variances are utilized. To these ends, SIMEX and modified estimating equations (MEE) rather than likelihood methods are … depends on the true value of the parameter. Furthermore, the performances of SIMEX and MEE are associated with the true value … those from SIMEX. It was also found that the MEE estimators contain singularities which attribute to its low precision and …

kernel regression context, we derive the limit distribution of the SIMEX estimate. With the regression spline technique, two … different methods of estimations are used. The first method is the SIMEX algorithm which attempts to estimate the bias, and …

under these specific contexts. Then we borrow the idea of simulation-extrapolation (SIMEX), or remeasurement method …

kernel regression context, we derive the limit distribution of the SIMEX estimate. With the regression spline technique, two … different methods of estimations are used. The first method is the SIMEX algorithm which attempts to estimate the bias, and …

vectors. The proposed SVM training is implemented and tested on two problems: (i) gender classification of facial images using … standard SVM training, the proposed approach leads to much faster SVM training, produces a more compact classifier while …

Vector Machines (SVM) for financial data. The financial series are fitted into a family of Asymmetric Power ARCH (APARCH … inefficient when the data distribution shows departure from normality, so the current paper utilizes the nonparametric-based SVM … method and shows that it is more efficient than the QML under the skewed Student's t-distributed error. As the SVM is a …