Calibration and reverse calibration : R functions and ...
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Calibration and reverse calibration : R functions and ...
Jun 18, 2013 - found in [3]. # return a data.frame of the linear model of calibration and prediction interval. # for content sequence. # x. : values of the standards.
Calibration and reverse calibration : R functions and examples Aur´elien THOMEN, Laurent REMUSAT, Fran¸cois ROBERT 06/18/2013 This supplementary information file provides recipe to perform an univariate calibration with a linear model, to calculate the prediction (and confidence) interval of the dependent variables, to reverse the calibration and the interval for a new measurement, to calculate the critical limit and its associated value in x axis. The code is written in R programming language [1]. R is free and opensource, dedicated to data mining and statistics and multi-platform (Windows, Mac OS X, Linux). It was found to be the most suitable way to share the calibration methods used in this paper. The data are shown in the Table 1.
1
R function
This section provides the functions to perform the calculation. The linear regression, prediction and confidence interval and linear model and interval inversion formula can be found in the book of [2, 3] the critical limit calculation can be found in [3]. # return a data.frame of the linear model of calibration and prediction interval # for content sequence # x : values of the standards # y : values of the measurements of the standards # content : unique values of the standards , # by default content = seq ( range ( x ) , len = length ( x )) # alpha : interval with a (1 - alpha )100 level ; # by default alpha = 0 .05 for 95 % confidance level # m : m = 1 by default to produce prediction interval # with a (1 - alpha )100 level # m = Inf to produce confidence interval interv
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