Runoff potentiality of a watershed was assessed based on identifying curve number (CN), soil conservation service (SCS), and functional data analysis (FDA) techniques. Daily discrete rainfall data were collected from weather stations in the study area and analyzed through lowess method for smoothing curve. As runoff data represents a periodic pattern in each watershed, Fourier series was introd...

COX-2 inhibitory activities of some 1,4-dihydropyridine and 5-oxo-1,4,5,6,7,8-hexahydroquinoline derivatives were modeled by quantitative structure–activity relationship (QSAR) using stepwise-multiple linear regression (SW-MLR) method. The built model was robust and predictive with correlation coefficient (R2) of 0.972 and 0.531 for training and test groups, respectively. The quality of the mod...

In analyzing data from a survey, researchers often need to compare the effectiveness of several logistic regression models. The receiver operating characteristic curve offers one way to measure effectiveness of prediction, by calculating the area under the curve (AUC). We present a SAS macro for calculating AUC that takes the survey weights into account. For comparing logistic regression models...

An introduction to robustness in statistics, with emphasis on its relevance to regression analysis. The weaknesses of the least squares estimator are highlighted, and the idea of error in data re ned. Properties such as breakdown, e ciency and equivariance are discussed and, through consideration of M, S and MM-estimators in relation to these properties, the progressive nature of robust estimat...

1. Introduction One of the most important statistical tools is a linear regression analysis for many fields. Nearly all regression analysis relies on the method of least squares for estimation of the parameters in the model. A problem that we often encountered in the application of regression is the presence of an outlier or outliers in the data. Outliers can be generated by from a simple opera...

ignoring two main characteristics of the concentration-response data, correlation between observations and presence of outliers, may lead to misleading results. therefore the special method should be considered. in this paper in to examine the effect of phenylephrine in rat corpus cavernosum, outlier robust nonlinear mixed estimation is used. in this study, eight different doses of phenylephrin...

COX-2 inhibitory activities of some 1,4-dihydropyridine and 5-oxo-1,4,5,6,7,8-hexahydroquinoline derivatives were modeled by quantitative structure–activity relationship (QSAR) using stepwise-multiple linear regression (SW-MLR) method. The built model was robust and predictive with correlation coefficient (R2) of 0.972 and 0.531 for training and test groups, respectively. The quality of the mod...

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...

Abstract Zaman and Bulut (2018a) developed a class of estimators for population mean utilising LMS robust regression supplementary attributes. In this paper, family is proposed, based on the adaptation presented by (2019), followed introduction new regression-type tools (LAD, H-M, LMS, H-MM, Hampel-M, Tukey-M, LTS) The square error expressions adapted proposed families are determined through ge...

The analysis of data assuming values in the real open interval (0;1) is a common issue in quantitative research when the effect of selected variables on the conditional expectation of a percentage or rate is considered. In the literature, various alternative methods to model ratios and percentage data have been proposed (see e.g. Papke and Wooldridge, 1996 and Kieschnick and McCullough, 2003). ...