Zobrazeno 1 - 10
of 646
pro vyhledávání: '"ridge estimator"'
Autor:
AVAN Al-Saffar, Zakaria Y. Algamal
Publikováno v:
المجلة العراقية للعلوم الاحصائية, Vol 21, Iss 1, Pp 102-111 (2024)
It has been consistently proven that the ridge estimator is an effective shrinking strategy for reducing the effects of multicollinearity. An effective model to use when the response variable is positively skewed is the Gamma Regression Model (GRM).
Externí odkaz:
https://doaj.org/article/227a1f00f7a548658e5994ff22b9ee2b
Publikováno v:
Heliyon, Vol 10, Iss 16, Pp e35848- (2024)
Frailty model examines the effect of observable and non-observable factors on time to event data. Presence of collinearity produces unstable estimates of parameters. Therefore, this research focus on the penalized estimation of frailty model and prop
Externí odkaz:
https://doaj.org/article/b5d343ff71394e899201db649b7d400c
Autor:
Hasan Yildirim
Publikováno v:
IEEE Access, Vol 12, Pp 102355-102367 (2024)
The multicollinearity problem is a common phenomenon in data-driven studies, significantly affecting the performance of machine learning algorithms during the process of extracting information from data. Despite its widespread use across various fiel
Externí odkaz:
https://doaj.org/article/d4e1908fddfc4e69b8c2225f3c742243
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
The study proposed and compared the biased estimators for the Poisson-Inverse Gaussian regression model to deal with correlated regressors. The limitations of each biased estimator are also discussed. Additionally, some biasing parameters for the Ste
Externí odkaz:
https://doaj.org/article/d0bdd41576784683840e4ee6e607c3c8
Publikováno v:
Iraqi Journal for Computer Science and Mathematics, Vol 5, Iss 1 (2024)
When there is collinearity among the regressors in gamma regression models, we present a new two-parameter ridge estimator in this study. We look into the new estimator's mean squared error characteristics. Additionally, we offer several theorems to
Externí odkaz:
https://doaj.org/article/e2e647093ce8464ea0b1ffe23f8ebeb3
Publikováno v:
Alexandria Engineering Journal, Vol 70, Iss , Pp 231-245 (2023)
The Poisson Inverse Gaussian Regression model (PIGRM) is used for modeling the count datasets to deal with the issue of over-dispersion. Generally, the maximum likelihood estimator (MLE) is used to estimate the PIGRM estimates. In the PIGRM, when the
Externí odkaz:
https://doaj.org/article/931b518571964ffc93c2e14013ee69d8
A generalized Liu-type estimator for logistic partial linear regression model with multicollinearity
Autor:
Dayang Dai, Dabuxilatu Wang
Publikováno v:
AIMS Mathematics, Vol 8, Iss 5, Pp 11851-11874 (2023)
This paper is concerned with proposing a generalized Liu-type estimator (GLTE) to address the multicollinearity problem of explanatory variable of the linear part in the logistic partially linear regression model. Using the profile likelihood method,
Externí odkaz:
https://doaj.org/article/c682e9929691476f9e2cc3cc7d864b09
Publikováno v:
African Scientific Reports, Pp 212-228 (2022)
Despite its common usage in estimating the linear regression model parameters, the ordinary least squares estimator often suffers a breakdown when two or more predictor variables are strongly correlated. This study proposes an alternative estimator t
Externí odkaz:
https://doaj.org/article/3481ef5410e8409e9e7bbf26872d9d43
Autor:
Marwan Al-Momani, Mohammad Arashi
Publikováno v:
Mathematics, Vol 12, Iss 3, p 390 (2024)
Spatial regression models are widely available across several disciplines, such as functional magnetic resonance imaging analysis, econometrics, and house price analysis. In nature, sparsity occurs when a limited number of factors strongly impact ove
Externí odkaz:
https://doaj.org/article/580e643dfabd4f3292d80ce0cd3e20a7