Liu, Cheng Ph.D., Purdue University, December 2013. Non-parametric Spatial Models. Major Professor: Hao Zhang. Covariance functions play a central role in spatial statistics. Parametric covariance functions have been used in most of the existing works on the analysis of spatial data. The primary reason for this is that the classes of parametric covariance functions guarantee that the fitted cov...

Recently, quantile regression (QR) models are often applied for longitudinal data analysis. When the distribution of responses seems to be skew and asymmetric due to outliers and heavy-tails, QR models may work suitably. In this paper, a semi-parametric quantile regression model is developed for analysing continuous longitudinal responses. The error term's distribution is assumed to be Asymmetr...

evapotranspiration is one of the most important components of the hydrological cycle which is directly influenced by atmospheric conditions. this study investigated annual and seasonal trends in reference evapotranspiration (et0) and its key influencing climatic variables during 1966-2005 at 10 stations in southern iran (with centrality of fars province). first, multivariate regression analysis...

Abstract Black-box model structures are dominated by large multivariate functions. Usually a generic basis function expansion is used, e.g. polynomial basis, and the parameters of tuned given data. This pragmatic often necessary step considering black-box nature problem. However, having identified suitable function, there no need to stick original basis. So-called decoupling techniques aim at t...

Abstract We study price optimization of perishable inventory over multiple, consecutive selling seasons in the presence demand uncertainty. Each season consists a finite number discrete time periods, and per period is Bernoulli distributed with price-dependent parameter. The set feasible prices finite, expected corresponding to each unknown seller, whose objective maximize cumulative revenue. p...