Background: Urmia Lake, the second largest hyper-saline lake of the world, has experienced lack of water and other environmental issues in recent years. Now, there is a danger of the lake drying out, which will affect the region and its inhabitants. This study aimed to present a model which can relate the water level of the lake to effective factors. Methods: Parameters that influence water le...

Local polynomial regression is a useful non-parametric regression tool to explore fine data structures and has been widely used in practice. We propose a new non-parametric regression technique called local composite quantile regression smoothing to improve local polynomial regression further. Sampling properties of the estimation procedure proposed are studied. We derive the asymptotic bias, v...

This paper aims at studying the interaction between the extraction of interscheme properties, such as synonymies, homonymies and type conflicts (which are exploited for dejining the semantics of involved schemes for integration purposes), and the resolution of type conjlicts. As a matter of facts, the transformations required by type conflict resolution could invalidate some of the detected int...

so far several methods have been developed for mapping and interpolation of isohyets.one of the recently accepted methods is geographically weighting regression which is suitable for evaluation of spatial heterogeneity of dependent variable by using local regressions. in order to evaluate annually precipitation spatial variation, this study was conducted in gilan province which precipitation is...

Abstract Many researchers have shown interest in profile monitoring; however, most of the applications this field research are developed under assumption normal response variable. Little attention has been given to monitoring with non-normal variables, known as general linear models which consists two main categories (i.e., logistic and Poisson profiles). This paper aims monitor problem Phase I...

Polynomial kernel regression is one of the standard and state-of-the-art learning strategies. However, as is well known, the choices of the degree of polynomial kernel and the regularization parameter are still open in the realm of model selection. The first aim of this paper is to develop a strategy to select these parameters. On one hand, based on the worst-case learning rate analysis, we sho...

Nonparametric regression estimates a conditional expectation of a response given a predictor variable without requiring parametric assumptions about this conditional expectation. There are many methods of nonparametric regression including kernel estimation, smoothing splines, regression splines, and orthogonal series. Local regression ts parametric models locally by using kernel weights. Local...

Cameras record three colour responses (RGB) which are device dependent. Camera coordinates are mapped to a standard colour space such as XYZ useful for colour measurement by a mapping function e.g. the simple 3 × 3 linear transform (usually derived through regression). This mapping, which we will refer to as LCC (linear colour correction), has been demonstrated to work well in the number of stu...

We consider a nonlinear polynomial regression model in which we wish to test the null hypothesis of structural stability in the regression parameters against the alternative of a break at an unknown time. We derive the extreme value distribution of a maximum–type test statistic which is asymptotically equivalent to the maximally selected likelihood ratio. AMS 2000 Subject Classification: Primar...