This study is about the development of a robust ridge regression estimator. It is based on weighted ridge MM-estimator (WRMM) and is believed to have potentials in remedying the problems of multicollinearity. The proposed method has been compared with several existing estimators, namely ordinary least squares (OLS), robust regression based on MM estimator, ridge regression (RIDGE), weighted rid...

Despite the fact that environmental variables often exhibit spatial correlation, this is not typically accounted in calibration models for remote sensed observations. Another feature in many remote sensing instruments is that the derived predictor variables are highly correlated. Both of these affect the prediction accuracy, especially when the training set for model calibration is small. We pr...

australian rainfall is related with numerous key climate predictors namely el-nino southern oscillation (enso), indian ocean dipole (iod) and southern annular mode (sam). some studies have tried to discover the effects of these climate predictors on rainfall variability of different parts of australia, particularly western australia, queensland and victoria. nonetheless, clear association betwe...

Multicollinearities among the coefficients obtained from the method of geographically weighted regression have been identified in recent research. This is a serious issue that poses a critical challenge for the utility of the method as a tool to investigate multivariate relationships. The evidence regarding the ability of GWR to retrieve spatially varying processes remains mixed due to partial ...

In dementia screening tests, item selection for shortening an existing screening test can be achieved using multiple logistic regression. However, maximum likelihood estimates for such logistic regression models often experience serious bias or even non-existence because of separation and multicollinearity problems resulting from a large number of highly correlated items. Firth (1993, Biometrik...

The method of partial least-squares regression (PLSR) can effectively deal with the problems of multicollinearity among independent variables, but can not ideally solve the complicated problems of nonlinearity between dependent variables and independent variables. The method of coupling model with back propagations artificial neural network (BP-ANN) and projection pursuit (PP) is an ideal tool ...

The demand for tourism in Indonesia continues to increase every year but cannot reach thepredetermined target. Studies on have been done a lot, especially Indonesia.The selection of the dependent variable is not problematic and acceptable,however, independent still unclear. This study aims provide anappropriate Indonesian model analyze determinants demandin Indonesia. estimation technique used ...