Copula‐based semiparametric models for spatiotemporal data-Reference-Cited by-同舟云学术

Copula‐based semiparametric models for spatiotemporal data

Published:2019-06-17 Issue:4 Volume:75 Page:1156-1167
ISSN:0006-341X
Container-title:Biometrics
language:en
Short-container-title:Biometrics

Author:

Tang Yanlin¹,Wang Huixia J.²,Sun Ying³,Hering Amanda S.⁴

Affiliation:

1. Key Laboratory of Advanced Theory and Application in Statistics and Data Science‐MOE School of Statistics, East China Normal University Shanghai China

2. Department of Statistics George Washington University Washington D.C

3. Computer, Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia

4. Department of Statistical Science Baylor University Waco Texas

Funder

National Science Foundation

National Natural Science Foundation of China

King Abdullah University of Science and Technology

Publisher

Wiley

Subject

Applied Mathematics,General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/biom.13066

Reference40 articles.

1. Efficient pairwise composite likelihood estimation for spatial-clustered data

2. Geostatistical interpolation using copulas

3. Space-Time Data fusion Under Error in Computer Model Output: An Application to Modeling Air Quality

4. Estimation of copula-based semiparametric time series models

5. Efficient estimation of copula-based semiparametric Markov models

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