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Data Mining Application of Non-Linear Mixed Modeling in Water Quality Analysis

Category: Data Management

Overview In regression analysis, non-linearity in fixed and random effects can adversely affect efficiency of regression parameter estimates. Successful non-linear time series modeling would improve regression parameter estimates and produce a richer notion of water quality than linear time series models allow. In addition multiple independent variables make each point in space a finite dimensional vector, non-linear in two dimensions jointly. The SAS/STAT procedure, NLMIXED fits non-linearity successfully in any time series using maximum likelihood-based methods.

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Publisher
SAS Institute
File Format
PDF
Date Published
Sep 19, 2008
Format
White Papers
Topics
Knowledge and Data Management, Data Mining - Analysis

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