Zobrazeno 1 - 10
of 496
pro vyhledávání: '"liu estimator"'
Autor:
Md Ariful Hoque, B. M. Golam Kibria
Publikováno v:
Surveys in Mathematics and its Applications, Vol 18 (2023), Pp 183-221 (2023)
The ordinary least square estimator is inefficient when there exists multicollinearity among regressors in linear regression model. There are many methods available in literature to solve the multicollinearity problem. In this study, we consider some
Externí odkaz:
https://doaj.org/article/fe5665595ac245459b0087a0383801dc
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:
Mathematics, Vol 12, Iss 17, p 2787 (2024)
Outliers are a common problem in applied statistics, together with multicollinearity. In this paper, robust Liu estimators are introduced into a partially linear model to combat the presence of multicollinearity and outlier challenges when the error
Externí odkaz:
https://doaj.org/article/d656c332b2ec447caff19dc2c43cc9c4
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
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
Akademický článek
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Kibria–Lukman estimator for the Conway–Maxwell Poisson regression model: Simulation and applications
Publikováno v:
Scientific African, Vol 19, Iss , Pp e01553- (2023)
The Conway–Maxwell Poisson (COMP) regression model is one of the count data models to account for over– and under–dispersion. In regression analysis, when the explanatory variables are correlated, when there is multicollinearity problem, this i
Externí odkaz:
https://doaj.org/article/a1b0962848f04760a5f36a12113d7f03
Publikováno v:
Scientific African, Vol 19, Iss , Pp e01565- (2023)
The probit regression model (PRORM) aims to model a binary response with one or more explanatory variables. The parameter of the PRORM is estimated using an estimation method called the maximum likelihood (ML), like a logistic model. When multicollin
Externí odkaz:
https://doaj.org/article/34a70dd9e3494630ae4dc062fbce8553
Publikováno v:
Mathematics, Vol 11, Iss 22, p 4632 (2023)
Shrinkage estimators are often used to mitigate the consequences of multicollinearity in linear regression models. Despite the ease with which these techniques can be applied to small- or moderate-size datasets, they encounter significant challenges
Externí odkaz:
https://doaj.org/article/caec9f2778524dcb8c8dc1952c915c95