Persistent Link:
http://hdl.handle.net/10150/596393
Title:
Analysis of Covariance with Linear Regression Error Model on Antenna Control Unit Tracking
Author:
Laird, Daniel T.
Issue Date:
2015-10
Rights:
Copyright © held by the author; distribution rights International Foundation for Telemetering
Collection Information:
Proceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection.
Publisher:
International Foundation for Telemetering
Journal:
International Telemetering Conference Proceedings
Abstract:
Over the past several years DoD imposed constraints on test deliverables, requiring objective measures of test results, i.e., statistically defensible test and evaluation (SDT&E) methods and results. These constraints force the tester to employ statistical hypotheses, analyses and perhaps modeling to assess test results objectively, i.e., based on statistical metrics, probability of confidence and logical inference to supplement rather than rely solely on expertise, which is too subjective. Experts often disagree on interpretation. Numbers, although interpretable, are less variable than opinion. Logic, statistical inference and belief are the bases of testable, repeatable and refutable hypothesis and analyses. In this paper we apply linear regression modeling and analysis of variance (ANOVA) to time-space position information (TSPI) to determine if a telemetry (TM) antenna control unit (ACU) under test (AUT) tracks statistically, thus as efficiently, in C-band while receiving both C- and S-band signals. Together, regression and ANOVA compose a method known as analysis of covariance (ANCOVA). In this, the second of three papers, we use data from a range test, but make no reference to the systems under test, nor to causes of error. The intent is to present examples of tools and techniques useful for SDT&E methodologies in testing.
Keywords:
Null- and alternative-hypotheses; tracking mode; TM; AGC; ACU; Scan rate; Slew rate; TSPI samples; GPS; INS; observables; calculated; dataframe; R; inner-product; modeling; ANOVA; ANCOVA; F-test and t-test; PDF; CDF
Sponsors:
International Foundation for Telemetering
ISSN:
0884-5123; 0074-9079
Additional Links:
http://www.telemetry.org/

Full metadata record

DC FieldValue Language
dc.language.isoen_USen
dc.titleAnalysis of Covariance with Linear Regression Error Model on Antenna Control Unit Trackingen_US
dc.contributor.authorLaird, Daniel T.en
dc.date.issued2015-10en
dc.rightsCopyright © held by the author; distribution rights International Foundation for Telemeteringen
dc.description.collectioninformationProceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection.en
dc.publisherInternational Foundation for Telemeteringen
dc.description.abstractOver the past several years DoD imposed constraints on test deliverables, requiring objective measures of test results, i.e., statistically defensible test and evaluation (SDT&E) methods and results. These constraints force the tester to employ statistical hypotheses, analyses and perhaps modeling to assess test results objectively, i.e., based on statistical metrics, probability of confidence and logical inference to supplement rather than rely solely on expertise, which is too subjective. Experts often disagree on interpretation. Numbers, although interpretable, are less variable than opinion. Logic, statistical inference and belief are the bases of testable, repeatable and refutable hypothesis and analyses. In this paper we apply linear regression modeling and analysis of variance (ANOVA) to time-space position information (TSPI) to determine if a telemetry (TM) antenna control unit (ACU) under test (AUT) tracks statistically, thus as efficiently, in C-band while receiving both C- and S-band signals. Together, regression and ANOVA compose a method known as analysis of covariance (ANCOVA). In this, the second of three papers, we use data from a range test, but make no reference to the systems under test, nor to causes of error. The intent is to present examples of tools and techniques useful for SDT&E methodologies in testing.en
dc.subjectNull- and alternative-hypothesesen
dc.subjecttracking modeen
dc.subjectTMen
dc.subjectAGCen
dc.subjectACUen
dc.subjectScan rateen
dc.subjectSlew rateen
dc.subjectTSPI samplesen
dc.subjectGPSen
dc.subjectINSen
dc.subjectobservablesen
dc.subjectcalculateden
dc.subjectdataframeen
dc.subjectRen
dc.subjectinner-producten
dc.subjectmodelingen
dc.subjectANOVAen
dc.subjectANCOVAen
dc.subjectF-test and t-testen
dc.subjectPDFen
dc.subjectCDFen
dc.description.sponsorshipInternational Foundation for Telemeteringen
dc.identifier.issn0884-5123en
dc.identifier.issn0074-9079en
dc.identifier.urihttp://hdl.handle.net/10150/596393en
dc.identifier.journalInternational Telemetering Conference Proceedingsen
dc.typetexten
dc.typeProceedingsen
dc.relation.urlhttp://www.telemetry.org/en
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