Results 1 to 10 of about 3,187,155 (299)

Estimating influenza incidence using search query deceptiveness and generalized ridge regression. [PDF]

PLoS Comput Biol, 2019
Seasonal influenza is a sometimes surprisingly impactful disease, causing thousands of deaths per year along with much additional morbidity. Timely knowledge of the outbreak state is valuable for managing an effective response.
Priedhorsky R, Daughton AR, Barnard M, O'Connell F, Osthus D.   +4 more
europepmc   +2 more sources

PENERAPAN METODE GENERALIZED RIDGE REGRESSION DALAM MENGATASI MASALAH MULTIKOLINEARITAS [PDF]

E-Jurnal Matematika, 2013
Ordinary least square is parameter estimation method for linier regression analysis by minimizing residual sum of square. In the presence of multicollinearity, estimators which are unbiased and have a minimum variance can not be generated ...
NI KETUT TRI UTAMI, I KOMANG GDE SUKARSA
doaj   +4 more sources

Multilocus association mapping using generalized ridge logistic regression [PDF]

BMC Bioinformatics, 2011
Background In genome-wide association studies, it is widely accepted that multilocus methods are more powerful than testing single-nucleotide polymorphisms (SNPs) one at a time.
Ott Jurg, Shen Yuanyuan, Liu Zhe
doaj   +4 more sources

A bias-reduced estimator for generalized Poisson regression with application to carbon dioxide emission in Canada. [PDF]

Sci Rep
The generalized Poisson regression model (GPRM) provides a flexible framework for modeling count data, especially those exhibiting over- or underdispersion.
Alghamdi FM, Gemeay AM, Abd-Elmougod GA, Almetwally EM, El-Qurashi MA, Mekiso GT, Hammad AT.   +6 more
europepmc   +2 more sources

Treating Multicollinearity Problem Using Gool Programming Technique [PDF]

The Egyptian Statistical Journal, 2011
Multiple regression analysis is usually efficient for prediction, but often produces poor results because of the multicollinearity among the independent variables.
Afaf El-Dash, Aly El-Hefnawy, Rasha Farghali   +2 more
doaj   +1 more source

Ridge Regression and the Elastic Net: How Do They Do as Finders of True Regressors and Their Coefficients?

Mathematics, 2022
For the linear model Y=Xb+error, where the number of regressors (p) exceeds the number of observations (n), the Elastic Net (EN) was proposed, in 2005, to estimate b.
Rajaram Gana
doaj   +1 more source

Ridge regression and its applications in genetic studies.

PLoS ONE, 2021
With the advancement of technology, analysis of large-scale data of gene expression is feasible and has become very popular in the era of machine learning. This paper develops an improved ridge approach for the genome regression modeling.
M Arashi, M Roozbeh, N A Hamzah, M Gasparini   +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

Generalized ridge estimators adapted in structural equation models

Acta Scientiarum: Technology, 2020
Multicollinearity is detected via regression models, where independent variables are strongly correlated. Since they entail linear relations between observed or latent variables, the structural equation models (SEM) are subject to the multicollinearity ...
Gislene Araujo Pereira, Mariana Resende, Marcelo í‚ngelo Cirillo   +2 more
doaj   +1 more source

KINERJA JACKKNIFE RIDGE REGRESSION DALAM MENGATASI MULTIKOLINEARITAS

E-Jurnal Matematika, 2014
Ordinary least square is a parameter estimations for minimizing residual sum of squares. If the multicollinearity was found in the data, unbias estimator with minimum variance could not be reached.
HANY DEVITA, I KOMANG GDE SUKARSA, I PUTU EKA N. KENCANA   +2 more
doaj   +1 more source