Estimating Crop Area at County Level on the North China Plain with an Indirect Sampling of Segments and an Adapted Regression Estimator [PDF]
Sensors, 2017 Image classifications, including sub-pixel analysis, are often used to estimate crop acreage directly. However, this type of assessment often leads to a biased estimation, because commission and omission errors generally do not compensate for each other.
Qinghan Dong +4 more
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Biased proportional hazard regression estimator in the existence of collinearity [PDF]
Heliyon, 2023 This paper proposed a new biased proportional hazard regression (PHR) estimator which is the combination of elastic net proportional hazard regression (ENPHR) and principal components proportional hazard regression (PCPHR) estimator.
Anu Sirohi +3 more
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On a Mixed Poisson Liu Regression Estimator for Overdispersed and Multicollinear Count Data [PDF]
The Scientific World Journal, 2022 The mixed Poisson regression models are commonly employed to analyze the overdispersed count data. However, multicollinearity is a common issue when estimating the regression coefficients by using the maximum likelihood estimator (MLE) in such regression
Ramajeyam Tharshan +1 more
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K-L Estimator: Dealing with Multicollinearity in the Logistic Regression Model
Mathematics, 2023 Multicollinearity negatively affects the efficiency of the maximum likelihood estimator (MLE) in both the linear and generalized linear models. The Kibria and Lukman estimator (KLE) was developed as an alternative to the MLE to handle multicollinearity ...
Adewale F. Lukman +5 more
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A Stochastic Restricted Principal Components Regression Estimator in the Linear Model [PDF]
The Scientific World Journal, 2014 We propose a new estimator to combat the multicollinearity in the linear model when there are stochastic linear restrictions on the regression coefficients.
Daojiang He, Yan Wu
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The chain ratio estimator and regression estimator with linear combination of two auxiliary variables. [PDF]
PLoS ONE, 2013 In sample surveys, it is usual to make use of auxiliary information to increase the precision of the estimators. We propose a new chain ratio estimator and regression estimator of a finite population mean using linear combination of two auxiliary ...
Jingli Lu
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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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A new biased regression estimator: Theory, simulation and application
Scientific African, 2022 The linear regression model explores the relationship between a response variable and one or more independent variables. The ordinary least squared estimator is usually adopted to estimate the parameters of the model when the independent variables are ...
Issam Dawoud +2 more
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A chain regression exponential type imputation method for mean estimation in the presence of missing data [PDF]
Songklanakarin Journal of Science and Technology (SJST), 2022 Imputation methods deal with item nonresponse to solve the missing data problem. A new imputation method and corresponding point estimators for population mean have been proposed under two situations: using the response rate and the constant that gives
Kanisa Chodjuntug, Nuanpan Lawson
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Predictive efficiency of ridge regression estimator [PDF]
Yugoslav Journal of Operations Research, 2017 In this article we have considered the problem of prediction within and outside the sample for actual and average values of the study variables in case of ordinary least squares and ridge regression estimators.
Tiwari Manoj, Sharma Amit
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