General methods for analyzing bounded proportion data

This thesis introduces two general classes of models for analyzing proportion response variable when the response variable Y can take values between zero and one, inclusive of zero and/or one. The models are inflated GAMLSS model and generalized Tobit GAMLSS model. The inflated GAMLSS model extends...

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Main Author: Hossain, Abu
Format: Thesis
Language:English
Published: 2017
Subjects:
Online Access:https://repository.londonmet.ac.uk/1243/1/Abu%20Munsar%20Hossain%20-%20PhD%20Final%20full%20thesis.pdf
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author Hossain, Abu
author_facet Hossain, Abu
author_sort Hossain, Abu
collection LMU
description This thesis introduces two general classes of models for analyzing proportion response variable when the response variable Y can take values between zero and one, inclusive of zero and/or one. The models are inflated GAMLSS model and generalized Tobit GAMLSS model. The inflated GAMLSS model extends the flexibility of beta inflated models by allowing the distribution on (0,1) of the continuous component of the dependent variable to come from any explicit or transformed (i.e. logit or truncated) distribution on (0,1) including highly skewed and/or kurtotic or bimodal distributions. The second proposed general class of model is the generalized Tobit GAMLSS model. The generalized Tobit GAMLSS model relaxes the underlying normal distribution assumption of the latent variable in the Tobit model to a very general class of distribution on the real line. The thesis also provides likelihood inference and diagnostic and model selection tools for these classes of models. Applications of both the models are conducted using different sets of data to check the robustness of the proposed models. The originality of the thesis starts from chapter 4 and in particular chapter 5, 6 and 7 with applications of models in chapter 8, 9 and 10.
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spelling oai:repository.londonmet.ac.uk:12432019-05-08T08:48:39Z https://repository.londonmet.ac.uk/1243/ General methods for analyzing bounded proportion data Hossain, Abu 330 Economics 510 Mathematics This thesis introduces two general classes of models for analyzing proportion response variable when the response variable Y can take values between zero and one, inclusive of zero and/or one. The models are inflated GAMLSS model and generalized Tobit GAMLSS model. The inflated GAMLSS model extends the flexibility of beta inflated models by allowing the distribution on (0,1) of the continuous component of the dependent variable to come from any explicit or transformed (i.e. logit or truncated) distribution on (0,1) including highly skewed and/or kurtotic or bimodal distributions. The second proposed general class of model is the generalized Tobit GAMLSS model. The generalized Tobit GAMLSS model relaxes the underlying normal distribution assumption of the latent variable in the Tobit model to a very general class of distribution on the real line. The thesis also provides likelihood inference and diagnostic and model selection tools for these classes of models. Applications of both the models are conducted using different sets of data to check the robustness of the proposed models. The originality of the thesis starts from chapter 4 and in particular chapter 5, 6 and 7 with applications of models in chapter 8, 9 and 10. 2017-06 Thesis NonPeerReviewed text en https://repository.londonmet.ac.uk/1243/1/Abu%20Munsar%20Hossain%20-%20PhD%20Final%20full%20thesis.pdf Hossain, Abu (2017) General methods for analyzing bounded proportion data. Doctoral thesis, London Metropolitan University.
spellingShingle 330 Economics
510 Mathematics
Hossain, Abu
General methods for analyzing bounded proportion data
title General methods for analyzing bounded proportion data
title_full General methods for analyzing bounded proportion data
title_fullStr General methods for analyzing bounded proportion data
title_full_unstemmed General methods for analyzing bounded proportion data
title_short General methods for analyzing bounded proportion data
title_sort general methods for analyzing bounded proportion data
topic 330 Economics
510 Mathematics
url https://repository.londonmet.ac.uk/1243/1/Abu%20Munsar%20Hossain%20-%20PhD%20Final%20full%20thesis.pdf
work_keys_str_mv AT hossainabu generalmethodsforanalyzingboundedproportiondata