Communications in Statistics Simulation and Computation Publication details, including instructions for authors and subscription information: http://www.informaworld.com/smpp/title~content=t713597237 Tolerance Factors in Multiple and Multivariate Linear Regressions K. Krishnamoorthy a; Sumona Mondal b a Department of Mathematics, University of Louisiana at Lafayette, Lafayette, Louisiana, USA b...

A quantitative structure-property relationship (QSPR) study based on multiple linear regression (MLR) and artificial neural network (ANN) techniques is carried out to investigate the retention time behavior of some pesticides on the DB-5ms fused-silica column in gas chromatography. Five descriptors selected in the MLR model are: first component WHIM index (E1v), highest eigenvalue n.7 of burden...

Quantitative structure-retention relationships (QSRRs) are used to correlate paper chromatographic retention factors of disperse dyes with theoretical molecular descriptors. A data set of 23 compounds with known RF values was used. The genetic algorithm-multiple linear regression analysis (GA-MLR) with three selected theoretical descriptors was obtained. The stability and predictability of the ...

it is important to determine whether a candidate molecule is capable of penetrating the plasma-brain barrier indrug discovery and development. the aim of this paper is to establish a predictive model for plasma-brainbarrier penetration using simple descriptors the usefulness of the quantum chemical descriptors, calculated atthe level of the dft and he theories using 6-310* basis set for qsar st...

We consider the problem of predicting total Indian summer monsoon rainfall (ISMR). A popular approach in prior literature [1], [2] has been to fit a regression model with the precipitation as predictand and various climatological indices and parameters as predictors. The predictor climatological indices and parameters are detected through an analysis of their linear correlations with the Indian...

abstract spatial prediction of soil organic carbon is a crucial proxy to manage and conserve natural resources, monitoring co2 and preventing soil erosion strategies within the landscape, regional, and global scale. the objectives of this study was to evaluate capability of artificial neural network and multivariate linear regression models in order to predict soil organic carbon using terrain ...

This paper presents a new method. It is a combination of two algorithms that have never been presented before. The research proposes the combination of the Hodrick-Prescott (HP) filters with Multiple linear regression method (MLR). The case study is the electricity demand of Thailand. The first stage, we separate the signal from the original demand signal to a trend and detail components. After...