Dohnal, Ludek and Faigl, Paul (2006) Classical or 'robust' linear regression? [Klasická nebo robustní lineární regrese?]. In: 9th Yearly Seminar on Securing Quality of Analytical Results, 27-29 Mar 2006, Komorni Lhotka, Czech Republic.
Mathematical processing of the data in Classical Linear Regression Analysis (Least Squares Method) is compared with more 'robust' linear approaches, e.g. the Standardized Principal Components Method and the Regression Method according to Passing & Bablok (Passing-Bablok Regression, 1983). By 'robust approaches' we understand such computational methods, where there is not possible (or advantageous) to make a distinction between 'independent' and 'dependent' variables. These are fundamentally indistinguishable as a choice and their uncertainties are of a similar order of magnitude. Typically, such is the case of comparison of the data of e.g. two analytical (instrumental) procedures in chemistry. The use of the often applied Least Square Method (LSM) is in such instance inappropriate. In the LSM it is implicitly assumed that the variables have inherently different uncertainty and therefore are not mutually exchangeable. A comparison between the 3 approaches is presented in a graphical form and open for further discussion.
|Item Type:||Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)|
|Uncontrolled Keywords:||regression analysis, least square method, analytical chemistry, biochemistry, method comparison|
|Subjects:||250000 Chemical Sciences > 250400 Analytical Chemistry > 250499 Analytical Chemistry not elsewhere classified
250000 Chemical Sciences > 250400 Analytical Chemistry > 250408 Chemometrics
250000 Chemical Sciences > 250400 Analytical Chemistry > 250409 Quality Assurance, Traceability and Metrological Chemistry
|Depositing User:||Dr Pavel Faigl|
|Date Deposited:||11 Oct 2007 01:20|
|Last Modified:||02 Jul 2013 22:49|
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