- Bias in parametric estimation: reduction and useful side-effects. Kosmidis, I. (2014). WIRE Computational Statistics, 6, 185-196 (also available at ArXiv e-prints, arXiv:1311.6311).
- Improved estimation in cumulative link models. Kosmidis, I. (2014). Journal of the Royal Statistical Society: Series B, 76, 169-196 (also available at ArXiv e-prints, arXiv:1204.0105).
- Extended Beta regression in R: Shaken, stirred, mixed, and partitioned. Grün, B., Kosmidis, I. and Zeileis, A. (2012). Journal of Statistical Software, 48, 11.
- Multinomial logit bias reduction via the Poisson log-linear model. Kosmidis, I., Firth, D. (2011). Biometrika, 98, 755-759.
- Simulating events of unknown probabilities via reverse time martingales. Latuszynski, K., Kosmidis, I., Papaspiliopoulos, O. and Roberts, G. O. (2011). Random Structures and Algorithms, 38, 441-452.
- A generic algorithm for reducing bias in parametric estimation. Kosmidis, I., Firth, D. (2010). Electronic Journal of Statistics, 4, 1097-1112. Relevant R Code and an example are available here .
- Bias reduction in exponential family nonlinear models. Kosmidis, I., Firth, D. (2009). Biometrika, 96, 793-804.
- The profileModel R package: Profiling objectives for models with linear predictors. Kosmidis, I. (2008). R News, 8/2, 12-18, R Foundation for Statistical Computing.
- Model-based clustering using copulas with applications. Kosmidis, I. and Karlis, D. (2014). ArXiv e-prints, arXiv:1404.4077.
- Liquidity commonality does not imply liquidity resilience commonality: A functional characterisation for ultra-high frequency cross-sectional LOB data. Panayi, E., Peters, G. W., Kosmidis, I. (2014). ArXiv e-prints, arXiv:1406.5486.
- Upside and downside risk exposures of currency carry trades via tail dependence. Ames, M., Peters, G. W., Bagnarosa, G. and Kosmidis, I. (2014). ArXiv e-prints, arXiv:1406.4322.
- Supervised sampling for clustering large data sets. Kosmidis, I., Karlis, D. (2010). CRiSM working paper 10-10.
- On iterative adjustment of responses for the reduction of bias in binary regression models. Kosmidis, I. (2009). CRiSM working paper 09-36.
- Bias reduction in exponential family nonlinear models (August 2007, Department of Statistics, University of Warwick)
- Reduced-bias inference for multi-dimensional Rasch models with applications . 28th International Workshop on Statistical Modelling, Palermo, Italy, July 2013.
- brglm: Bias reduction in generalized linear models . useR! 2011, Coventry, UK, August 2011.
- Bias reduction in generalized nonlinear models . Joint Statistical Meetings 2009, Washington, DC, 2009.
- On iterative adjustment of the responses for the reduction of bias in binary regression models . 24th International Workshop on Statistical Modelling , Ithaka, NY, July 2009.
- Reduction of bias in exponential family models with emphasis on models for categorical responses . University of Padua, Italy, May 2009.
- Profiling the parameters of models with linear predictors . useR 2008, Dortmund, Germany, August 2008.
Below is a list of titles that I am highly interested in and I would be keen to research collaborating with a PhD student. Please contact me if you are interested on any of those to discuss or even arrange for a meeting. My contact details can be found here.
Optimal estimation and inference
- Inference for models with many nuisance parameters.
- Improved estimation for generalized linear mixed effects models.
- The bias of functional estimators.
- Estimation and inference for generalized linear models from big data sets.
Mixture models and applications
- Model-based image segmentation with covariates.
- Automatic identification of cell populations from flow-cytometry data.
Applications in Sports
- Models for predicting "performance" in Sports.
The above list is certainly not exhaustive; if you have something else in mind and you are interested in working with me I would be more than happy to discuss.