Outputs (2004)

A sensitivity analysis and error bounds for the adaptive lasso (2020)
Presentation / Conference Contribution
Basu, T., Einbeck, J., & Troffaes, M. (2020). A sensitivity analysis and error bounds for the adaptive lasso. In I. Irigoien, D. -. Lee, J. Martinez-Minaya, & M. X. Rodriguez-Alvarez (Eds.), Proceedings of the 35th International Workshop on Statistical Modelling (278-281)

Sparse regression is an efficient statistical modelling technique which is of major relevance for high dimensional problems. There are several ways of achieving sparse regression, the well-known lasso being one of them. However, lasso variable select... Read More about A sensitivity analysis and error bounds for the adaptive lasso.

The Unintended Effects of School Inspection (2014)
Presentation / Conference Contribution
Jones, K., Tymms, P., Kemethofer, D., O’Hara, J., Skedsmo, G., Myrberg, E., & Huber, S. (2014, October). The Unintended Effects of School Inspection. Paper presented at EES, Dublin, Ireland

Box-Cox response transformations for random effect models (2018)
Presentation / Conference Contribution
Almohaimeed, A., & Einbeck, J. (2018). Box-Cox response transformations for random effect models. In Proceedings of the 33rd International Workshop on Statistical Modelling (1-6)

For the linear model with random effects of unspecified distribution, we develop methodology for simultaneous response transformation and estimation of regres- sion parameters. This is achieved by extending the Nonparametric Maximum Likelihood toward... Read More about Box-Cox response transformations for random effect models.

Binary Credal Classification Under Sparsity Constraints (2020)
Presentation / Conference Contribution
Basu, T., Troffaes, M. C., & Einbeck, J. (2020). Binary Credal Classification Under Sparsity Constraints. In M. Lesot, S. Vieira, M. Z. Reformat, J. P. Carvalho, A. Wilbik, B. Bouchon-Meunier, & R. R. Yager (Eds.), Information processing and management of uncertainty in knowledge-based systems : 18th International Conference, IPMU 2020, Lisbon, Portugal, June 15–19, 2020, proceedings, Part II (82-95). https://doi.org/10.1007/978-3-030-50143-3_7

Binary classification is a well known problem in statistics. Besides classical methods, several techniques such as the naive credal classifier (for categorical data) and imprecise logistic regression (for continuous data) have been proposed to handle... Read More about Binary Credal Classification Under Sparsity Constraints.

The unintended consequences of school inspection: the prevalence of inspection side-effects in Austria, the Czech Republic, England, Ireland, the Netherlands, Sweden, and Switzerland (2014)
Presentation / Conference Contribution
Jones, K., Tymms, P., Kemethofer, D., O'Hara, J., McNamara, G., Huber, S., …Gregger, D. (2014). The unintended consequences of school inspection: the prevalence of inspection side-effects in Austria, the Czech Republic, England, Ireland, the Netherlands, Sweden, and Switzerland. . https://doi.org/10.1080/03054985.2017.1352499

The unintended effects of school inspection: evidence from an EU comparative study (2014)
Presentation / Conference Contribution
Tymms, P., & Jones, K. (2014). The unintended effects of school inspection: evidence from an EU comparative study.

Sample quantiles corresponding to mid p-values for zero-modification tests (2017)
Presentation / Conference Contribution
Einbeck, J., & Wilson, P. (2017). Sample quantiles corresponding to mid p-values for zero-modification tests. In M. Grzegorczyk, & G. Ceoldo (Eds.), Proceedings of the 32nd International Workshop on Statistical Modelling : Groningen, Netherlands, 3-7 July, 2017 (275-279)

A non-parametric Bayesian prior for causal inference of auditory streaming (2017)
Presentation / Conference Contribution
Yates, T., Larigaldie, N., & Beierholm, U. (2017). A non-parametric Bayesian prior for causal inference of auditory streaming. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. . J. Davelaar (Eds.), Proceedings of the 39th Annual Conference of the Cognitive Science Society (1381-1386). https://doi.org/10.1101/139188

traditionally been modeled using a mechanistic approach. The problem however is essentially one of source inference – a problem that has recently been tackled using statistical Bayesian models in visual and auditory-visual modalities. Usually the mod... Read More about A non-parametric Bayesian prior for causal inference of auditory streaming.

Con fidence intervals for posterior intercepts, with application to the PIAAC literacy survey (2017)
Presentation / Conference Contribution
Einbeck, J., Gray, E., Sofroniou, N., Marques da Silva Junior, A., & Gledhill, J. (2017). Con fidence intervals for posterior intercepts, with application to the PIAAC literacy survey. In M. Grzegorczyk, & G. Ceoldo (Eds.), Proceedings of the 32nd International Workshop on Statistical Modelling : Groningen, Netherlands, 3-7 July, 2017 (217-222)

For variance component models, it is often the posterior estimate of the random effect (‘posterior intercept’) rather than the estimate of the fixed effect parameters, which is of main interest. This is the case, for instance, when ranking region–wis... Read More about Con fidence intervals for posterior intercepts, with application to the PIAAC literacy survey.

On statistical testing and mean parameter estimation for zero-modification in count data regression (2016)
Presentation / Conference Contribution
Wilson, P., & Einbeck, J. (2016). On statistical testing and mean parameter estimation for zero-modification in count data regression. In J. F. Dupuy, & J. Josse (Eds.), Proceedings of the 31st International Workshop on Statistical Modelling. July 4-8, 2016, Rennes, France (327-332)

For the problem of testing for zero-modification in Poisson regression, a simple and intuitive test can be constructed by computing directly confidence intervals for the number of 0's under the Poisson assumption. This requires the ability of estimat... Read More about On statistical testing and mean parameter estimation for zero-modification in count data regression.

Gradient test for generalised linear models with random effects (2016)
Presentation / Conference Contribution
da Silva-Junior, A., Einbeck, J., & Craig, P. (2016). Gradient test for generalised linear models with random effects. In J. F. Dupuy, & J. Josse (Eds.), Proceedings of the 31st International Workshop on Statistical Modelling. July 4-8, 2016, Rennes, France (213-218)

This work develops the gradient test for parameter selection in generalised linear models with random effects. Asymptotically, the test statistic has a chi-squared distribution and the statistic has a compelling feature: it does not require computati... Read More about Gradient test for generalised linear models with random effects.

Comparing Bayesian models for multisensory cue combination without mandatory integration (2008)
Presentation / Conference Contribution
Beierholm, U., Kording, K., Shams, L., & Ma, W. (2008). Comparing Bayesian models for multisensory cue combination without mandatory integration. In J. C. Platt, D. Koller, Y. Singer, & S. T. Roweis (Eds.), Advances in neural information processing systems 20: Proceedings of the 21st Annual Conference on Neural Information Processing Systems 2007; December 3-6, 2007, Vancouver, B.C., Canada (81-88)

Bayesian models of multisensory perception traditionally address the problem of estimating an underlying variable that is assumed to be the cause of the two sensory signals. The brain, however, has to solve a more general problem: it also has to esta... Read More about Comparing Bayesian models for multisensory cue combination without mandatory integration.

A diagnostic plot for assessing model fit in count data models (2016)
Presentation / Conference Contribution
Einbeck, J., & Wilson, P. (2016). A diagnostic plot for assessing model fit in count data models. In J. F. Dupuy, & J. Josse (Eds.), Proceedings of the 31st International Workshop on Statistical Modelling. July 4-8, 2016, Rennes, France (103-108)

Whilst many numeric methods, such as AIC and deviance, exist for assessing model fit, diagrammatic methods are few. We present here a diagnostic plot, to which we refer as `Christmas tree plot' due its characteristic shape, that may be used to visual... Read More about A diagnostic plot for assessing model fit in count data models.

A systematic review of methods to assess metacognition in school‐aged children. Paper presented at symposium entitled Metacognition, executive functioning and self‐regulation: measurement tools from infancy to adolescence (2014)
Presentation / Conference Contribution
Gascoine, L., Higgins, S., & Wall, K. (2014). A systematic review of methods to assess metacognition in school‐aged children. Paper presented at symposium entitled Metacognition, executive functioning and self‐regulation: measurement tools from infancy to adolescence.

A simple and intuitive test for number-inflation or number-deflation (2015)
Presentation / Conference Contribution
Wilson, P., & Einbeck, J. (2015). A simple and intuitive test for number-inflation or number-deflation. In H. Wagner, & H. Friedl (Eds.), Proceedings of the 30th International Workshop on Statistical Modelling. Linz, Austria, 6-10 July 2015 (299-302)

We present a test of zero-modification which checks if the number of zeros is consistent with the hypothesized count distribution. This test is easily extended to test for inflation or deflation of any non-negative values, and, by performing multiple... Read More about A simple and intuitive test for number-inflation or number-deflation.

The Tools of Teacher Evaluation: What Should Be Used in Teacher Evaluation from the Teachers’ Perspective (2015)
Presentation / Conference Contribution
Almutairi, T., Tymms, P., & Kind, P. (2015). The Tools of Teacher Evaluation: What Should Be Used in Teacher Evaluation from the Teachers’ Perspective.

This paper presents a study that was conducted to investigate the tools of teacher evaluation. The focus is on what teachers state about such tools in terms of what should be used when they are evaluated. Teachers were asked by questionnaire about th... Read More about The Tools of Teacher Evaluation: What Should Be Used in Teacher Evaluation from the Teachers’ Perspective.

A study of online and blockwise updating of the EM algorithm for Gaussian mixtures (2014)
Presentation / Conference Contribution
Einbeck, J., & Bonetti, D. (2014). A study of online and blockwise updating of the EM algorithm for Gaussian mixtures. In T. Kneib, F. Sobotka, J. Fahrenholz, & H. Irmer (Eds.), 29th International Workshop on Statistical Modelling, 14-18 July 2014, Göttingen, Germany ; proceedings (35-38)

A variant of the EM algorithm for the estimation of multivariate Gaussian mixtures, which allows for online as well as blockwise updating of sequentially obtained parameter estimates, is investigated. Several dierent update schemes are considered and... Read More about A study of online and blockwise updating of the EM algorithm for Gaussian mixtures.

Bayesian shape modelling of cross-sectional geological data (2014)
Presentation / Conference Contribution
Tsiftsi, T., Jermyn, I., & Einbeck, J. (2014). Bayesian shape modelling of cross-sectional geological data. In K. Thomas, S. Fabian, F. Jan, & I. Henriette (Eds.), 29th International Workshop on Statistical Modelling, 14-18 July 2014, Göttingen, Germany ; proceedings (161-164)

Shape information is of great importance in many applications. For example, the oil-bearing capacity of sand bodies, the subterranean remnants of ancient rivers, is related to their cross-sectional shapes. The analysis of these shapes is therefore of... Read More about Bayesian shape modelling of cross-sectional geological data.

Bivariate Estimation of Distribution Algorithms for Protein Structure Prediction (2014)
Presentation / Conference Contribution
Bonetti, D., Delbem, A., & Einbeck, J. (2014). Bivariate Estimation of Distribution Algorithms for Protein Structure Prediction. In T. Kneib, F. Sobotka, J. Fahrenholz, & H. Irmer (Eds.), 29th International Workshop on Statistical Modelling, 14-18 July 2014, Göttingen, Germany ; proceedings (15-18)

A real-valued bivariate ‘Estimation of Distribution Algorithm’ specific for the ab initio and full-atom Protein Structure Prediction problem is proposed. It is known that this is a multidimensional and multimodal problem. In order to deal with the mu... Read More about Bivariate Estimation of Distribution Algorithms for Protein Structure Prediction.

Penalized regression on principal manifolds with application to combustion modelling (2012)
Presentation / Conference Contribution
Einbeck, J., Isaac, B., Evers, L., & Parente, A. (2012). Penalized regression on principal manifolds with application to combustion modelling. In A. Komarek, & S. Nagy (Eds.), 27th International Workshop on Statistical Modelling, 16-20 July 2012, Prague, Czech Republic ; proceedings (117-122)

For multivariate regression problems featuring strong and non–linear dependency patterns between the involved predictors, it is attractive to reduce the dimension of the estimation problem by approximating the predictor space through a principal surf... Read More about Penalized regression on principal manifolds with application to combustion modelling.