Using a non-homogeneous Poisson model with spatial anisotropy and change-points to study air pollution data-Reference-Cited by-同舟云学术

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Using a non-homogeneous Poisson model with spatial anisotropy and change-points to study air pollution data

Published:2019-06 Issue:2 Volume:26 Page:153-184
ISSN:1352-8505
Container-title:Environmental and Ecological Statistics
language:en
Short-container-title:Environ Ecol Stat

Author:

Rodrigues Eliane R.,Nicholls Geoff,Tarumoto Mario H.,Tzintzun Guadalupe

Funder

Direccion General de Apoyo al Personal Academico - Universidad Nacional Autonoma de Mexico

Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México

Publisher

Springer Science and Business Media LLC

Subject

Statistics, Probability and Uncertainty,General Environmental Science,Statistics and Probability

Link

http://link.springer.com/content/pdf/10.1007/s10651-019-00423-6.pdf

Reference57 articles.

1. Achcar JA, Fernández-Bremauntz AA, Rodrigues ER, Tzintzun G (2008) Estimating the number of ozone peaks in Mexico City using a non-homogeneous Poisson model. Environmetrics 19:469–485. https://doi.org/10.1002/env.890

2. Achcar JA, Rodrigues ER, Paulino CD, Soares P (2010) Non-homogeneous Poisson processes with a change-point: an application to ozone exceedances in Mexico City. Environ Ecol Stat 17:521–541

3. Achcar JA, Rodrigues ER, Tzintzun G (2011a) Using non-homogeneous Poisson models with multiple change-points to estimate the number of ozone exceedances in Mexico City. Environmetrics 22:1–12. https://doi.org/10.1002/env.1029

4. Achcar JA, Rodrigues ER, Tzintzun G (2011b) Using stochastic volatility models to analyse weekly ozone averages in Mexico City. Environ Ecol Stat 18:271–290. https://doi.org/10.1007/s10651-010-0132-1

5. Álvarez LJ, Fernández-Bremauntz AA, Rodrigues ER, Tzintzun G (2005) Maximum a posteriori estimation of the daily ozone peaks in Mexico City. J Agric Biol Environ Stat 10:276–290. https://doi.org/10.1198/108571105X5917

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1. State‐space prior distribution for parameter of nonhomogeneous Poisson spatiotemporal models;Biometrical Journal;2023-07-09

2. Distribution-free changepoint detection tests based on the breaking of records;Environmental and Ecological Statistics;2022-07-06

3. Spatiotemporal nonhomogeneous poisson model with a seasonal component applied to the analysis of extreme rainfall;Journal of Applied Statistics;2022-04-21

4. An application of a non-homogeneous Poisson model to study PM2.5 exceedances in Mexico City and Bogota;Journal of Applied Statistics;2021-03-09

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