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Simultaneous Prediction of Actual and Average Values of Study Variable Using Stein-rule Estimators [PDF]
, 2011 The simultaneous prediction of average and actual values of study variable in a linear regression model is considered in this paper. Generally, either of the ordinary least squares estimator or Stein-rule estimators are employed for the construction of ...
Shalabh, Shalabh +2 more
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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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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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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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A New Biased Estimator to Combat the Multicollinearity of the Gaussian Linear Regression Model
Stats, 2020 In a multiple linear regression model, the ordinary least squares estimator is inefficient when the multicollinearity problem exists. Many authors have proposed different estimators to overcome the multicollinearity problem for linear regression models ...
Issam Dawoud, B. M. Golam Kibria
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Stein-Rule Estimation under an Extended Balanced Loss Function [PDF]
, 2007 This paper extends the balanced loss function to a more general set up. The ordinary least squares and Stein-rule estimators are exposed to this general loss function with quadratic loss structure in a linear regression model.
Toutenburg, Helge +3 more
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Least squares fitting the three-parameter inverse Weibull density [PDF]
, 2010 The inverse Weibull model was developed by Erto [10]. In practice, the unknown parameters of the appropriate inverse Weibull density are not known and must be estimated from a random sample.
Marušić, Miljenko +5 more
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The estimations for parameter of Suja distribution with application
Alexandria Engineering JournalStrong relation between reliability studies and product quality. And reliability analysis deals with failure time of units and there are many well-known lifetime distributions.
Hanaa Abu-Zinadah, Tamadur Alsumairi
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Parameter Estimation for Long-Memory Stochastic Volatility at Discrete Observation
Abstract and Applied Analysis, 2014 Ordinary least squares estimators of variogram parameters in long-memory stochastic volatility are studied in this paper. We use the discrete observations for practical purposes under the assumption that the Hurst parameter H∈(1/2,1) is known.
Xiaohui Wang, Weiguo Zhang
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