Data snooping in deformation surveys

The use of least squares estimation methods to provide accurate and reliable results in the analysis of deformation monitoring networks requires observational data that is random in nature. This necessities the elimination of all blunders to ensure that the data follows a normal distribution. The el...

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Main Author: Mansor, Shattri
Format: Article
Language:English
Online Access:http://psasir.upm.edu.my/id/eprint/39033/1/Data%20snooping%20in%20deformation%20surveys.pdf
http://psasir.upm.edu.my/id/eprint/39033/
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Institution: Universiti Putra Malaysia
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spelling my.upm.eprints.390332015-07-07T03:31:45Z http://psasir.upm.edu.my/id/eprint/39033/ Data snooping in deformation surveys Mansor, Shattri The use of least squares estimation methods to provide accurate and reliable results in the analysis of deformation monitoring networks requires observational data that is random in nature. This necessities the elimination of all blunders to ensure that the data follows a normal distribution. The elimination of gross errors from observations is a complex problem, which may be solved in various ways i.e . by application of observational methods designed to prevent the occurrence of blunders; by safeguarding against erroneous data transfer; by testing the functional conditions which the observations in question must satisfy (eg. the sum of angles in a triangle must be 180 degrees); and finally by detection of blunders through statistical analysis of post-adjustments. A brief overview of the reliability in network design is given before investigating the statistic of residuals and method of data snooping. Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/39033/1/Data%20snooping%20in%20deformation%20surveys.pdf Mansor, Shattri Data snooping in deformation surveys. The Surveyor. pp. 16-18.
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description The use of least squares estimation methods to provide accurate and reliable results in the analysis of deformation monitoring networks requires observational data that is random in nature. This necessities the elimination of all blunders to ensure that the data follows a normal distribution. The elimination of gross errors from observations is a complex problem, which may be solved in various ways i.e . by application of observational methods designed to prevent the occurrence of blunders; by safeguarding against erroneous data transfer; by testing the functional conditions which the observations in question must satisfy (eg. the sum of angles in a triangle must be 180 degrees); and finally by detection of blunders through statistical analysis of post-adjustments. A brief overview of the reliability in network design is given before investigating the statistic of residuals and method of data snooping.
format Article
author Mansor, Shattri
spellingShingle Mansor, Shattri
Data snooping in deformation surveys
author_facet Mansor, Shattri
author_sort Mansor, Shattri
title Data snooping in deformation surveys
title_short Data snooping in deformation surveys
title_full Data snooping in deformation surveys
title_fullStr Data snooping in deformation surveys
title_full_unstemmed Data snooping in deformation surveys
title_sort data snooping in deformation surveys
url http://psasir.upm.edu.my/id/eprint/39033/1/Data%20snooping%20in%20deformation%20surveys.pdf
http://psasir.upm.edu.my/id/eprint/39033/
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