Results 61 to 70 of about 300,687 (184)

A group-based approach to the least squares regression for handling multicollinearity from strongly correlated variables

, 2019
Multicollinearity due to strongly correlated predictor variables is a long-standing problem in regression analysis. It leads to difficulties in parameter estimation, inference, variable selection and prediction for the least squares regression.
Tsao, Min
core  

A comparative study between LSSVM, LSTM, and ANN in predicting the unconfined compressive strength of virgin fine-grained soil

Frontiers in Built Environment
The present investigation introduces a robust soft computing model by comparing twelve least square support vector machine (LSSVM), six long short-term memory (LSTM), and thirty-six artificial neural network (ANN) models to predict the unconfined ...
Jitendra Khatti, Kamaldeep Singh Grover, Pijush Samui   +2 more
doaj   +1 more source

Do instructional attributes pose multicollinearity problems? An empirical exploration [PDF]

It is commonly perceived that variables ‘measuring’ different dimensions of teaching (construed as instructional attributes) used in student evaluation of teaching (SET) questionnaires are so highly correlated that they pose a serious multicollinearity ...
Hong Son Nghiem, Mohammad Alauddin
core  

Modeling Bangladesh's gross domestic product using regression approach [PDF]

, 2016
This study finds the factors that affect Bangladesh’s Gross Domestic Product (GDP) through regression approach. Stepwise and Ridge regression techniques have been applied to build the suitable regression model.
Das, K. R., Hasan, M. N., Malek, M. B., Rana, Md. Sohel, Sultana, N.   +4 more
core  

MELE: MAXIMUM ENTROPY LEUVEN ESTIMATORS [PDF]

Multicollinearity hampers empirical econometrics. The remedies proposed to date suffer from pitfalls of their own. The ridge estimator is not generally accepted as a vital alternative to the ordinary least-squares (OLS) estimator because it depends upon ...
Paris, Quirino
core   +1 more source

Using Linear Regression to Analyze Economics Content Mastery and Learner’s Autonomy Towards English Writing Competence [PDF]

, 2019
English is used widely in education area. It is also used in higher education. Many universities put English in the curriculum. In industrial revolution 4.0., English has an important role.
Ratnaningsih, Paskalina Widiastuti
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Average group effect of strongly correlated predictor variables is estimable

, 2018
It is well known that individual parameters of strongly correlated predictor variables in a linear model cannot be accurately estimated by the least squares regression due to multicollinearity generated by such variables.
Tsao, Min
core  

Effects of Asset Structure, Operating Cash Flow, and Profitability on Debt Policy in Property and Real Estate Companies on the Indonesia Stock Exchange Period 2013-2017 [PDF]

, 2018
This study aims to determine the effect of asset structure, operating cash flow, and profitability on debt policy in property and real estate companies in the Indonesia Stock Exchange in 2013-2017. The analytical method used is multiple linear regression,
Guci, S. T. (Siti), Hantono, H. (Hantono), Peranginangin, M. B. (Meilianta), Rahmi, N. U. (Namira), Saragih, C. M. (Cathrin)   +4 more
core  

Relationship Quality among Married Couples [PDF]

, 2016
Having a high quality relationship is a key part of a marriage. In this project, I performed an econometric analysis to determine what impacts a couple\u27s relationship quality.
Haack, Amber R
core   +2 more sources

Evaluating Estimator Performance Under Multicollinearity: A Trade-Off Between MSE and Accuracy in Logistic, Lasso, Elastic Net, and Ridge Regression with Varying Penalty Parameters

Stats
Multicollinearity in logistic regression models can result in inflated variances and yield unreliable estimates of parameters. Ridge regression, a regularized estimation technique, is frequently employed to address this issue.
H. M. Nayem, Sinha Aziz, B. M. Golam Kibria   +2 more
doaj   +1 more source