Articles | Volume 19, issue 19
Atmos. Chem. Phys., 19, 12531–12543, 2019
https://doi.org/10.5194/acp-19-12531-2019
Atmos. Chem. Phys., 19, 12531–12543, 2019
https://doi.org/10.5194/acp-19-12531-2019

Technical note 09 Oct 2019

Technical note | 09 Oct 2019

Technical note: Effects of uncertainties and number of data points on line fitting – a case study on new particle formation

Santtu Mikkonen et al.

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Cited articles

Boggs, P. T., Byrd, R. H., and Schnabel, R. B.: A Stable and Efficient Algorithm for Nonlinear Orthogonal Distance Regression, SIAM J. Sci. Stat. Comput., 8, 1052–1078, https://doi.org/10.1137/0908085, 1987. 
Boggs, P. T., Donaldson, J. R., Byrd, R. H., and Schnabel, R. B.: Algorithm 676 ODRPACK: software for weighted orthogonal distance regression, ACM Trans. Math. Softw., 15, 348–364, https://doi.org/10.1145/76909.76913, 1989. 
Boy, M., Karl, T., Turnipseed, A., Mauldin, R. L., Kosciuch, E., Greenberg, J., Rathbone, J., Smith, J., Held, A., Barsanti, K., Wehner, B., Bauer, S., Wiedensohler, A., Bonn, B., Kulmala, M., and Guenther, A.: New particle formation in the Front Range of the Colorado Rocky Mountains, Atmos. Chem. Phys., 8, 1577–1590, https://doi.org/10.5194/acp-8-1577-2008, 2008. 
Cantrell, C. A.: Technical Note: Review of methods for linear least-squares fitting of data and application to atmospheric chemistry problems, Atmos. Chem. Phys., 8, 5477–5487, https://doi.org/10.5194/acp-8-5477-2008, 2008. 
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Atmospheric measurement data never come without measurement error. Too often, these errors are neglected when researchers make inferences from their data. We applied multiple line-fitting methods to simulated data mimicking two central variables in aerosol research. Our results show that an ordinary least squares fit, typically used to describe relationships, underestimates the slope of the fit and that methods taking the measurement uncertainty into account performed significantly better.
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