2015
DOI: 10.1107/s2053273314027363
|View full text |Cite
|
Sign up to set email alerts
|

Statistical tests against systematic errors in data sets based on the equality of residual means and variances from control samples: theory and applications

Abstract: Statistical tests are applied for the detection of systematic errors in data sets from least-squares refinements or other residual-based reconstruction processes. Samples of the residuals of the data are tested against the hypothesis that they belong to the same distribution. For this it is necessary that they show the same mean values and variances within the limits given by statistical fluctuations. When the samples differ significantly from each other, they are not from the same distribution within the limi… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
4
0

Year Published

2017
2017
2022
2022

Publication Types

Select...
7
1

Relationship

0
8

Authors

Journals

citations
Cited by 10 publications
(4 citation statements)
references
References 23 publications
0
4
0
Order By: Relevance
“…The residual density features on the map indicate noise in the experimental data and also hint toward modeling shortcomings, suggesting the need for further improvements to the model. The parabolic shape of the fractal distribution indicates the presence of Gaussian noise in the residual density and provides a benchmark for improving the model to be refined further when fractal distribution deviates from this characteristic shape possibly due to various systematic errors [14].…”
Section: R L (R) =mentioning
confidence: 99%
“…The residual density features on the map indicate noise in the experimental data and also hint toward modeling shortcomings, suggesting the need for further improvements to the model. The parabolic shape of the fractal distribution indicates the presence of Gaussian noise in the residual density and provides a benchmark for improving the model to be refined further when fractal distribution deviates from this characteristic shape possibly due to various systematic errors [14].…”
Section: R L (R) =mentioning
confidence: 99%
“…We will conduct additional studies of the indicator of self-sufficiency in order to identify the relationship between the data presented in Table 2. For this, we will be using the statistical control methods, namely, the scatter chart proposed by A. Cohen, T. Tiplica, A. Kobi, J. Henn, K. Meindl (Cohen et al, 2016;Henn et al, Meindl, 2015). Correlation study indicators "production" and "import" are presented in Figure 1.…”
Section: Resultsmentioning
confidence: 99%
“…The measurements are corrected for multiple scattering, thermal diffuse scattering, absorption and extinction, and the electron density of a crystal is reconstructed by means of the fit of the analytical multipole model to the obtained Bragg structure factors. Due to the model deficiencies (Koritsanszky, Volkov Chodkiewicz, 2012), limited resolution and incomplete thermal deconvolution (Madsen, 2012;Henn & Meindl, 2015), reconstructed electron density is distorted by the random and model errors, which are maximal in the vicinity of the nuclei. Therefore, these regions should be excluded from consideration.…”
Section: Resultsmentioning
confidence: 99%