Short-term forecasting of wind generation requires a model of the function for the conversion of meteorological variables (mainly wind speed) to power production. Such a power curve is nonlinear and bounded, in addition to being nonstationary. Local linear regression is an appealing nonparametric approach for power curve estimation, for which the model coefficients can be tracked with recursive...

The Support Vector Regression (SVR) is applied on a key problem in financial economics: interest rate curve estimation. The SVR is able to introduce two important types of a priori information into the estimation. First, the kernel and the parameter C can jointly assure an implicit quality requirement on the estimated curve. It is presented a proposition that reduces the search space for the op...

For the peak picking of tempo candidates, applying kmeans clustering on tempo curve is straightforward and leading to good result. But the tempo candidates obtained from tempo curve are limited and lose a lot of information for possible tempi. The study proposes the local maximum peak picking method to increase the number and information of possible tempo candidates. Therefore, the accuracy of ...

Bootstrap methods in curve estimation have been introduced for smoothing parameter selection and for construction of conndence intervals. Most of the papers on conndence intervals use explicit bias estimation or the technique of \undersmoothing" to deal with bias. Coverage accuracy has only been considered for curve estimates with constant variance function. In this paper we show that explicit ...

The purpose of this work is to compare the linear and non-linear kriging methods in the mineral resource estimation of the Qolqoleh gold deposit in Saqqez, NW Iran. Considering the fact that the gold distribution is positively skewed and has a significant difference with a normal curve, a geostatistical estimation is complicated in these cases. Linear kriging, as a resource estimation method, c...

Many studies reported that the hematocrit (HCT) is the most highly influencing factor affecting the accuracy of the glucose measurements by portable/handheld devices. It is also known as an important factor for clinical decision-making situations. Therefore, estimation of HCT plays a crucial role for enhancing accuracy of glucose measurements and performance of therapy. In this paper, we presen...