 12,224 (267)
INVESTIGATING THE IMPACT OF MULTICOLLINEARITY ON LINEAR REGRESSION ESTIMATES [PDF]
Malaysian Journal of Computing, 2021 The study was to investigate the impact of multicollinearity on linear regression estimates. The study was guided by the following specific objectives, (i) to examine the asymptotic properties of estimators and (ii) to compare lasso, ridge, elastic ...
Adewoye Kunle Bayo +3 more
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A New Convex Estimator Combining Ridge and Ordinary Least Squares Estimators [PDF]
مجلة جامعة الانبار للعلوم الصرفةIn the presence of high correlation between the independent variables in the linear regression model, which is known as the multicollinearity problem, the ordinary least squares estimator produce large variations in the sample.
Karam Al-janabi, Mustafa Alheety
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Journal of Advanced Research in Natural and Applied Sciences, 2020 The determination of leverage observations have been frequently investigated through ordinary least squares and some biased estimators proposed under the multicollinearity problem in the linear regression models.
Tuğba Söküt
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Least squares image matching: A comparison of the performance of robust estimators [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2014 Least squares image matching (LSM) has been extensively applied and researched for high matching accuracy. However, it still suffers from some problems. Firstly, it needs the appropriate estimate of initial value.
Z. Li, J. Wang
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Topp–Leone odd log-logistic exponential distribution: Its improved estimators and applications
Anais da Academia Brasileira de Ciências, 2021 In this paper, a new three-parameter lifetime model called the Topp–Leone odd log-logistic exponential distribution is proposed. Its density function can be expressed as a linear mixture of exponentiated exponential densities and can be reversed-J shaped,
AHMED Z. AFIFY +2 more
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Journal of Probability and Statistics, 2020 This study compared a ridge maximum likelihood estimator to Yuan and Chan (2008) ridge maximum likelihood, maximum likelihood, unweighted least squares, generalized least squares, and asymptotic distribution-free estimators in fitting six models that ...
David Adedia +2 more
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Mathematics, 2020 In this paper, we study a new flexible three-parameter exponential distribution called the extended odd Weibull exponential distribution, which can have constant, decreasing, increasing, bathtub, upside-down bathtub and reversed-J shaped hazard rates ...
Ahmed Z. Afify, Osama Abdo Mohamed
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Estimation of the Mixed Gamma Distributions Parameters Based on Censored Life test Data [PDF]
The Egyptian Statistical Journal, 1989 This work concerns with the estimation of scale parameters and mixture proportion of two gamma distributions. Using maximum likelihood and weighted least. Squares methods the estimation is carried out when the data are ungrouped and censored. A simulated
E.M Shoukry, Abd-Elghani M.
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a simulation comparison of Ridge regression estimators with Lars
پژوهشهای ریاضی, 2022 Introduction Regression analysis is a common method for modeling relationships between variables. Usually Ordinary Least Squares method is applied to estimate regression model parameters.
Roshanak Alimohammadi, Jaleh Bahari
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On Robust Estimation of Error Variance in (Highly) Robust Regression
Measurement Science Review, 2020 The linear regression model requires robust estimation of parameters, if the measured data are contaminated by outlying measurements (outliers). While a number of robust estimators (i.e. resistant to outliers) have been proposed, this paper is focused on
Kalina Jan, Tichavský Jan
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