Algorithmic trading is a common topic researched in the neural network due to abundance of data available. It phenomenon where an approximately linear relationship exists between two or more independent variables. especially prevalent financial interrelated nature data. The existing feature selection methods are not efficient enough solving such problem potential loss essential and relevant inf...

13 In this paper, a user-defined inter-band correlation filter function was used to resample 14 hyperspectral data and thereby mitigate the problem of multicollinearity in classification 15 analysis. The proposed resampling technique convolves the spectral dependence information 16 between a chosen band-centre and its shorter and longer wavelength neighbours. Weighting 17 threshold of inter-ban...

Assessment of discriminant validity is a must in any research that involves latent variables for the prevention of multicollinearity issues. Fornell and Larcker criterion is the most widely used method for this purpose. However, a new method has emerged for establishing the discriminant validity assessment through heterotrait-monotrait (HTMT) ratio of correlations method. Therefore, this articl...

STUDY OBJECTIVE This study examined whether high levels of racial segregation are associated with high county level intentional injury rates. DESIGN Multiple linear regression was used to assess the association between county racial segregation (measured by the Gini coefficient) and intentional injury rates. Multicollinearity was assessed with Eigenvalues and condition indices. SETTING Stat...

Regularization regression techniques are widely used to overcome a model’s parameter estimation problem in the presence of multicollinearity. Several biased available literature, including ridge, Least Angle Shrinkage Selection Operator (LASSO), and elastic net. In this work, we study performance classical LASSO, adaptive ordinary least squares (OLS) methods high-multicollinearity scenarios pro...

The development of corporate Sukuk, which is relatively small compared to the state background this research. This study aims determine whether there an effect bi-7 day reverse repo rate, gross domestic product, and industrial production index on growth Sukuk with inflation as moderating variable in 2011-2021. research a quantitative sample 44 data Indonesia for 2011-2021 period, results are pu...

The main problem when dealing with fuzzy data variables is that it cannot be formed by a model represents the through method of Fuzzy Least Squares Estimator (FLSE) which gives false estimates invalidity in case existence multicollinearity. To overcome this problem, Bridge Regression (FBRE) Method was relied upon to estimate linear regression triangular numbers. Moreover, detection multicolline...