Results 1 to 10 of about 172,938 (287)

Stochastic Restricted Biased Estimators in Misspecified Regression Model with Incomplete Prior Information

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, Pushpakanthie Wijekoon   +1 more
doaj   +3 more sources

A New Mixed Biased Estimator for Ill‐Conditioning Challenges in Linear Regression Model With Chemometrics Applications [PDF]

Analytical Science Advances
In linear regression models, the ordinary least squares (OLS) method is used to estimate the unknown regression coefficients. However, the OLS estimator may provide unreliable estimates in non‐orthogonal models.
Muhammad Amin, Sadiah M. A. Aljeddani, Muhammad Nauman Akram, Sajida Yasmeen   +3 more
doaj   +2 more sources

New two parameter hybrid estimator for zero inflated negative binomial regression models [PDF]

Scientific Reports
The zero-inflated negative binomial regression (ZINBR) model is used for modeling count data that exhibit both overdispersion and zero-inflated counts. However, a persistent challenge in the efficient estimation of parameters within ZINBR models is the ...
Fatimah A. Almulhim, M. Nagy, Ali T. Hammad, A. H. Mansi, Getachew Tekle Mekiso, M. M. Abd El-Raouf   +5 more
doaj   +2 more sources

New robust two-parameter estimator for overcoming outliers and multicollinearity in Poisson regression model [PDF]

Scientific Reports
The Poisson maximum likelihood estimator (PMLE) is commonly used to estimate the coefficients of the Poisson regression model (PRM). However, it is well known that the PMLE is highly sensitive to outliers, which can distort the estimated coefficients and
Hebatalla H. Mohammad, Ali T. Hammad, Abeer A. EL-Helbawy, Zakiah I. Kalantan, Alexis Habineza, Eslam Hussam, Ahmed M. Gemeay   +6 more
doaj   +2 more sources

Evaluating AUC estimators across complex sampling designs: insights from COVID-19 patient data [PDF]

BMC Medical Research Methodology
Purpose Many studies in medical research are currently based on large-scale health surveys. Data collected in these surveys are usually obtained by following complex sampling designs, which include techniques such as stratification and clustering.
Amaia Iparragirre, José María Quintana-López, Irantzu Barrio   +2 more
doaj   +2 more sources

On Restricted Shrinkage Jackknife Biased Estimator for Restricted Linear Regression Model [PDF]

مجلة جامعة الانبار للعلوم الصرفة, 2023
In restricted linear regression model, more methods proposed to address the Multicollinearity problem and the high variance. For example, shrinkage biased estimation and optimization (Lagrange function).
Ahmed Mohammed, Feras Algareri
doaj   +1 more source

A new class of Poisson Ridge-type estimator

Scientific Reports, 2023
The Poisson Regression Model (PRM) is one of the benchmark models when analyzing the count data. The Maximum Likelihood Estimator (MLE) is used to estimate the model parameters in PRMs. However, the MLE may suffer from various drawbacks that arise due to
Esra Ertan, Kadri Ulaş Akay
doaj   +1 more source

A New Two-Parameter Estimator for Beta Regression Model: Method, Simulation, and Application

Frontiers in Applied Mathematics and Statistics, 2022
The beta regression is a widely known statistical model when the response (or the dependent) variable has the form of fractions or percentages. In most of the situations in beta regression, the explanatory variables are related to each other which is ...
Mohamed R. Abonazel, Zakariya Yahya Algamal, Fuad A. Awwad, Ibrahim M. Taha   +3 more
doaj   +1 more source

Kibria-Lukman Estimator for General Linear Regression Model with AR(2) Errors: A Comparative Study with Monte Carlo Simulation

Journal of New Theory, 2022
The sensitivity of the least-squares estimation in a regression model is impacted by multicollinearity and autocorrelation problems. To deal with the multicollinearity, Ridge, Liu, and Ridge-type biased estimators have been presented in the statistical ...
Tuğba Söküt Açar
doaj   +1 more source

Liu Estimates and Influence Analysis in Regression Models with Stochastic Linear Restrictions and AR (1) Errors [PDF]

Journal of Sciences, Islamic Republic of Iran, 2019
In the linear regression models with AR (1) error structure when collinearity exists, stochastic linear restrictions or modifications of biased estimators (including Liu estimators) can be used to reduce the estimated variance of the regression ...
Hoda Mohammadi, Abdolrahman Rasekh
doaj   +1 more source