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324  Articles
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The aim of this study is to investigate the effectiveness of biased estimation methods, principal component regression (PC) and ridge regression (RR) methods, according to unbiased the least squares (LS) method, against the multiple linearity problem (mul... see more

The aim of this study was to compare estimation methods: least squares method (LS), ridge regression (RR), Principal component regression (PCR) to estimate the parameters of multiple regression model in situations when the underlying assumptions of least ... see more

A new estimator for the Poisson model is introduced in this study. Poisson regression model is an important log- Linear models which is the tool of modeling the dependent variable when its values are positive and as a form of count data or rates additiona... see more

Multicollinearity is a relationship or correlation between predictor variables. Multicollinearity can also occur in longitudinal data, which is a combination of cross-section data and time-series data. The impact of multicollinearity causes the influence ... see more

Forage cactus is widely cultivated in environments with low rainfall, due to its adaptability to the climate and richness in water and carbohydrates for ruminants. Knowing the morphology of these plants and their responses to management practices through ... see more

The demand for tourism in Indonesia continues to increase every year but cannot reach thepredetermined target. Studies on tourism demand have been done a lot, especially in Indonesia.The selection of the dependent variable in tourism demand is not problem... see more

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 ef... see more

This study is dedicated to solving multicollinearity problem for the general linear model by using Ridge regression method. The basic formulation of this method and suggested forms for Ridge parameter is applied to the Gross Domestic Product data in Iraq.... see more

The aim of this study is to compare the least squares (LS) method that lost its function in the case of multicollinearity in regression methods with Ridge Regression (RR) and Principal Components Regression (PCR) which are bias estimators. For this aim, t... see more

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