nonlinear regression

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nonlinear regression

[′nän‚lin·ē·ər ri′gresh·ən]
(statistics)
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KEY WORDS: Hyperthyroidism, Pulmonary hypertension, Linear and Non-linear Regression.
First, non-linear regression seems more difficult because it requires an iterative procedure to minimize an objective function.
Historical unpublished data comprising of average monthly weights up to yearling age on Thalli lambs (n=130) from January 2009 to December 2009 were evaluated statistically with the aim of identifying the growth of Thalli sheep using non-linear regression models to discover growth-development mechanism of the Thalli sheep.
For the present system, non-linear regression was carried out for all of the five kinetic models and seven adsorption isotherms by directly fitting the experimental [Q.
The information obtained by the equipment was analyzed through Non-linear Regression Method of Logsdon and Jaynes [5].
To achieve the above-stated research objective regarding a possible curvilinearity of relationships, the relationships between the four ACAP dimensions and performance measures are analyzed by means of both linear and non-linear regressions.
The characteristic curve-fitting coefficients can be determined with non-linear regression analysis.
2001, Determination of kinetic parameters by direct non-linear regression from TG curves, Thermochimica Acta, 372, No.
For the first approach, the relationships between surface soil organic carbon concentrations and the pixel intensity values for each band were developed by non-linear regression analysis.
In other words, the decision, for example, to run a linear rather than non-linear regression affects the outcome in much the same way as the choice of a particular prior distribution for the regression coefficient.
Non-linear regression was performed using S-PLUS (S-PLUS2000 1999).

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