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Modelling Inverse Gaussian Data with Censored Response Values : EM versus MCMC
Joint Authors
Ormerod, J. T.
Toscas, P.
Sutton, G.
Sparks, R. S.
Source
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-07-05
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Economics & Business Administration
Business Administration
Abstract EN
Low detection limits are common in measure environmental variables.
Building models using data containing low or high detection limits without adjusting for the censoring produces biased models.
This paper offers approaches to estimate an inverse Gaussian distribution when some of the data used are censored because of low or high detection limits.
Adjustments for the censoring can be made if there is between 2% and 20% censoring using either the EM algorithm or MCMC.
This paper compares these approaches.
American Psychological Association (APA)
Sparks, R. S.& Sutton, G.& Toscas, P.& Ormerod, J. T.. 2011. Modelling Inverse Gaussian Data with Censored Response Values : EM versus MCMC. Advances in Decision Sciences،Vol. 2011, no. 2011, pp.1-8.
https://search.emarefa.net/detail/BIM-481703
Modern Language Association (MLA)
Sparks, R. S.…[et al.]. Modelling Inverse Gaussian Data with Censored Response Values : EM versus MCMC. Advances in Decision Sciences No. 2011 (2011), pp.1-8.
https://search.emarefa.net/detail/BIM-481703
American Medical Association (AMA)
Sparks, R. S.& Sutton, G.& Toscas, P.& Ormerod, J. T.. Modelling Inverse Gaussian Data with Censored Response Values : EM versus MCMC. Advances in Decision Sciences. 2011. Vol. 2011, no. 2011, pp.1-8.
https://search.emarefa.net/detail/BIM-481703
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-481703