The New Odd Log-Logistic Generalized Inverse Gaussian Regression Model
Joint Authors
Cordeiro, Gauss M.
Souza Vasconcelos, Julio Cezar
Araújo, Elton G.
Ortega, Edwin M. M.
Source
Journal of Probability and Statistics
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-01-10
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
We define a new four-parameter model called the odd log-logistic generalized inverse Gaussian distribution which extends the generalized inverse Gaussian and inverse Gaussian distributions.
We obtain some structural properties of the new distribution.
We construct an extended regression model based on this distribution with two systematic structures, which can provide more realistic fits to real data than other special regression models.
We adopt the method of maximum likelihood to estimate the model parameters.
In addition, various simulations are performed for different parameter settings and sample sizes to check the accuracy of the maximum likelihood estimators.
We provide a diagnostics analysis based on case-deletion and quantile residuals.
Finally, the potentiality of the new regression model to predict price of urban property is illustrated by means of real data.
American Psychological Association (APA)
Souza Vasconcelos, Julio Cezar& Cordeiro, Gauss M.& Ortega, Edwin M. M.& Araújo, Elton G.. 2019. The New Odd Log-Logistic Generalized Inverse Gaussian Regression Model. Journal of Probability and Statistics،Vol. 2019, no. 2019, pp.1-13.
https://search.emarefa.net/detail/BIM-1186878
Modern Language Association (MLA)
Souza Vasconcelos, Julio Cezar…[et al.]. The New Odd Log-Logistic Generalized Inverse Gaussian Regression Model. Journal of Probability and Statistics No. 2019 (2019), pp.1-13.
https://search.emarefa.net/detail/BIM-1186878
American Medical Association (AMA)
Souza Vasconcelos, Julio Cezar& Cordeiro, Gauss M.& Ortega, Edwin M. M.& Araújo, Elton G.. The New Odd Log-Logistic Generalized Inverse Gaussian Regression Model. Journal of Probability and Statistics. 2019. Vol. 2019, no. 2019, pp.1-13.
https://search.emarefa.net/detail/BIM-1186878
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1186878