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Displaying similar documents to “Detecting atypical data in air pollution studies by using shorth intervals for regression”

Comparison of clinical data based on limits of agreement

Luís M. Grilo, Helena L. Grilo (2012)

Biometrical Letters

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Two different medical measurement methods, which usually do not produce exactly the same results, are used to analyse the serum levels of folic acid in a blood sample. We assess the (dis)agreement of the available data in order to replace the old method (the reference method, which involves a lot of human intervention) with the new one (which uses mostly machines), without causing problems in clinical interpretation. The 95% limits of agreement are estimated, before and after a logarithmic...

Detecting atypical data in air pollution studies by using shorth intervals for regression

Cécile Durot, Karelle Thiébot (2010)

ESAIM: Probability and Statistics

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To validate pollution data, subject-matter experts in Airpl (an organization that maintains a network of air pollution monitoring stations in western France) daily perform visual examinations of the data and check their consistency. In this paper, we describe these visual examinations and propose a formalization for this problem. The examinations consist in comparisons of so-called shorth intervals so we build a statistical test that compares such intervals in a nonparametric regression...

Quantile plots in the analysis of heteroscedastic models.

Montserrat Pepió Viñals, Carlos Polo Miranda (1992)

Qüestiió

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Recent developments in quality engineering methods have led to considerable interest in the analysis of variance, buiding a dispersion model, identifying important effects from replicated experiments and checking for significance by means of a half-normal plot. A methodology based on a chi-squared quantile plot is presented here for checking first the presence of heteroscedasticity, outliers and other data peculiarities, and after the estimation stage a new stepwise procedure tests for...