scholarly journals Corrigendum to “Statistical Analysis of Influence of Cover Depth on Loess Tunnel Deformation in NW China”

2021 ◽  
Vol 2021 ◽  
pp. 1-1
Author(s):  
Zhao Hu ◽  
Ke Du ◽  
Jinxing Lai ◽  
Yongli Xie
Keyword(s):  
Statistical Analysis ◽  
Nw China ◽  
Cover Depth

Multivariate statistical analysis of heavy metals in street dust of Baoji, NW China

2010 ◽  
Vol 173 (1-3) ◽  
pp. 744-749 ◽  
Author(s):  
Xinwei Lu ◽  
Lijun Wang ◽  
Loretta Y. Li ◽  
Kai Lei ◽  
Li Huang ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Statistical Analysis ◽  
Multivariate Statistical Analysis ◽  
Street Dust ◽  
Multivariate Statistical ◽  
Nw China

scholarly journals Statistical Analysis of Influence of Cover Depth on Loess Tunnel Deformation in NW China

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Zhao Hu ◽  
Ke Du ◽  
Jinxing Lai ◽  
Yongli Xie
Keyword(s):  
Statistical Analysis ◽  
Surrounding Rock ◽  
Structural System ◽  
Cover Depth ◽  
Shallow Tunnels ◽  
The Difference ◽  
The Stability ◽  
Different Characteristics ◽  
Vertical Deformations ◽  
Special Soil

Loess is a kind of special soil with structure and hydrocollapse behavior; due to the particularity of loess, the deformation regularity of the tunnel in loess shows different characteristics from those in rock. To ensure the safety of construction, crown settlement (CS) and horizontal convergence (HC) are widely used to assess the stability of the tunnel structural system. Based on statistical analysis, this study focused on analyzing the influence of cover depth on the deformation of surrounding rock of loess tunnels by ANOVA, and relationships between them were presented by regression analysis. The achieved results indicated that the influence of cover depth on deformation was not obvious in shallow tunnels, while the cover depth had a significant effect on deformation in deep tunnels. Based on the difference of influence of cover depth on deformation between shallow tunnels and deep tunnels, a method for determining the cover depth threshold (CDT) in the tunnel by statistical analysis was proposed. The horizontal and vertical deformations in shallow tunnels were discrete and obeyed the positive distribution, mainly concentrated within 200 mm. The deformation allowance in shallow tunnels was recommended to be 200 mm. In deep tunnels, as the cover depth increased, the deformation increased linearly, while the CS/HC decreased.

Statistical analysis of classification

1966 ◽  
Vol 24 ◽  
pp. 188-189
Author(s):  
T. J. Deeming
Keyword(s):  
Multivariate Analysis ◽  
Statistical Analysis ◽  
Classification Scheme ◽  
Analytical Procedure ◽  
Narrow Band ◽  
Scientific Research ◽  
Maximum Amount ◽  
Amount Of Information

If we make a set of measurements, such as narrow-band or multicolour photo-electric measurements, which are designed to improve a scheme of classification, and in particular if they are designed to extend the number of dimensions of classification, i.e. the number of classification parameters, then some important problems of analytical procedure arise. First, it is important not to reproduce the errors of the classification scheme which we are trying to improve. Second, when trying to extend the number of dimensions of classification we have little or nothing with which to test the validity of the new parameters.Problems similar to these have occurred in other areas of scientific research (notably psychology and education) and the branch of Statistics called Multivariate Analysis has been developed to deal with them. The techniques of this subject are largely unknown to astronomers, but, if carefully applied, they should at the very least ensure that the astronomer gets the maximum amount of information out of his data and does not waste his time looking for information which is not there. More optimistically, these techniques are potentially capable of indicating the number of classification parameters necessary and giving specific formulas for computing them, as well as pinpointing those particular measurements which are most crucial for determining the classification parameters.

Quantitative parallel EELS spectrum imaging developed as a new tool in AEM

1992 ◽  
Vol 50 (2) ◽  
pp. 1202-1203
Author(s):  
Gianluigi Botton ◽  
Gilles L'espérance
Keyword(s):  
Statistical Analysis ◽  
Spatial Resolution ◽  
Personal Computer ◽  
Systematic Study ◽  
Present Author ◽  
Chemical Elements ◽  
Detection Limits ◽  
Research Groups ◽  
Quantitative Performance ◽  
Spectrum Imaging

As interest for parallel EELS spectrum imaging grows in laboratories equipped with commercial spectrometers, different approaches were used in recent years by a few research groups in the development of the technique of spectrum imaging as reported in the literature. Either by controlling, with a personal computer both the microsope and the spectrometer or using more powerful workstations interfaced to conventional multichannel analysers with commercially available programs to control the microscope and the spectrometer, spectrum images can now be obtained. Work on the limits of the technique, in terms of the quantitative performance was reported, however, by the present author where a systematic study of artifacts detection limits, statistical errors as a function of desired spatial resolution and range of chemical elements to be studied in a map was carried out The aim of the present paper is to show an application of quantitative parallel EELS spectrum imaging where statistical analysis is performed at each pixel and interpretation is carried out using criteria established from the statistical analysis and variations in composition are analyzed with the help of information retreived from t/γ maps so that artifacts are avoided.

Intraindividual Variability in Development Within and Between Individuals

2001 ◽  
Vol 6 (3) ◽  
pp. 187-193 ◽  
Author(s):  
John R. Nesselroade
Keyword(s):  
Statistical Analysis ◽  
Research Design ◽  
Intraindividual Variability ◽  
Factor Analytic

A focus on the study of development and other kinds of changes in the whole individual has been one of the hallmarks of research by Magnusson and his colleagues. A number of different approaches emphasize this individual focus in their respective ways. This presentation focuses on intraindividual variability stemming from Cattell's P-technique factor analytic proposals, making several refinements to make it more tractable from a research design standpoint and more appropriate from a statistical analysis perspective. The associated methods make it possible to study intraindividual variability both within and between individuals. An empirical example is used to illustrate the procedure.

Review of Basic FORTRAN for Statistical Analysis.

1967 ◽  
Vol 12 (9) ◽  
pp. 467-467
Author(s):  
JOHN C. LOEHLIN
Keyword(s):  
Statistical Analysis
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