NDLI: A non-homogeneous skew-Gaussian Bayesian spatial model

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A non-homogeneous skew-Gaussian Bayesian spatial model

Content Provider	Springer Nature Link
Author	Boojari, Hossein Khaledi, Majid Jafari Rivaz, Firoozeh
Copyright Year	2015
Abstract	In spatial statistics, models are often constructed based on some common, but possible restrictive assumptions for the underlying spatial process, including Gaussianity as well as stationarity and isotropy. However, these assumptions are frequently violated in applied problems. In order to simultaneously handle skewness and non-homogeneity (i.e., non-stationarity and anisotropy), we develop the fixed rank kriging model through the use of skew-normal distribution for its non-spatial latent variables. Our approach to spatial modeling is easy to implement and also provides a great flexibility in adjusting to skewed and large datasets with heterogeneous correlation structures. We adopt a Bayesian framework for our analysis, and describe a simple MCMC algorithm for sampling from the posterior distribution of the model parameters and performing spatial prediction. Through a simulation study, we demonstrate that the proposed model could detect departures from normality and, for illustration, we analyze a synthetic dataset of CO $$_2$$ measurements. Finally, to deal with multivariate spatial data showing some degree of skewness, a multivariate extension of the model is also provided.
Starting Page	55
Ending Page	73
Page Count	19
File Format	PDF
ISSN	16182510
Journal	Statistical Methods and Applications
Volume Number	25
Issue Number	1
e-ISSN	1613981X
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2015-08-08
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Non-homogeneous Skew-normal Fixed rank kriging Basis function Latent variable Multivariate spatial data Bayesian analysis Statistics Statistical Theory and Methods Statistics for Business/Economics/Mathematical Finance/Insurance Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Statistics for Life Sciences, Medicine, Health Sciences Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law
Content Type	Text
Resource Type	Article
Subject	Statistics and Probability Statistics, Probability and Uncertainty

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
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7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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