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Monitoring Environmental Risk by a Methodology Based on Control Charts · Study

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ChapterMonitoring Environmental Risk by a Methodology Based on Control Charts

Helton Saulo2015

Chapter2015

Monitoring Environmental Risk by a Methodology Based on Control Charts

Helton Saulo · Víctor Leiva · Fabrizio Ruggeri

13 citations·0/0 files stored·Springer proceedings in mathematics & statistics

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Advanced Statistical Process Monitoring Statistical Distribution Estimation and Applications Fault Detection and Control Systems

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References

2006The Use of Control Charts in Health-Care and Public-Health Surveillance 2007Acceptance Sampling Plans from Truncated Life Tests Based on the Generalized Birnbaum–Saunders Distribution 2009Acceptance Sampling Plans from Truncated Life Tests Based on the Birnbaum–Saunders Distribution for Percentiles 2014Capability indices for Birnbaum–Saunders processes applied to electronic and food industries 2010The Birnbaum–Saunders autoregressive conditional duration model 2008A bootstrap control chart for Birnbaum–Saunders percentiles 2014A family of autoregressive conditional duration models applied to financial data 2008The Use of Control Charts to Interpret Environmental Monitoring Data

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2015A criterion for environmental assessment using Birnbaum–Saunders attribute control chartsarticle · 4 shared references 2015Exploring the Potential Use of the Birnbaum-Saunders Distribution in Inventory Managementarticle · 4 shared references 2014A family of autoregressive conditional duration models applied to financial dataarticle · 3 shared references 2017Birnbaum–Saunders autoregressive conditional duration models applied to high-frequency financial dataarticle · 3 shared references 2015Optimization of Contribution Margins in Food Services by Modeling Independent Component Demandarticle · 3 shared references 2016An Attribute Control Chart Based on the Birnbaum-Saunders Distribution Using Repetitive Samplingarticle · 3 shared references

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Year2015

Typechapter

Published2015-01-01

VenueSpringer proceedings in mathematics & statistics

ISSN-L2194-1009

Languageen

Citations13

Files0 public / 0

ShelfAdvanced Statistical Process Monitoring

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doi10.1007/978-3-319-18029-8_14

openalex_workW967028616

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