Omiros Papaspiliopoulos : Citation Profile


Are you Omiros Papaspiliopoulos?

Barcelona Graduate School of Economics (Barcelona GSE)

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H index

5

i10 index

152

Citations

RESEARCH PRODUCTION:

6

Articles

RESEARCH ACTIVITY:

   7 years (2004 - 2011). See details.
   Cites by year: 21
   Journals where Omiros Papaspiliopoulos has often published
   Relations with other researchers
   Recent citing documents: 10.    Total self citations: 4 (2.56 %)

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ABOUT THIS REPORT:

   Permalink: http://citec.repec.org/ppa697
   Updated: 2021-04-17    RAS profile: 2011-05-25    
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Relations with other researchers


Works with:

Authors registered in RePEc who have co-authored more than one work in the last five years with Omiros Papaspiliopoulos.

Is cited by:

Kalogeropoulos, Konstantinos (7)

Liu, Laura (6)

Galeano, Pedro (5)

Sørensen, Michael (5)

Dellaportas, Petros (5)

Chopin, Nicolas (4)

Griffin, Jim (4)

Forbes, Catherine (4)

Steel, Mark (4)

Martin, Gael (4)

Veraart, Almut (3)

Cites to:

Gallant, A. (2)

Kalogeropoulos, Konstantinos (1)

Kim, Chang-Jin (1)

Singleton, Kenneth (1)

Barndorff-Nielsen, Ole (1)

Hamilton, James (1)

yi, li (1)

Shephard, Neil (1)

Duffie, Darrell (1)

Main data


Where Omiros Papaspiliopoulos has published?


Journals with more than one article published# docs
Journal of the Royal Statistical Society Series B5

Recent works citing Omiros Papaspiliopoulos (2021 and 2020)


YearTitle of citing document
2020Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective. (2018). Liu, Laura. In: Papers. RePEc:arx:papers:1805.04178.

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2020Forecasting with Bayesian Grouped Random Effects in Panel Data. (2020). Zhang, Boyuan. In: Papers. RePEc:arx:papers:2007.02435.

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2020On the inferential implications of decreasing weight structures in mixture models. (2020). Prunster, Igor ; Mena, Ramses H ; Martinez, Asael Fabian ; De Blasi, Pierpaolo . In: Computational Statistics & Data Analysis. RePEc:eee:csdana:v:147:y:2020:i:c:s0167947320300311.

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2020Bayesian nonparametric clustering as a community detection problem. (2020). Tonellato, Stefano F. In: Computational Statistics & Data Analysis. RePEc:eee:csdana:v:152:y:2020:i:c:s0167947320301353.

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2020A Bayesian nonparametric model and its application in insurance loss prediction. (2020). Meng, Shengwang ; Huang, Yifan. In: Insurance: Mathematics and Economics. RePEc:eee:insuma:v:93:y:2020:i:c:p:84-94.

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2020Application of iterated filtering to stochastic volatility models based on non-Gaussian Ornstein-Uhlenbeck process. (2020). Szczepocki, Piotr. In: Statistics in Transition New Series. RePEc:exl:29stat:v:21:y:2020:i:2:p:173-187.

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2020Identifying latent subgroups of children with developmental delay using Bayesian sequential updating and Dirichlet process mixture modelling. (2020). Thompson, Helen ; Mengersen, Kerrie ; Gilholm, Patricia. In: PLOS ONE. RePEc:plo:pone00:0233542.

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2020A Bayesian Signals Approach for the Detection of Crises. (2020). Michaelides, Panayotis ; Xidonas, Panos ; Tsionas, Mike. In: Journal of Quantitative Economics. RePEc:spr:jqecon:v:18:y:2020:i:3:d:10.1007_s40953-019-00186-8.

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2020Optimal control for estimation in partially observed elliptic and hypoelliptic linear stochastic differential equations. (2020). Samson, Adeline ; Clairon, Quentin. In: Statistical Inference for Stochastic Processes. RePEc:spr:sistpr:v:23:y:2020:i:1:d:10.1007_s11203-019-09199-9.

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2020Bayesian nonparametric estimation of first passage distributions in semi‐Markov processes. (2020). Warr, Richard L ; Woodfield, Travis B. In: Applied Stochastic Models in Business and Industry. RePEc:wly:apsmbi:v:36:y:2020:i:2:p:237-250.

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Works by Omiros Papaspiliopoulos:


YearTitleTypeCited
2004Bayesian inference for non‐Gaussian Ornstein–Uhlenbeck stochastic volatility processes In: Journal of the Royal Statistical Society Series B.
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article37
2006Exact and computationally efficient likelihood‐based estimation for discretely observed diffusion processes (with discussion) In: Journal of the Royal Statistical Society Series B.
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article51
2008Particle filters for partially observed diffusions In: Journal of the Royal Statistical Society Series B.
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article11
2010Random‐weight particle filtering of continuous time processes In: Journal of the Royal Statistical Society Series B.
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article0
2011Bayesian non‐parametric hidden Markov models with applications in genomics In: Journal of the Royal Statistical Society Series B.
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article14
2008Retrospective Markov chain Monte Carlo methods for Dirichlet process hierarchical models In: Biometrika.
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article39

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