Noisy data are often fitted using a smoothing parameter, controling the importance of two objectives that are opposite to a certain extent. One of these two is smoothness and the other is closeness to the input data. The optimal value of this paramater minimizes the error of the result (as compared to the unknown, exact data), usually expressed in the L2 norm. This optimum cannot be found exact...

estimation of the conceptual costs in construction projects can be regarded as an important issue in feasibility studies. this estimation has a major impact on the success of construction projects. indeed, this estimation supports the required information that can be employed in cost management and budgeting of these projects. the purpose of this paper is to introduce an intelligent model to im...

This article considers spline smoothing of variance functions. We focus on selection of smoothing parameters and develop three direct data-driven methods: unbiased risk (UBR), generalized approximate cross validation (GACV) and generalized maximum likelihood (GML). In addition to guaranteed convergence, simulations show that these direct methods perform better than existing indirect UBR, genera...

several characterizations of marshall-olkin generalized distributions, introduced by gui (2013) and by al-saiari et al. (2014) are presented. these characterizations are based on: (i) a simple relationship between two truncated moments ; (ii) the hazard function.

Longitudinal data modeling is widely carried out using parametric methods. However, when the model misspecified, obtained estimator might be severely biased and lead to erroneous conclusions. In this study, we propose a new estimation method for longitudinal mixed in nonparametric regression. The objective of study was estimate regression curve two combined estimators: truncated spline local li...