Publication

Determination of partition coefficients of labile compounds subject to dissociation extraction: Analysis of partitioning

Albert Renken
1993
Journal Articles

Abstract

A novel method for the detn. of partition coeffs. in aq.-org. two-phase systems is described. It is applicable for characterizing the distribution of substances undergoing proton dissocn. in the aq. phase. The method is based on titrn. by means of the org. phase. A linear form of the resp. model is given for parameter estn. by linear regression. This strategy is used for the detn. of the partition coeffs. of some N-unprotected n-alkyl esters of phenylalanine in various aq.-org. biphasic systems. These esters are of interest for the optical resoln. of phenylalanine with chymotrypsin. [on SciFinder (R)]

Official source

https://infoscience.epfl.ch/entities/publication/52cc6a30-86f5-4547-9bb9-d2f067effe3a

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Albert Renken
1993
Journal Articles

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/52cc6a30-86f5-4547-9bb9-d2f067effe3a

About this result

Related concepts (30)

Linear regression

In statistics, linear regression is a linear approach for modelling the relationship between a scalar response and one or more explanatory variables (also known as dependent and independent variables). The case of one explanatory variable is called simple linear regression; for more than one, the process is called multiple linear regression. This term is distinct from multivariate linear regression, where multiple correlated dependent variables are predicted, rather than a single scalar variable.

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In statistics, nonlinear regression is a form of regression analysis in which observational data are modeled by a function which is a nonlinear combination of the model parameters and depends on one or more independent variables. The data are fitted by a method of successive approximations. In nonlinear regression, a statistical model of the form, relates a vector of independent variables, , and its associated observed dependent variables, . The function is nonlinear in the components of the vector of parameters , but otherwise arbitrary.

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In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships between a dependent variable (often called the 'outcome' or 'response' variable, or a 'label' in machine learning parlance) and one or more independent variables (often called 'predictors', 'covariates', 'explanatory variables' or 'features'). The most common form of regression analysis is linear regression, in which one finds the line (or a more complex linear combination) that most closely fits the data according to a specific mathematical criterion.

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Determination of partition coefficients of labile compounds subject to dissociation extraction: Analysis of partitioning

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