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
doaj +2 more sources
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
doaj +2 more sources
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
doaj +2 more sources
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
doaj +2 more sources
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
doaj +2 more sources
Journal of Probability and Statistics, 2018 The analysis of misspecification was extended to the recently introduced stochastic restricted biased estimators when multicollinearity exists among the explanatory variables. The Stochastic Restricted Ridge Estimator (SRRE), Stochastic Restricted Almost
Manickavasagar Kayanan +1 more
doaj +3 more sources
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
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source
Unbiased Area Estimation Using Copernicus High Resolution Layers and Reference Data
Remote Sensing, 2022 Land cover area estimates can be derived via design-based approaches using a probability (random) reference sample. The collection of samples is usually costly and requires an effective sampling design.
Luca Kleinewillinghöfer +6 more
doaj +1 more source